A longitudinal analysis of the privacy paradox
# relevant packages
devtools::install_github("tdienlin/td@v0.0.2.6")
required <- c("GGally", "ggplot2", "lavaan", "lme4", "magrittr",
"MissMech", # attention: pkg is obsolete, needs to be installed manually
"papaja", "psych", "pwr", "MVN", "semTools",
"sjstats", "tidyverse", "td")
# load required libraries
lapply(required, function(x) library(x, character.only = T))
load("data/workspace.RData") In what follows, we report the results of additional analyses that were also calculated. For example, for each measure we also report exploratory factor analyses, first order model solutions, and unconstrained solutions to estimate longitudinal invariance.
1 Measures
1.1 Concerns about online privacy
1.1.1 EFA
# set-up
no <- 0
name <- "pri_con"
d_tmp <- select(d_wide, contains(paste0("t1_", name)), -contains("_m"), -contains("_fs"))
model <- fa.parallel(d_tmp, fa = "fa", fm = "ml")
## Parallel analysis suggests that the number of factors = 3 and the number of components = NAfactan <- fa(d_tmp, fm = "ml", nfactors = model$nfact, rotate = "promax")
print(factan, sort = TRUE, cut = 0.3)## Factor Analysis using method = ml
## Call: fa(r = d_tmp, nfactors = model$nfact, rotate = "promax", fm = "ml")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item ML2 ML1 ML3 h2 u2 com
## t1_pri_con_03 3 0.84 0.65 0.35 1.1
## t1_pri_con_02 2 0.83 0.62 0.38 1.1
## t1_pri_con_05 5 0.57 0.52 0.48 1.3
## t1_pri_con_04 4 0.53 0.65 0.35 1.5
## t1_pri_con_01 1 0.36 0.45 0.55 2.0
## t1_pri_con_09 9 0.89 0.74 0.26 1.1
## t1_pri_con_08 8 0.86 0.73 0.27 1.1
## t1_pri_con_07 7 0.60 0.37 0.70 0.30 1.7
## t1_pri_con_06 6 0.72 0.73 0.27 1.1
##
## ML2 ML1 ML3
## SS loadings 2.40 2.31 1.08
## Proportion Var 0.27 0.26 0.12
## Cumulative Var 0.27 0.52 0.64
## Proportion Explained 0.41 0.40 0.19
## Cumulative Proportion 0.41 0.81 1.00
##
## With factor correlations of
## ML2 ML1 ML3
## ML2 1.00 0.69 0.71
## ML1 0.69 1.00 0.71
## ML3 0.71 0.71 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 3 factors are sufficient.
##
## The degrees of freedom for the null model are 36 and the objective function was 5.18 with Chi Square of 7246
## The degrees of freedom for the model are 12 and the objective function was 0.06
##
## The root mean square of the residuals (RMSR) is 0.02
## The df corrected root mean square of the residuals is 0.03
##
## The harmonic number of observations is 1392 with the empirical chi square 29.4 with prob < 0.0035
## The total number of observations was 1403 with Likelihood Chi Square = 89.1 with prob < 7.3e-14
##
## Tucker Lewis Index of factoring reliability = 0.968
## RMSEA index = 0.068 and the 90 % confidence intervals are 0.055 0.081
## BIC = 2.16
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## ML2 ML1 ML3
## Correlation of (regression) scores with factors 0.93 0.95 0.90
## Multiple R square of scores with factors 0.87 0.90 0.81
## Minimum correlation of possible factor scores 0.75 0.79 0.611.1.2 CFA
1.1.2.1 First-Order Model Unconstrained
model <- '
# create factors
t1_pri_con_f =~ 1*t1_pri_con_01 + t1_pri_con_02 + t1_pri_con_03 + t1_pri_con_04 + t1_pri_con_05 + t1_pri_con_06 + t1_pri_con_07 + t1_pri_con_08 + t1_pri_con_09
t2_pri_con_f =~ 1*t2_pri_con_01 + t2_pri_con_02 + t2_pri_con_03 + t2_pri_con_04 + t2_pri_con_05 + t2_pri_con_06 + t2_pri_con_07 + t2_pri_con_08 + t2_pri_con_09
t3_pri_con_f =~ 1*t3_pri_con_01 + t3_pri_con_02 + t3_pri_con_03 + t3_pri_con_04 + t3_pri_con_05 + t3_pri_con_06 + t3_pri_con_07 + t3_pri_con_08 + t3_pri_con_09
# error covariances
t3_pri_con_01 ~~ t2_pri_con_01 + t1_pri_con_01
t3_pri_con_02 ~~ t2_pri_con_02 + t1_pri_con_02
t3_pri_con_03 ~~ t2_pri_con_03 + t1_pri_con_03
t3_pri_con_04 ~~ t2_pri_con_04 + t1_pri_con_04
t3_pri_con_05 ~~ t2_pri_con_05 + t1_pri_con_05
t3_pri_con_06 ~~ t2_pri_con_06 + t1_pri_con_06
t3_pri_con_07 ~~ t2_pri_con_07 + t1_pri_con_07
t3_pri_con_08 ~~ t2_pri_con_08 + t1_pri_con_08
t3_pri_con_09 ~~ t2_pri_con_09 + t1_pri_con_09
t2_pri_con_01 ~~ t1_pri_con_01
t2_pri_con_02 ~~ t1_pri_con_02
t2_pri_con_03 ~~ t1_pri_con_03
t2_pri_con_04 ~~ t1_pri_con_04
t2_pri_con_05 ~~ t1_pri_con_05
t2_pri_con_06 ~~ t1_pri_con_06
t2_pri_con_07 ~~ t1_pri_con_07
t2_pri_con_08 ~~ t1_pri_con_08
t2_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t1_pri_con_f ~~ t2_pri_con_f + t3_pri_con_f
t2_pri_con_f ~~ t3_pri_con_f
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 101 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 111
##
## Number of observations 1403
## Number of missing patterns 29
##
## Model Test User Model:
##
## Test statistic 2726.529
## Degrees of freedom 294
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 29137.955
## Degrees of freedom 351
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.915
## Tucker-Lewis Index (TLI) 0.899
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -45195.456
## Loglikelihood unrestricted model (H1) -43832.192
##
## Akaike (AIC) 90612.913
## Bayesian (BIC) 91195.260
## Sample-size adjusted Bayesian (BIC) 90842.654
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.077
## 90 Percent confidence interval - lower 0.074
## 90 Percent confidence interval - upper 0.079
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.051
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pri_con_01 1.000 0.728 0.672
## t1_pri_con_02 0.927 0.039 23.800 0.000 0.675 0.675
## t1_pri_con_03 1.103 0.047 23.669 0.000 0.803 0.662
## t1_pri_con_04 1.198 0.043 27.544 0.000 0.872 0.806
## t1_pri_con_05 1.176 0.050 23.621 0.000 0.857 0.669
## t1_pri_con_06 1.226 0.047 25.980 0.000 0.892 0.757
## t1_pri_con_07 1.343 0.050 26.665 0.000 0.978 0.777
## t1_pri_con_08 1.243 0.048 26.133 0.000 0.905 0.767
## t1_pri_con_09 1.115 0.042 26.333 0.000 0.812 0.774
## t2_pri_con_f =~
## t2_pri_con_01 1.000 0.724 0.683
## t2_pri_con_02 0.944 0.039 24.509 0.000 0.684 0.677
## t2_pri_con_03 1.126 0.045 24.972 0.000 0.815 0.682
## t2_pri_con_04 1.192 0.042 28.303 0.000 0.863 0.810
## t2_pri_con_05 1.215 0.050 24.474 0.000 0.879 0.680
## t2_pri_con_06 1.230 0.045 27.083 0.000 0.891 0.770
## t2_pri_con_07 1.395 0.049 28.252 0.000 1.010 0.807
## t2_pri_con_08 1.293 0.047 27.719 0.000 0.936 0.793
## t2_pri_con_09 1.202 0.043 27.945 0.000 0.870 0.801
## t3_pri_con_f =~
## t3_pri_con_01 1.000 0.779 0.716
## t3_pri_con_02 0.949 0.035 27.110 0.000 0.740 0.720
## t3_pri_con_03 1.065 0.040 26.378 0.000 0.830 0.688
## t3_pri_con_04 1.126 0.037 30.533 0.000 0.878 0.826
## t3_pri_con_05 1.108 0.044 25.221 0.000 0.863 0.668
## t3_pri_con_06 1.148 0.040 28.735 0.000 0.895 0.776
## t3_pri_con_07 1.273 0.043 29.592 0.000 0.992 0.797
## t3_pri_con_08 1.194 0.040 29.630 0.000 0.931 0.800
## t3_pri_con_09 1.101 0.038 29.296 0.000 0.858 0.795
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t2_pri_con_01 ~~
## .t3_pri_con_01 0.188 0.018 10.432 0.000 0.188 0.319
## .t1_pri_con_01 ~~
## .t3_pri_con_01 0.198 0.019 10.556 0.000 0.198 0.324
## .t2_pri_con_02 ~~
## .t3_pri_con_02 0.186 0.016 11.324 0.000 0.186 0.351
## .t1_pri_con_02 ~~
## .t3_pri_con_02 0.164 0.016 10.173 0.000 0.164 0.311
## .t2_pri_con_03 ~~
## .t3_pri_con_03 0.405 0.025 16.132 0.000 0.405 0.528
## .t1_pri_con_03 ~~
## .t3_pri_con_03 0.383 0.026 14.928 0.000 0.383 0.481
## .t2_pri_con_04 ~~
## .t3_pri_con_04 0.047 0.012 3.894 0.000 0.047 0.126
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.059 0.013 4.709 0.000 0.059 0.155
## .t2_pri_con_05 ~~
## .t3_pri_con_05 0.381 0.029 13.280 0.000 0.381 0.418
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.402 0.029 13.809 0.000 0.402 0.440
## .t2_pri_con_06 ~~
## .t3_pri_con_06 0.157 0.017 9.272 0.000 0.157 0.293
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.153 0.018 8.736 0.000 0.153 0.274
## .t2_pri_con_07 ~~
## .t3_pri_con_07 0.195 0.018 10.585 0.000 0.195 0.351
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.235 0.020 11.730 0.000 0.235 0.395
## .t2_pri_con_08 ~~
## .t3_pri_con_08 0.166 0.017 9.991 0.000 0.166 0.331
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.175 0.017 10.092 0.000 0.175 0.332
## .t2_pri_con_09 ~~
## .t3_pri_con_09 0.129 0.014 9.247 0.000 0.129 0.301
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.113 0.014 8.049 0.000 0.113 0.259
## .t1_pri_con_01 ~~
## .t2_pri_con_01 0.215 0.019 11.310 0.000 0.215 0.346
## .t1_pri_con_02 ~~
## .t2_pri_con_02 0.191 0.017 11.391 0.000 0.191 0.348
## .t1_pri_con_03 ~~
## .t2_pri_con_03 0.358 0.025 14.190 0.000 0.358 0.450
## .t1_pri_con_04 ~~
## .t2_pri_con_04 0.065 0.013 5.034 0.000 0.065 0.163
## .t1_pri_con_05 ~~
## .t2_pri_con_05 0.358 0.028 12.611 0.000 0.358 0.397
## .t1_pri_con_06 ~~
## .t2_pri_con_06 0.149 0.018 8.377 0.000 0.149 0.262
## .t1_pri_con_07 ~~
## .t2_pri_con_07 0.210 0.019 10.796 0.000 0.210 0.358
## .t1_pri_con_08 ~~
## .t2_pri_con_08 0.141 0.017 8.085 0.000 0.141 0.260
## .t1_pri_con_09 ~~
## .t2_pri_con_09 0.097 0.014 7.036 0.000 0.097 0.225
## t1_pri_con_f ~~
## t2_pri_con_f 0.413 0.027 15.322 0.000 0.783 0.783
## t3_pri_con_f 0.434 0.028 15.608 0.000 0.764 0.764
## t2_pri_con_f ~~
## t3_pri_con_f 0.443 0.028 15.956 0.000 0.785 0.785
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 3.334 0.029 115.127 0.000 3.334 3.078
## .t1_pri_con_02 3.834 0.027 143.391 0.000 3.834 3.835
## .t1_pri_con_03 3.623 0.032 111.778 0.000 3.623 2.989
## .t1_pri_con_04 3.745 0.029 129.436 0.000 3.745 3.460
## .t1_pri_con_05 3.842 0.034 111.938 0.000 3.842 3.002
## .t1_pri_con_06 3.314 0.032 105.186 0.000 3.314 2.812
## .t1_pri_con_07 3.623 0.034 107.747 0.000 3.623 2.880
## .t1_pri_con_08 3.624 0.032 114.843 0.000 3.624 3.070
## .t1_pri_con_09 4.095 0.028 146.054 0.000 4.095 3.905
## .t2_pri_con_01 3.334 0.028 117.727 0.000 3.334 3.146
## .t2_pri_con_02 3.824 0.027 141.720 0.000 3.824 3.787
## .t2_pri_con_03 3.577 0.032 112.037 0.000 3.577 2.994
## .t2_pri_con_04 3.675 0.028 128.972 0.000 3.675 3.448
## .t2_pri_con_05 3.784 0.035 109.118 0.000 3.784 2.925
## .t2_pri_con_06 3.258 0.031 105.352 0.000 3.258 2.818
## .t2_pri_con_07 3.555 0.033 106.315 0.000 3.555 2.842
## .t2_pri_con_08 3.550 0.032 112.492 0.000 3.550 3.007
## .t2_pri_con_09 3.994 0.029 137.529 0.000 3.994 3.675
## .t3_pri_con_01 3.337 0.029 114.707 0.000 3.337 3.068
## .t3_pri_con_02 3.770 0.027 137.192 0.000 3.770 3.669
## .t3_pri_con_03 3.557 0.032 110.186 0.000 3.557 2.947
## .t3_pri_con_04 3.664 0.028 128.933 0.000 3.664 3.448
## .t3_pri_con_05 3.710 0.035 107.098 0.000 3.710 2.872
## .t3_pri_con_06 3.255 0.031 105.623 0.000 3.255 2.824
## .t3_pri_con_07 3.492 0.033 104.929 0.000 3.492 2.806
## .t3_pri_con_08 3.560 0.031 114.458 0.000 3.560 3.061
## .t3_pri_con_09 3.960 0.029 137.133 0.000 3.960 3.668
## t1_pri_con_f 0.000 0.000 0.000
## t2_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 0.643 0.026 24.370 0.000 0.643 0.548
## .t1_pri_con_02 0.544 0.022 24.301 0.000 0.544 0.544
## .t1_pri_con_03 0.825 0.034 24.259 0.000 0.825 0.561
## .t1_pri_con_04 0.411 0.019 21.877 0.000 0.411 0.351
## .t1_pri_con_05 0.904 0.037 24.229 0.000 0.904 0.552
## .t1_pri_con_06 0.592 0.025 23.324 0.000 0.592 0.426
## .t1_pri_con_07 0.626 0.028 22.490 0.000 0.626 0.396
## .t1_pri_con_08 0.574 0.025 22.683 0.000 0.574 0.412
## .t1_pri_con_09 0.440 0.019 22.680 0.000 0.440 0.400
## .t2_pri_con_01 0.600 0.024 24.517 0.000 0.600 0.534
## .t2_pri_con_02 0.552 0.023 24.417 0.000 0.552 0.542
## .t2_pri_con_03 0.764 0.031 24.251 0.000 0.764 0.535
## .t2_pri_con_04 0.391 0.018 22.204 0.000 0.391 0.345
## .t2_pri_con_05 0.901 0.037 24.409 0.000 0.901 0.538
## .t2_pri_con_06 0.544 0.023 23.388 0.000 0.544 0.407
## .t2_pri_con_07 0.546 0.024 22.352 0.000 0.546 0.349
## .t2_pri_con_08 0.518 0.023 22.481 0.000 0.518 0.371
## .t2_pri_con_09 0.424 0.019 22.382 0.000 0.424 0.359
## .t3_pri_con_01 0.576 0.024 24.115 0.000 0.576 0.487
## .t3_pri_con_02 0.509 0.021 23.879 0.000 0.509 0.482
## .t3_pri_con_03 0.768 0.032 24.130 0.000 0.768 0.527
## .t3_pri_con_04 0.359 0.017 21.645 0.000 0.359 0.318
## .t3_pri_con_05 0.923 0.038 24.596 0.000 0.923 0.553
## .t3_pri_con_06 0.528 0.023 23.357 0.000 0.528 0.397
## .t3_pri_con_07 0.565 0.025 22.376 0.000 0.565 0.365
## .t3_pri_con_08 0.486 0.022 22.211 0.000 0.486 0.359
## .t3_pri_con_09 0.429 0.019 22.629 0.000 0.429 0.368
## t1_pri_con_f 0.530 0.038 14.041 0.000 1.000 1.000
## t2_pri_con_f 0.524 0.036 14.435 0.000 1.000 1.000
## t3_pri_con_f 0.607 0.040 15.297 0.000 1.000 1.000reliability(get(paste("fit", name, no, sep = "_")))## t1_pri_con_f t2_pri_con_f t3_pri_con_f
## alpha 0.911 0.918 0.921
## omega 0.911 0.918 0.921
## omega2 0.911 0.918 0.921
## omega3 0.902 0.915 0.920
## avevar 0.533 0.558 0.5671.1.2.2 First-Order Model Constrained
model <- '
# create factors
t1_pri_con_f =~ 1*t1_pri_con_01 + b2*t1_pri_con_02 + b3*t1_pri_con_03 + b4*t1_pri_con_04 + b5*t1_pri_con_05 + b6*t1_pri_con_06 + b7*t1_pri_con_07 + b8*t1_pri_con_08 + b9*t1_pri_con_09
t2_pri_con_f =~ 1*t2_pri_con_01 + b2*t2_pri_con_02 + b3*t2_pri_con_03 + b4*t2_pri_con_04 + b5*t2_pri_con_05 + b6*t2_pri_con_06 + b7*t2_pri_con_07 + b8*t2_pri_con_08 + b9*t2_pri_con_09
t3_pri_con_f =~ 1*t3_pri_con_01 + b2*t3_pri_con_02 + b3*t3_pri_con_03 + b4*t3_pri_con_04 + b5*t3_pri_con_05 + b6*t3_pri_con_06 + b7*t3_pri_con_07 + b8*t3_pri_con_08 + b9*t3_pri_con_09
# error covariances
t3_pri_con_01 ~~ t2_pri_con_01 + t1_pri_con_01
t3_pri_con_02 ~~ t2_pri_con_02 + t1_pri_con_02
t3_pri_con_03 ~~ t2_pri_con_03 + t1_pri_con_03
t3_pri_con_04 ~~ t2_pri_con_04 + t1_pri_con_04
t3_pri_con_05 ~~ t2_pri_con_05 + t1_pri_con_05
t3_pri_con_06 ~~ t2_pri_con_06 + t1_pri_con_06
t3_pri_con_07 ~~ t2_pri_con_07 + t1_pri_con_07
t3_pri_con_08 ~~ t2_pri_con_08 + t1_pri_con_08
t3_pri_con_09 ~~ t2_pri_con_09 + t1_pri_con_09
t2_pri_con_01 ~~ t1_pri_con_01
t2_pri_con_02 ~~ t1_pri_con_02
t2_pri_con_03 ~~ t1_pri_con_03
t2_pri_con_04 ~~ t1_pri_con_04
t2_pri_con_05 ~~ t1_pri_con_05
t2_pri_con_06 ~~ t1_pri_con_06
t2_pri_con_07 ~~ t1_pri_con_07
t2_pri_con_08 ~~ t1_pri_con_08
t2_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t1_pri_con_f ~~ t2_pri_con_f + t3_pri_con_f
t2_pri_con_f ~~ t3_pri_con_f
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 91 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 111
## Number of equality constraints 16
##
## Number of observations 1403
## Number of missing patterns 29
##
## Model Test User Model:
##
## Test statistic 2742.286
## Degrees of freedom 310
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 29137.955
## Degrees of freedom 351
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.916
## Tucker-Lewis Index (TLI) 0.904
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -45203.335
## Loglikelihood unrestricted model (H1) -43832.192
##
## Akaike (AIC) 90596.670
## Bayesian (BIC) 91095.075
## Sample-size adjusted Bayesian (BIC) 90793.295
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.075
## 90 Percent confidence interval - lower 0.072
## 90 Percent confidence interval - upper 0.077
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.052
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pr__01 1.000 0.732 0.674
## t1_pr__02 (b2) 0.942 0.027 35.461 0.000 0.689 0.683
## t1_pr__03 (b3) 1.096 0.032 34.033 0.000 0.802 0.661
## t1_pr__04 (b4) 1.168 0.028 41.826 0.000 0.855 0.799
## t1_pr__05 (b5) 1.164 0.034 33.805 0.000 0.852 0.667
## t1_pr__06 (b6) 1.198 0.031 38.839 0.000 0.877 0.751
## t1_pr__07 (b7) 1.335 0.034 39.462 0.000 0.977 0.777
## t1_pr__08 (b8) 1.242 0.032 39.320 0.000 0.909 0.769
## t1_pr__09 (b9) 1.138 0.029 39.675 0.000 0.833 0.783
## t2_pri_con_f =~
## t2_pr__01 1.000 0.747 0.695
## t2_pr__02 (b2) 0.942 0.027 35.461 0.000 0.703 0.689
## t2_pr__03 (b3) 1.096 0.032 34.033 0.000 0.818 0.684
## t2_pr__04 (b4) 1.168 0.028 41.826 0.000 0.872 0.814
## t2_pr__05 (b5) 1.164 0.034 33.805 0.000 0.869 0.675
## t2_pr__06 (b6) 1.198 0.031 38.839 0.000 0.895 0.772
## t2_pr__07 (b7) 1.335 0.034 39.462 0.000 0.997 0.802
## t2_pr__08 (b8) 1.242 0.032 39.320 0.000 0.928 0.789
## t2_pr__09 (b9) 1.138 0.029 39.675 0.000 0.850 0.792
## t3_pri_con_f =~
## t3_pr__01 1.000 0.754 0.703
## t3_pr__02 (b2) 0.942 0.027 35.461 0.000 0.710 0.703
## t3_pr__03 (b3) 1.096 0.032 34.033 0.000 0.826 0.685
## t3_pr__04 (b4) 1.168 0.028 41.826 0.000 0.881 0.826
## t3_pr__05 (b5) 1.164 0.034 33.805 0.000 0.878 0.675
## t3_pr__06 (b6) 1.198 0.031 38.839 0.000 0.904 0.780
## t3_pr__07 (b7) 1.335 0.034 39.462 0.000 1.007 0.803
## t3_pr__08 (b8) 1.242 0.032 39.320 0.000 0.937 0.804
## t3_pr__09 (b9) 1.138 0.029 39.675 0.000 0.859 0.796
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t2_pri_con_01 ~~
## .t3_pri_con_01 0.188 0.018 10.446 0.000 0.188 0.319
## .t1_pri_con_01 ~~
## .t3_pri_con_01 0.200 0.019 10.654 0.000 0.200 0.327
## .t2_pri_con_02 ~~
## .t3_pri_con_02 0.186 0.016 11.291 0.000 0.186 0.349
## .t1_pri_con_02 ~~
## .t3_pri_con_02 0.165 0.016 10.194 0.000 0.165 0.311
## .t2_pri_con_03 ~~
## .t3_pri_con_03 0.405 0.025 16.146 0.000 0.405 0.528
## .t1_pri_con_03 ~~
## .t3_pri_con_03 0.385 0.026 14.960 0.000 0.385 0.481
## .t2_pri_con_04 ~~
## .t3_pri_con_04 0.047 0.012 3.914 0.000 0.047 0.126
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.061 0.013 4.830 0.000 0.061 0.158
## .t2_pri_con_05 ~~
## .t3_pri_con_05 0.381 0.029 13.287 0.000 0.381 0.418
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.403 0.029 13.825 0.000 0.403 0.441
## .t2_pri_con_06 ~~
## .t3_pri_con_06 0.156 0.017 9.249 0.000 0.156 0.293
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.153 0.017 8.735 0.000 0.153 0.274
## .t2_pri_con_07 ~~
## .t3_pri_con_07 0.193 0.018 10.525 0.000 0.193 0.349
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.232 0.020 11.680 0.000 0.232 0.393
## .t2_pri_con_08 ~~
## .t3_pri_con_08 0.165 0.017 9.970 0.000 0.165 0.330
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.173 0.017 10.032 0.000 0.173 0.331
## .t2_pri_con_09 ~~
## .t3_pri_con_09 0.129 0.014 9.275 0.000 0.129 0.301
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.111 0.014 8.000 0.000 0.111 0.258
## .t1_pri_con_01 ~~
## .t2_pri_con_01 0.213 0.019 11.275 0.000 0.213 0.344
## .t1_pri_con_02 ~~
## .t2_pri_con_02 0.189 0.017 11.345 0.000 0.189 0.347
## .t1_pri_con_03 ~~
## .t2_pri_con_03 0.357 0.025 14.208 0.000 0.357 0.451
## .t1_pri_con_04 ~~
## .t2_pri_con_04 0.065 0.013 5.037 0.000 0.065 0.162
## .t1_pri_con_05 ~~
## .t2_pri_con_05 0.358 0.028 12.614 0.000 0.358 0.396
## .t1_pri_con_06 ~~
## .t2_pri_con_06 0.148 0.018 8.366 0.000 0.148 0.261
## .t1_pri_con_07 ~~
## .t2_pri_con_07 0.209 0.019 10.791 0.000 0.209 0.357
## .t1_pri_con_08 ~~
## .t2_pri_con_08 0.141 0.018 8.073 0.000 0.141 0.259
## .t1_pri_con_09 ~~
## .t2_pri_con_09 0.097 0.014 7.049 0.000 0.097 0.225
## t1_pri_con_f ~~
## t2_pri_con_f 0.428 0.026 16.458 0.000 0.783 0.783
## t3_pri_con_f 0.422 0.026 16.288 0.000 0.764 0.764
## t2_pri_con_f ~~
## t3_pri_con_f 0.442 0.027 16.529 0.000 0.784 0.784
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 3.334 0.029 114.874 0.000 3.334 3.071
## .t1_pri_con_02 3.834 0.027 142.129 0.000 3.834 3.801
## .t1_pri_con_03 3.623 0.032 111.773 0.000 3.623 2.989
## .t1_pri_con_04 3.745 0.029 130.858 0.000 3.745 3.498
## .t1_pri_con_05 3.842 0.034 112.133 0.000 3.842 3.007
## .t1_pri_con_06 3.314 0.031 106.100 0.000 3.314 2.837
## .t1_pri_con_07 3.623 0.034 107.859 0.000 3.623 2.883
## .t1_pri_con_08 3.624 0.032 114.692 0.000 3.624 3.066
## .t1_pri_con_09 4.095 0.028 144.074 0.000 4.095 3.852
## .t2_pri_con_01 3.334 0.029 116.232 0.000 3.334 3.106
## .t2_pri_con_02 3.824 0.027 140.175 0.000 3.824 3.745
## .t2_pri_con_03 3.577 0.032 111.955 0.000 3.577 2.991
## .t2_pri_con_04 3.675 0.029 128.218 0.000 3.675 3.428
## .t2_pri_con_05 3.784 0.034 109.689 0.000 3.784 2.940
## .t2_pri_con_06 3.258 0.031 105.070 0.000 3.258 2.810
## .t2_pri_con_07 3.555 0.033 107.036 0.000 3.555 2.861
## .t2_pri_con_08 3.551 0.031 112.944 0.000 3.551 3.020
## .t2_pri_con_09 3.994 0.029 139.243 0.000 3.994 3.721
## .t3_pri_con_01 3.337 0.029 116.272 0.000 3.337 3.109
## .t3_pri_con_02 3.770 0.027 139.573 0.000 3.770 3.733
## .t3_pri_con_03 3.557 0.032 110.256 0.000 3.557 2.949
## .t3_pri_con_04 3.664 0.029 128.465 0.000 3.664 3.435
## .t3_pri_con_05 3.710 0.035 106.313 0.000 3.710 2.851
## .t3_pri_con_06 3.255 0.031 105.108 0.000 3.255 2.811
## .t3_pri_con_07 3.492 0.034 104.143 0.000 3.492 2.785
## .t3_pri_con_08 3.560 0.031 114.166 0.000 3.560 3.054
## .t3_pri_con_09 3.960 0.029 137.190 0.000 3.960 3.669
## t1_pri_con_f 0.000 0.000 0.000
## t2_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 0.643 0.026 24.529 0.000 0.643 0.546
## .t1_pri_con_02 0.543 0.022 24.367 0.000 0.543 0.533
## .t1_pri_con_03 0.827 0.034 24.399 0.000 0.827 0.563
## .t1_pri_con_04 0.415 0.019 22.280 0.000 0.415 0.362
## .t1_pri_con_05 0.907 0.037 24.315 0.000 0.907 0.556
## .t1_pri_con_06 0.595 0.025 23.518 0.000 0.595 0.436
## .t1_pri_con_07 0.625 0.028 22.703 0.000 0.625 0.396
## .t1_pri_con_08 0.571 0.025 22.838 0.000 0.571 0.408
## .t1_pri_con_09 0.437 0.019 22.697 0.000 0.437 0.386
## .t2_pri_con_01 0.595 0.024 24.560 0.000 0.595 0.516
## .t2_pri_con_02 0.548 0.022 24.479 0.000 0.548 0.526
## .t2_pri_con_03 0.760 0.031 24.346 0.000 0.760 0.532
## .t2_pri_con_04 0.388 0.017 22.340 0.000 0.388 0.338
## .t2_pri_con_05 0.901 0.037 24.475 0.000 0.901 0.544
## .t2_pri_con_06 0.543 0.023 23.449 0.000 0.543 0.404
## .t2_pri_con_07 0.550 0.024 22.548 0.000 0.550 0.356
## .t2_pri_con_08 0.522 0.023 22.707 0.000 0.522 0.378
## .t2_pri_con_09 0.430 0.019 22.703 0.000 0.430 0.373
## .t3_pri_con_01 0.583 0.024 24.323 0.000 0.583 0.506
## .t3_pri_con_02 0.516 0.021 24.116 0.000 0.516 0.506
## .t3_pri_con_03 0.772 0.032 24.254 0.000 0.772 0.531
## .t3_pri_con_04 0.361 0.016 21.902 0.000 0.361 0.318
## .t3_pri_con_05 0.923 0.038 24.588 0.000 0.923 0.545
## .t3_pri_con_06 0.525 0.022 23.386 0.000 0.525 0.391
## .t3_pri_con_07 0.559 0.025 22.459 0.000 0.559 0.355
## .t3_pri_con_08 0.481 0.022 22.322 0.000 0.481 0.354
## .t3_pri_con_09 0.427 0.019 22.773 0.000 0.427 0.367
## t1_pri_con_f 0.536 0.030 17.573 0.000 1.000 1.000
## t2_pri_con_f 0.558 0.031 17.728 0.000 1.000 1.000
## t3_pri_con_f 0.569 0.032 17.672 0.000 1.000 1.0001.1.2.3 Second-Order Model Unconstrained
In what follows, we analyze a second-order solution of privacy concerns. Here, we distinguish between horizontal privacy concerns (items 4, 5, 6) and vertical privacy concerns (items 7, 8, 9). The resulting model fits the data better than the unidimensional one.
model <- '
# create factors
t1_pri_con_f =~ 1*t1_pri_con_f1 + t1_pri_con_f2
t2_pri_con_f =~ 1*t2_pri_con_f1 + t2_pri_con_f2
t3_pri_con_f =~ 1*t3_pri_con_f1 + t3_pri_con_f2
t1_pri_con_f1 =~ 1*t1_pri_con_04 + t1_pri_con_05 + t1_pri_con_06
t1_pri_con_f2 =~ 1*t1_pri_con_07 + t1_pri_con_08 + t1_pri_con_09
t2_pri_con_f1 =~ 1*t2_pri_con_04 + t2_pri_con_05 + t2_pri_con_06
t2_pri_con_f2 =~ 1*t2_pri_con_07 + t2_pri_con_08 + t2_pri_con_09
t3_pri_con_f1 =~ 1*t3_pri_con_04 + t3_pri_con_05 + t3_pri_con_06
t3_pri_con_f2 =~ 1*t3_pri_con_07 + t3_pri_con_08 + t3_pri_con_09
# error covariances
t3_pri_con_04 ~~ t2_pri_con_04 + t1_pri_con_04
t3_pri_con_05 ~~ t2_pri_con_05 + t1_pri_con_05
t3_pri_con_06 ~~ t2_pri_con_06 + t1_pri_con_06
t3_pri_con_07 ~~ t2_pri_con_07 + t1_pri_con_07
t3_pri_con_08 ~~ t2_pri_con_08 + t1_pri_con_08
t3_pri_con_09 ~~ t2_pri_con_09 + t1_pri_con_09
t2_pri_con_04 ~~ t1_pri_con_04
t2_pri_con_05 ~~ t1_pri_con_05
t2_pri_con_06 ~~ t1_pri_con_06
t2_pri_con_07 ~~ t1_pri_con_07
t2_pri_con_08 ~~ t1_pri_con_08
t2_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t1_pri_con_f ~~ t2_pri_con_f + t3_pri_con_f
t2_pri_con_f ~~ t3_pri_con_f
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 83 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 81
##
## Number of observations 1403
## Number of missing patterns 26
##
## Model Test User Model:
##
## Test statistic 657.682
## Degrees of freedom 108
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 18770.022
## Degrees of freedom 153
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.970
## Tucker-Lewis Index (TLI) 0.958
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -30261.591
## Loglikelihood unrestricted model (H1) -29932.750
##
## Akaike (AIC) 60685.182
## Bayesian (BIC) 61110.138
## Sample-size adjusted Bayesian (BIC) 60852.831
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.060
## 90 Percent confidence interval - lower 0.056
## 90 Percent confidence interval - upper 0.065
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.035
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pri_con_f1 1.000 0.942 0.942
## t1_pri_con_f2 1.213 0.048 25.484 0.000 0.951 0.951
## t2_pri_con_f =~
## t2_pri_con_f1 1.000 0.962 0.962
## t2_pri_con_f2 1.231 0.044 27.818 0.000 0.956 0.956
## t3_pri_con_f =~
## t3_pri_con_f1 1.000 0.989 0.989
## t3_pri_con_f2 1.195 0.042 28.147 0.000 0.952 0.952
## t1_pri_con_f1 =~
## t1_pri_con_04 1.000 0.850 0.791
## t1_pri_con_05 1.011 0.038 26.326 0.000 0.859 0.671
## t1_pri_con_06 1.082 0.037 29.612 0.000 0.919 0.779
## t1_pri_con_f2 =~
## t1_pri_con_07 1.000 1.021 0.819
## t1_pri_con_08 0.971 0.027 36.207 0.000 0.991 0.843
## t1_pri_con_09 0.839 0.024 34.422 0.000 0.857 0.822
## t2_pri_con_f1 =~
## t2_pri_con_04 1.000 0.839 0.793
## t2_pri_con_05 1.045 0.039 26.889 0.000 0.877 0.677
## t2_pri_con_06 1.086 0.035 30.776 0.000 0.911 0.788
## t2_pri_con_f2 =~
## t2_pri_con_07 1.000 1.040 0.839
## t2_pri_con_08 0.969 0.025 39.030 0.000 1.007 0.855
## t2_pri_con_09 0.871 0.023 37.594 0.000 0.906 0.839
## t3_pri_con_f1 =~
## t3_pri_con_04 1.000 0.835 0.791
## t3_pri_con_05 1.020 0.039 26.407 0.000 0.852 0.657
## t3_pri_con_06 1.095 0.035 31.391 0.000 0.915 0.793
## t3_pri_con_f2 =~
## t3_pri_con_07 1.000 1.037 0.841
## t3_pri_con_08 0.972 0.024 40.887 0.000 1.008 0.868
## t3_pri_con_09 0.865 0.023 37.695 0.000 0.897 0.832
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t2_pri_con_04 ~~
## .t3_pri_con_04 0.073 0.014 5.089 0.000 0.073 0.176
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.094 0.015 6.273 0.000 0.094 0.223
## .t2_pri_con_05 ~~
## .t3_pri_con_05 0.433 0.031 14.123 0.000 0.433 0.464
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.454 0.031 14.641 0.000 0.454 0.489
## .t2_pri_con_06 ~~
## .t3_pri_con_06 0.166 0.018 9.428 0.000 0.166 0.332
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.160 0.018 8.817 0.000 0.160 0.309
## .t2_pri_con_07 ~~
## .t3_pri_con_07 0.157 0.017 9.446 0.000 0.157 0.349
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.170 0.018 9.690 0.000 0.170 0.358
## .t2_pri_con_08 ~~
## .t3_pri_con_08 0.109 0.014 8.034 0.000 0.109 0.309
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.099 0.014 7.167 0.000 0.099 0.272
## .t2_pri_con_09 ~~
## .t3_pri_con_09 0.107 0.013 8.438 0.000 0.107 0.305
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.069 0.012 5.546 0.000 0.069 0.195
## .t1_pri_con_04 ~~
## .t2_pri_con_04 0.090 0.015 5.985 0.000 0.090 0.213
## .t1_pri_con_05 ~~
## .t2_pri_con_05 0.401 0.030 13.362 0.000 0.401 0.443
## .t1_pri_con_06 ~~
## .t2_pri_con_06 0.157 0.019 8.467 0.000 0.157 0.298
## .t1_pri_con_07 ~~
## .t2_pri_con_07 0.156 0.018 8.914 0.000 0.156 0.325
## .t1_pri_con_08 ~~
## .t2_pri_con_08 0.092 0.014 6.402 0.000 0.092 0.238
## .t1_pri_con_09 ~~
## .t2_pri_con_09 0.074 0.012 5.978 0.000 0.074 0.213
## t1_pri_con_f ~~
## t2_pri_con_f 0.508 0.031 16.209 0.000 0.786 0.786
## t3_pri_con_f 0.511 0.031 16.327 0.000 0.772 0.772
## t2_pri_con_f ~~
## t3_pri_con_f 0.525 0.031 16.806 0.000 0.787 0.787
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 3.745 0.029 130.430 0.000 3.745 3.487
## .t1_pri_con_05 3.842 0.034 111.844 0.000 3.842 3.000
## .t1_pri_con_06 3.314 0.032 105.077 0.000 3.314 2.809
## .t1_pri_con_07 3.623 0.033 108.832 0.000 3.623 2.909
## .t1_pri_con_08 3.624 0.031 115.296 0.000 3.624 3.082
## .t1_pri_con_09 4.095 0.028 146.945 0.000 4.095 3.929
## .t2_pri_con_04 3.675 0.028 129.967 0.000 3.675 3.475
## .t2_pri_con_05 3.784 0.035 108.978 0.000 3.784 2.921
## .t2_pri_con_06 3.258 0.031 105.353 0.000 3.258 2.818
## .t2_pri_con_07 3.556 0.033 107.327 0.000 3.556 2.869
## .t2_pri_con_08 3.551 0.032 112.679 0.000 3.551 3.012
## .t2_pri_con_09 3.994 0.029 138.427 0.000 3.994 3.699
## .t3_pri_con_04 3.664 0.028 129.676 0.000 3.664 3.468
## .t3_pri_con_05 3.709 0.035 106.637 0.000 3.709 2.859
## .t3_pri_con_06 3.256 0.031 105.607 0.000 3.256 2.824
## .t3_pri_con_07 3.492 0.033 105.953 0.000 3.492 2.833
## .t3_pri_con_08 3.560 0.031 114.604 0.000 3.560 3.065
## .t3_pri_con_09 3.959 0.029 137.357 0.000 3.959 3.674
## t1_pri_con_f 0.000 0.000 0.000
## t2_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
## .t1_pri_con_f1 0.000 0.000 0.000
## .t1_pri_con_f2 0.000 0.000 0.000
## .t2_pri_con_f1 0.000 0.000 0.000
## .t2_pri_con_f2 0.000 0.000 0.000
## .t3_pri_con_f1 0.000 0.000 0.000
## .t3_pri_con_f2 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 0.431 0.022 19.198 0.000 0.431 0.374
## .t1_pri_con_05 0.902 0.040 22.711 0.000 0.902 0.550
## .t1_pri_con_06 0.546 0.027 20.013 0.000 0.546 0.392
## .t1_pri_con_07 0.509 0.026 19.666 0.000 0.509 0.328
## .t1_pri_con_08 0.399 0.021 18.622 0.000 0.399 0.289
## .t1_pri_con_09 0.353 0.018 19.768 0.000 0.353 0.325
## .t2_pri_con_04 0.414 0.021 19.815 0.000 0.414 0.371
## .t2_pri_con_05 0.910 0.039 23.075 0.000 0.910 0.542
## .t2_pri_con_06 0.507 0.025 20.332 0.000 0.507 0.380
## .t2_pri_con_07 0.455 0.023 19.557 0.000 0.455 0.296
## .t2_pri_con_08 0.375 0.020 18.782 0.000 0.375 0.270
## .t2_pri_con_09 0.345 0.018 19.456 0.000 0.345 0.296
## .t3_pri_con_04 0.418 0.021 20.354 0.000 0.418 0.375
## .t3_pri_con_05 0.956 0.041 23.557 0.000 0.956 0.568
## .t3_pri_con_06 0.492 0.024 20.489 0.000 0.492 0.370
## .t3_pri_con_07 0.444 0.022 19.740 0.000 0.444 0.292
## .t3_pri_con_08 0.333 0.018 18.288 0.000 0.333 0.247
## .t3_pri_con_09 0.357 0.018 20.263 0.000 0.357 0.307
## t1_pri_con_f 0.641 0.043 15.025 0.000 1.000 1.000
## t2_pri_con_f 0.652 0.041 15.720 0.000 1.000 1.000
## t3_pri_con_f 0.683 0.042 16.106 0.000 1.000 1.000
## .t1_pri_con_f1 0.081 0.015 5.266 0.000 0.112 0.112
## .t1_pri_con_f2 0.099 0.021 4.818 0.000 0.095 0.095
## .t2_pri_con_f1 0.052 0.014 3.831 0.000 0.074 0.074
## .t2_pri_con_f2 0.094 0.019 5.012 0.000 0.087 0.087
## .t3_pri_con_f1 0.015 0.013 1.199 0.230 0.022 0.022
## .t3_pri_con_f2 0.101 0.018 5.558 0.000 0.094 0.0941.1.2.4 Second-Order Model Constrained
model <- '
# create factors
t1_pri_con_f =~ 1*t1_pri_con_f1 + a2*t1_pri_con_f2
t2_pri_con_f =~ 1*t2_pri_con_f1 + a2*t2_pri_con_f2
t3_pri_con_f =~ 1*t3_pri_con_f1 + a2*t3_pri_con_f2
t1_pri_con_f1 =~ 1*t1_pri_con_04 + b2*t1_pri_con_05 + b3*t1_pri_con_06
t1_pri_con_f2 =~ 1*t1_pri_con_07 + c2*t1_pri_con_08 + c3*t1_pri_con_09
t2_pri_con_f1 =~ 1*t2_pri_con_04 + b2*t2_pri_con_05 + b3*t2_pri_con_06
t2_pri_con_f2 =~ 1*t2_pri_con_07 + c2*t2_pri_con_08 + c3*t2_pri_con_09
t3_pri_con_f1 =~ 1*t3_pri_con_04 + b2*t3_pri_con_05 + b3*t3_pri_con_06
t3_pri_con_f2 =~ 1*t3_pri_con_07 + c2*t3_pri_con_08 + c3*t3_pri_con_09
# error covariances
t3_pri_con_04 ~~ t2_pri_con_04 + t1_pri_con_04
t3_pri_con_05 ~~ t2_pri_con_05 + t1_pri_con_05
t3_pri_con_06 ~~ t2_pri_con_06 + t1_pri_con_06
t3_pri_con_07 ~~ t2_pri_con_07 + t1_pri_con_07
t3_pri_con_08 ~~ t2_pri_con_08 + t1_pri_con_08
t3_pri_con_09 ~~ t2_pri_con_09 + t1_pri_con_09
t2_pri_con_04 ~~ t1_pri_con_04
t2_pri_con_05 ~~ t1_pri_con_05
t2_pri_con_06 ~~ t1_pri_con_06
t2_pri_con_07 ~~ t1_pri_con_07
t2_pri_con_08 ~~ t1_pri_con_08
t2_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t1_pri_con_f ~~ t2_pri_con_f + t3_pri_con_f
t2_pri_con_f ~~ t3_pri_con_f
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 86 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 81
## Number of equality constraints 10
##
## Number of observations 1403
## Number of missing patterns 26
##
## Model Test User Model:
##
## Test statistic 661.175
## Degrees of freedom 118
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 18770.022
## Degrees of freedom 153
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.971
## Tucker-Lewis Index (TLI) 0.962
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -30263.337
## Loglikelihood unrestricted model (H1) -29932.750
##
## Akaike (AIC) 60668.675
## Bayesian (BIC) 61041.167
## Sample-size adjusted Bayesian (BIC) 60815.626
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.057
## 90 Percent confidence interval - lower 0.053
## 90 Percent confidence interval - upper 0.062
## P-value RMSEA <= 0.05 0.002
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.036
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pr_c_1 1.000 0.942 0.942
## t1_pr_c_2 (a2) 1.212 0.031 38.916 0.000 0.952 0.952
## t2_pri_con_f =~
## t2_pr_c_1 1.000 0.966 0.966
## t2_pr_c_2 (a2) 1.212 0.031 38.916 0.000 0.952 0.952
## t3_pri_con_f =~
## t3_pr_c_1 1.000 0.986 0.986
## t3_pr_c_2 (a2) 1.212 0.031 38.916 0.000 0.955 0.955
## t1_pri_con_f1 =~
## t1_pr__04 1.000 0.845 0.789
## t1_pr__05 (b2) 1.026 0.028 36.986 0.000 0.867 0.675
## t1_pr__06 (b3) 1.088 0.024 44.494 0.000 0.919 0.779
## t1_pri_con_f2 =~
## t1_pr__07 1.000 1.013 0.817
## t1_pr__08 (c2) 0.971 0.018 55.102 0.000 0.984 0.841
## t1_pr__09 (c3) 0.859 0.016 52.558 0.000 0.871 0.828
## t2_pri_con_f1 =~
## t2_pr__04 1.000 0.846 0.796
## t2_pr__05 (b2) 1.026 0.028 36.986 0.000 0.868 0.672
## t2_pr__06 (b3) 1.088 0.024 44.494 0.000 0.920 0.791
## t2_pri_con_f2 =~
## t2_pr__07 1.000 1.039 0.839
## t2_pr__08 (c2) 0.971 0.018 55.102 0.000 1.009 0.855
## t2_pr__09 (c3) 0.859 0.016 52.558 0.000 0.893 0.834
## t3_pri_con_f1 =~
## t3_pr__04 1.000 0.833 0.790
## t3_pr__05 (b2) 1.026 0.028 36.986 0.000 0.855 0.658
## t3_pr__06 (b3) 1.088 0.024 44.494 0.000 0.906 0.791
## t3_pri_con_f2 =~
## t3_pr__07 1.000 1.043 0.843
## t3_pr__08 (c2) 0.971 0.018 55.102 0.000 1.013 0.869
## t3_pr__09 (c3) 0.859 0.016 52.558 0.000 0.896 0.832
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t2_pri_con_04 ~~
## .t3_pri_con_04 0.073 0.014 5.085 0.000 0.073 0.176
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.095 0.015 6.341 0.000 0.095 0.224
## .t2_pri_con_05 ~~
## .t3_pri_con_05 0.433 0.031 14.129 0.000 0.433 0.464
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.454 0.031 14.640 0.000 0.454 0.490
## .t2_pri_con_06 ~~
## .t3_pri_con_06 0.166 0.018 9.428 0.000 0.166 0.332
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.160 0.018 8.830 0.000 0.160 0.309
## .t2_pri_con_07 ~~
## .t3_pri_con_07 0.156 0.017 9.428 0.000 0.156 0.348
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.171 0.018 9.728 0.000 0.171 0.358
## .t2_pri_con_08 ~~
## .t3_pri_con_08 0.109 0.014 8.043 0.000 0.109 0.310
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.099 0.014 7.180 0.000 0.099 0.272
## .t2_pri_con_09 ~~
## .t3_pri_con_09 0.108 0.013 8.511 0.000 0.108 0.306
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.069 0.012 5.512 0.000 0.069 0.195
## .t1_pri_con_04 ~~
## .t2_pri_con_04 0.090 0.015 5.985 0.000 0.090 0.212
## .t1_pri_con_05 ~~
## .t2_pri_con_05 0.401 0.030 13.348 0.000 0.401 0.442
## .t1_pri_con_06 ~~
## .t2_pri_con_06 0.157 0.019 8.461 0.000 0.157 0.298
## .t1_pri_con_07 ~~
## .t2_pri_con_07 0.157 0.018 8.955 0.000 0.157 0.325
## .t1_pri_con_08 ~~
## .t2_pri_con_08 0.092 0.014 6.430 0.000 0.092 0.239
## .t1_pri_con_09 ~~
## .t2_pri_con_09 0.074 0.012 5.999 0.000 0.074 0.214
## t1_pri_con_f ~~
## t2_pri_con_f 0.511 0.030 17.157 0.000 0.786 0.786
## t3_pri_con_f 0.505 0.029 17.166 0.000 0.772 0.772
## t2_pri_con_f ~~
## t3_pri_con_f 0.528 0.030 17.351 0.000 0.786 0.786
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 3.745 0.029 130.814 0.000 3.745 3.498
## .t1_pri_con_05 3.842 0.034 111.479 0.000 3.842 2.990
## .t1_pri_con_06 3.314 0.032 105.073 0.000 3.314 2.809
## .t1_pri_con_07 3.623 0.033 109.216 0.000 3.623 2.920
## .t1_pri_con_08 3.624 0.031 115.845 0.000 3.624 3.097
## .t1_pri_con_09 4.095 0.028 145.606 0.000 4.095 3.893
## .t2_pri_con_04 3.675 0.028 129.357 0.000 3.675 3.459
## .t2_pri_con_05 3.784 0.035 109.375 0.000 3.784 2.932
## .t2_pri_con_06 3.258 0.031 104.716 0.000 3.258 2.801
## .t2_pri_con_07 3.556 0.033 107.425 0.000 3.556 2.872
## .t2_pri_con_08 3.551 0.032 112.593 0.000 3.551 3.010
## .t2_pri_con_09 3.994 0.029 139.662 0.000 3.994 3.732
## .t3_pri_con_04 3.664 0.028 129.881 0.000 3.664 3.473
## .t3_pri_con_05 3.709 0.035 106.555 0.000 3.709 2.857
## .t3_pri_con_06 3.256 0.031 106.189 0.000 3.256 2.839
## .t3_pri_con_07 3.492 0.033 105.575 0.000 3.492 2.823
## .t3_pri_con_08 3.560 0.031 114.210 0.000 3.560 3.055
## .t3_pri_con_09 3.959 0.029 137.398 0.000 3.959 3.675
## t1_pri_con_f 0.000 0.000 0.000
## t2_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
## .t1_pri_con_f1 0.000 0.000 0.000
## .t1_pri_con_f2 0.000 0.000 0.000
## .t2_pri_con_f1 0.000 0.000 0.000
## .t2_pri_con_f2 0.000 0.000 0.000
## .t3_pri_con_f1 0.000 0.000 0.000
## .t3_pri_con_f2 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 0.433 0.022 19.819 0.000 0.433 0.377
## .t1_pri_con_05 0.900 0.040 22.779 0.000 0.900 0.545
## .t1_pri_con_06 0.546 0.027 20.364 0.000 0.546 0.392
## .t1_pri_con_07 0.513 0.025 20.282 0.000 0.513 0.333
## .t1_pri_con_08 0.401 0.021 19.096 0.000 0.401 0.293
## .t1_pri_con_09 0.349 0.017 19.948 0.000 0.349 0.315
## .t2_pri_con_04 0.413 0.020 20.196 0.000 0.413 0.366
## .t2_pri_con_05 0.913 0.039 23.235 0.000 0.913 0.548
## .t2_pri_con_06 0.506 0.025 20.513 0.000 0.506 0.374
## .t2_pri_con_07 0.453 0.023 19.877 0.000 0.453 0.296
## .t2_pri_con_08 0.373 0.020 18.959 0.000 0.373 0.268
## .t2_pri_con_09 0.348 0.017 19.944 0.000 0.348 0.304
## .t3_pri_con_04 0.419 0.020 20.670 0.000 0.419 0.376
## .t3_pri_con_05 0.955 0.040 23.579 0.000 0.955 0.567
## .t3_pri_con_06 0.493 0.024 20.717 0.000 0.493 0.375
## .t3_pri_con_07 0.443 0.022 20.042 0.000 0.443 0.289
## .t3_pri_con_08 0.333 0.018 18.506 0.000 0.333 0.245
## .t3_pri_con_09 0.358 0.017 20.632 0.000 0.358 0.308
## t1_pri_con_f 0.633 0.035 18.237 0.000 1.000 1.000
## t2_pri_con_f 0.667 0.036 18.585 0.000 1.000 1.000
## t3_pri_con_f 0.675 0.036 18.769 0.000 1.000 1.000
## .t1_pri_con_f1 0.081 0.014 5.626 0.000 0.113 0.113
## .t1_pri_con_f2 0.097 0.019 5.195 0.000 0.094 0.094
## .t2_pri_con_f1 0.048 0.013 3.735 0.000 0.067 0.067
## .t2_pri_con_f2 0.100 0.018 5.713 0.000 0.093 0.093
## .t3_pri_con_f1 0.019 0.012 1.569 0.117 0.027 0.027
## .t3_pri_con_f2 0.097 0.017 5.669 0.000 0.089 0.0891.1.3 Reliability
reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t1", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.852 0.946 0.896reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t2", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.870 0.956 0.905reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t3", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.880 0.966 0.9061.1.4 Longitudinal Invariance
(anova(get(paste("fit", name, no - 1, sep = "_")), get(paste("fit", name, no, sep = "_"))))1.2 Attitude Toward Online Sharing of Personal Information
1.2.1 EFA
no <- 0
name <- "inf_sha_att"
d_tmp <- select(d_wide, contains(paste0("t1_", name)), -contains("_m"))
model <- fa.parallel(d_tmp, fa = "fa", fm = "ml")
## Parallel analysis suggests that the number of factors = 5 and the number of components = NAfactan <- fa(d_tmp, fm = "ml", nfactors = model$nfact, rotate = "promax")
print(factan, sort = TRUE, cut = 0.3)## Factor Analysis using method = ml
## Call: fa(r = d_tmp, nfactors = model$nfact, rotate = "promax", fm = "ml")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item ML1 ML4 ML2 ML3 ML5 h2 u2 com
## t1_inf_sha_att_06 7 1.06 0.86 0.1400 1.0
## t1_inf_sha_att_05 6 0.95 0.88 0.1179 1.1
## t1_inf_sha_att_03 4 0.64 0.40 0.82 0.1788 1.7
## t1_inf_sha_att_08 9 0.63 0.51 0.4885 1.4
## t1_inf_sha_att_fs 1 0.58 1.00 0.0044 1.9
## t1_inf_sha_att_10 11 0.99 0.89 0.1130 1.0
## t1_inf_sha_att_11 12 0.98 0.87 0.1290 1.0
## t1_inf_sha_att_09 10 0.47 0.24 0.7619 1.1
## t1_inf_sha_att_01 2 1.06 1.00 0.0050 1.1
## t1_inf_sha_att_02 3 0.54 0.34 0.6614 1.1
## t1_inf_sha_att_07 8 1.01 1.00 0.0050 1.0
## t1_inf_sha_att_04 5 0.32 0.74 0.97 0.0320 1.4
##
## ML1 ML4 ML2 ML3 ML5
## SS loadings 3.54 2.18 1.38 1.08 1.19
## Proportion Var 0.30 0.18 0.11 0.09 0.10
## Cumulative Var 0.30 0.48 0.59 0.68 0.78
## Proportion Explained 0.38 0.23 0.15 0.12 0.13
## Cumulative Proportion 0.38 0.61 0.76 0.87 1.00
##
## With factor correlations of
## ML1 ML4 ML2 ML3 ML5
## ML1 1.00 0.48 0.43 0.66 0.52
## ML4 0.48 1.00 0.29 0.47 0.40
## ML2 0.43 0.29 1.00 0.34 0.21
## ML3 0.66 0.47 0.34 1.00 0.37
## ML5 0.52 0.40 0.21 0.37 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 5 factors are sufficient.
##
## The degrees of freedom for the null model are 66 and the objective function was 12.7 with Chi Square of 17754
## The degrees of freedom for the model are 16 and the objective function was 1.58
##
## The root mean square of the residuals (RMSR) is 0.02
## The df corrected root mean square of the residuals is 0.04
##
## The harmonic number of observations is 1396 with the empirical chi square 61.6 with prob < 2.8e-07
## The total number of observations was 1403 with Likelihood Chi Square = 2196 with prob < 0
##
## Tucker Lewis Index of factoring reliability = 0.49
## RMSEA index = 0.312 and the 90 % confidence intervals are 0.301 0.323
## BIC = 2080
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## ML1 ML4 ML2 ML3 ML5
## Correlation of (regression) scores with factors 0.99 0.98 1.00 1.00 0.97
## Multiple R square of scores with factors 0.98 0.96 1.00 0.99 0.94
## Minimum correlation of possible factor scores 0.95 0.91 0.99 0.99 0.881.2.2 CFA
1.2.2.1 First-Order Model Unconstrained
model <- '
# create factors
t1_pri_con_f =~ 1*t1_pri_con_01 + t1_pri_con_02 + t1_pri_con_03 + t1_pri_con_04 + t1_pri_con_05 + t1_pri_con_06 + t1_pri_con_07 + t1_pri_con_08 + t1_pri_con_09
t2_pri_con_f =~ 1*t2_pri_con_01 + t2_pri_con_02 + t2_pri_con_03 + t2_pri_con_04 + t2_pri_con_05 + t2_pri_con_06 + t2_pri_con_07 + t2_pri_con_08 + t2_pri_con_09
t3_pri_con_f =~ 1*t3_pri_con_01 + t3_pri_con_02 + t3_pri_con_03 + t3_pri_con_04 + t3_pri_con_05 + t3_pri_con_06 + t3_pri_con_07 + t3_pri_con_08 + t3_pri_con_09
# error covariances
t3_pri_con_01 ~~ t2_pri_con_01 + t1_pri_con_01
t3_pri_con_02 ~~ t2_pri_con_02 + t1_pri_con_02
t3_pri_con_03 ~~ t2_pri_con_03 + t1_pri_con_03
t3_pri_con_04 ~~ t2_pri_con_04 + t1_pri_con_04
t3_pri_con_05 ~~ t2_pri_con_05 + t1_pri_con_05
t3_pri_con_06 ~~ t2_pri_con_06 + t1_pri_con_06
t3_pri_con_07 ~~ t2_pri_con_07 + t1_pri_con_07
t3_pri_con_08 ~~ t2_pri_con_08 + t1_pri_con_08
t3_pri_con_09 ~~ t2_pri_con_09 + t1_pri_con_09
t2_pri_con_01 ~~ t1_pri_con_01
t2_pri_con_02 ~~ t1_pri_con_02
t2_pri_con_03 ~~ t1_pri_con_03
t2_pri_con_04 ~~ t1_pri_con_04
t2_pri_con_05 ~~ t1_pri_con_05
t2_pri_con_06 ~~ t1_pri_con_06
t2_pri_con_07 ~~ t1_pri_con_07
t2_pri_con_08 ~~ t1_pri_con_08
t2_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t1_pri_con_f ~~ t2_pri_con_f + t3_pri_con_f
t2_pri_con_f ~~ t3_pri_con_f
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 101 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 111
##
## Number of observations 1403
## Number of missing patterns 29
##
## Model Test User Model:
##
## Test statistic 2726.529
## Degrees of freedom 294
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 29137.955
## Degrees of freedom 351
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.915
## Tucker-Lewis Index (TLI) 0.899
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -45195.456
## Loglikelihood unrestricted model (H1) -43832.192
##
## Akaike (AIC) 90612.913
## Bayesian (BIC) 91195.260
## Sample-size adjusted Bayesian (BIC) 90842.654
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.077
## 90 Percent confidence interval - lower 0.074
## 90 Percent confidence interval - upper 0.079
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.051
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pri_con_01 1.000 0.728 0.672
## t1_pri_con_02 0.927 0.039 23.800 0.000 0.675 0.675
## t1_pri_con_03 1.103 0.047 23.669 0.000 0.803 0.662
## t1_pri_con_04 1.198 0.043 27.544 0.000 0.872 0.806
## t1_pri_con_05 1.176 0.050 23.621 0.000 0.857 0.669
## t1_pri_con_06 1.226 0.047 25.980 0.000 0.892 0.757
## t1_pri_con_07 1.343 0.050 26.665 0.000 0.978 0.777
## t1_pri_con_08 1.243 0.048 26.133 0.000 0.905 0.767
## t1_pri_con_09 1.115 0.042 26.333 0.000 0.812 0.774
## t2_pri_con_f =~
## t2_pri_con_01 1.000 0.724 0.683
## t2_pri_con_02 0.944 0.039 24.509 0.000 0.684 0.677
## t2_pri_con_03 1.126 0.045 24.972 0.000 0.815 0.682
## t2_pri_con_04 1.192 0.042 28.303 0.000 0.863 0.810
## t2_pri_con_05 1.215 0.050 24.474 0.000 0.879 0.680
## t2_pri_con_06 1.230 0.045 27.083 0.000 0.891 0.770
## t2_pri_con_07 1.395 0.049 28.252 0.000 1.010 0.807
## t2_pri_con_08 1.293 0.047 27.719 0.000 0.936 0.793
## t2_pri_con_09 1.202 0.043 27.945 0.000 0.870 0.801
## t3_pri_con_f =~
## t3_pri_con_01 1.000 0.779 0.716
## t3_pri_con_02 0.949 0.035 27.110 0.000 0.740 0.720
## t3_pri_con_03 1.065 0.040 26.378 0.000 0.830 0.688
## t3_pri_con_04 1.126 0.037 30.533 0.000 0.878 0.826
## t3_pri_con_05 1.108 0.044 25.221 0.000 0.863 0.668
## t3_pri_con_06 1.148 0.040 28.735 0.000 0.895 0.776
## t3_pri_con_07 1.273 0.043 29.592 0.000 0.992 0.797
## t3_pri_con_08 1.194 0.040 29.630 0.000 0.931 0.800
## t3_pri_con_09 1.101 0.038 29.296 0.000 0.858 0.795
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t2_pri_con_01 ~~
## .t3_pri_con_01 0.188 0.018 10.432 0.000 0.188 0.319
## .t1_pri_con_01 ~~
## .t3_pri_con_01 0.198 0.019 10.556 0.000 0.198 0.324
## .t2_pri_con_02 ~~
## .t3_pri_con_02 0.186 0.016 11.324 0.000 0.186 0.351
## .t1_pri_con_02 ~~
## .t3_pri_con_02 0.164 0.016 10.173 0.000 0.164 0.311
## .t2_pri_con_03 ~~
## .t3_pri_con_03 0.405 0.025 16.132 0.000 0.405 0.528
## .t1_pri_con_03 ~~
## .t3_pri_con_03 0.383 0.026 14.928 0.000 0.383 0.481
## .t2_pri_con_04 ~~
## .t3_pri_con_04 0.047 0.012 3.894 0.000 0.047 0.126
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.059 0.013 4.709 0.000 0.059 0.155
## .t2_pri_con_05 ~~
## .t3_pri_con_05 0.381 0.029 13.280 0.000 0.381 0.418
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.402 0.029 13.809 0.000 0.402 0.440
## .t2_pri_con_06 ~~
## .t3_pri_con_06 0.157 0.017 9.272 0.000 0.157 0.293
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.153 0.018 8.736 0.000 0.153 0.274
## .t2_pri_con_07 ~~
## .t3_pri_con_07 0.195 0.018 10.585 0.000 0.195 0.351
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.235 0.020 11.730 0.000 0.235 0.395
## .t2_pri_con_08 ~~
## .t3_pri_con_08 0.166 0.017 9.991 0.000 0.166 0.331
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.175 0.017 10.092 0.000 0.175 0.332
## .t2_pri_con_09 ~~
## .t3_pri_con_09 0.129 0.014 9.247 0.000 0.129 0.301
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.113 0.014 8.049 0.000 0.113 0.259
## .t1_pri_con_01 ~~
## .t2_pri_con_01 0.215 0.019 11.310 0.000 0.215 0.346
## .t1_pri_con_02 ~~
## .t2_pri_con_02 0.191 0.017 11.391 0.000 0.191 0.348
## .t1_pri_con_03 ~~
## .t2_pri_con_03 0.358 0.025 14.190 0.000 0.358 0.450
## .t1_pri_con_04 ~~
## .t2_pri_con_04 0.065 0.013 5.034 0.000 0.065 0.163
## .t1_pri_con_05 ~~
## .t2_pri_con_05 0.358 0.028 12.611 0.000 0.358 0.397
## .t1_pri_con_06 ~~
## .t2_pri_con_06 0.149 0.018 8.377 0.000 0.149 0.262
## .t1_pri_con_07 ~~
## .t2_pri_con_07 0.210 0.019 10.796 0.000 0.210 0.358
## .t1_pri_con_08 ~~
## .t2_pri_con_08 0.141 0.017 8.085 0.000 0.141 0.260
## .t1_pri_con_09 ~~
## .t2_pri_con_09 0.097 0.014 7.036 0.000 0.097 0.225
## t1_pri_con_f ~~
## t2_pri_con_f 0.413 0.027 15.322 0.000 0.783 0.783
## t3_pri_con_f 0.434 0.028 15.608 0.000 0.764 0.764
## t2_pri_con_f ~~
## t3_pri_con_f 0.443 0.028 15.956 0.000 0.785 0.785
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 3.334 0.029 115.127 0.000 3.334 3.078
## .t1_pri_con_02 3.834 0.027 143.391 0.000 3.834 3.835
## .t1_pri_con_03 3.623 0.032 111.778 0.000 3.623 2.989
## .t1_pri_con_04 3.745 0.029 129.436 0.000 3.745 3.460
## .t1_pri_con_05 3.842 0.034 111.938 0.000 3.842 3.002
## .t1_pri_con_06 3.314 0.032 105.186 0.000 3.314 2.812
## .t1_pri_con_07 3.623 0.034 107.747 0.000 3.623 2.880
## .t1_pri_con_08 3.624 0.032 114.843 0.000 3.624 3.070
## .t1_pri_con_09 4.095 0.028 146.054 0.000 4.095 3.905
## .t2_pri_con_01 3.334 0.028 117.727 0.000 3.334 3.146
## .t2_pri_con_02 3.824 0.027 141.720 0.000 3.824 3.787
## .t2_pri_con_03 3.577 0.032 112.037 0.000 3.577 2.994
## .t2_pri_con_04 3.675 0.028 128.972 0.000 3.675 3.448
## .t2_pri_con_05 3.784 0.035 109.118 0.000 3.784 2.925
## .t2_pri_con_06 3.258 0.031 105.352 0.000 3.258 2.818
## .t2_pri_con_07 3.555 0.033 106.315 0.000 3.555 2.842
## .t2_pri_con_08 3.550 0.032 112.492 0.000 3.550 3.007
## .t2_pri_con_09 3.994 0.029 137.529 0.000 3.994 3.675
## .t3_pri_con_01 3.337 0.029 114.707 0.000 3.337 3.068
## .t3_pri_con_02 3.770 0.027 137.192 0.000 3.770 3.669
## .t3_pri_con_03 3.557 0.032 110.186 0.000 3.557 2.947
## .t3_pri_con_04 3.664 0.028 128.933 0.000 3.664 3.448
## .t3_pri_con_05 3.710 0.035 107.098 0.000 3.710 2.872
## .t3_pri_con_06 3.255 0.031 105.623 0.000 3.255 2.824
## .t3_pri_con_07 3.492 0.033 104.929 0.000 3.492 2.806
## .t3_pri_con_08 3.560 0.031 114.458 0.000 3.560 3.061
## .t3_pri_con_09 3.960 0.029 137.133 0.000 3.960 3.668
## t1_pri_con_f 0.000 0.000 0.000
## t2_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 0.643 0.026 24.370 0.000 0.643 0.548
## .t1_pri_con_02 0.544 0.022 24.301 0.000 0.544 0.544
## .t1_pri_con_03 0.825 0.034 24.259 0.000 0.825 0.561
## .t1_pri_con_04 0.411 0.019 21.877 0.000 0.411 0.351
## .t1_pri_con_05 0.904 0.037 24.229 0.000 0.904 0.552
## .t1_pri_con_06 0.592 0.025 23.324 0.000 0.592 0.426
## .t1_pri_con_07 0.626 0.028 22.490 0.000 0.626 0.396
## .t1_pri_con_08 0.574 0.025 22.683 0.000 0.574 0.412
## .t1_pri_con_09 0.440 0.019 22.680 0.000 0.440 0.400
## .t2_pri_con_01 0.600 0.024 24.517 0.000 0.600 0.534
## .t2_pri_con_02 0.552 0.023 24.417 0.000 0.552 0.542
## .t2_pri_con_03 0.764 0.031 24.251 0.000 0.764 0.535
## .t2_pri_con_04 0.391 0.018 22.204 0.000 0.391 0.345
## .t2_pri_con_05 0.901 0.037 24.409 0.000 0.901 0.538
## .t2_pri_con_06 0.544 0.023 23.388 0.000 0.544 0.407
## .t2_pri_con_07 0.546 0.024 22.352 0.000 0.546 0.349
## .t2_pri_con_08 0.518 0.023 22.481 0.000 0.518 0.371
## .t2_pri_con_09 0.424 0.019 22.382 0.000 0.424 0.359
## .t3_pri_con_01 0.576 0.024 24.115 0.000 0.576 0.487
## .t3_pri_con_02 0.509 0.021 23.879 0.000 0.509 0.482
## .t3_pri_con_03 0.768 0.032 24.130 0.000 0.768 0.527
## .t3_pri_con_04 0.359 0.017 21.645 0.000 0.359 0.318
## .t3_pri_con_05 0.923 0.038 24.596 0.000 0.923 0.553
## .t3_pri_con_06 0.528 0.023 23.357 0.000 0.528 0.397
## .t3_pri_con_07 0.565 0.025 22.376 0.000 0.565 0.365
## .t3_pri_con_08 0.486 0.022 22.211 0.000 0.486 0.359
## .t3_pri_con_09 0.429 0.019 22.629 0.000 0.429 0.368
## t1_pri_con_f 0.530 0.038 14.041 0.000 1.000 1.000
## t2_pri_con_f 0.524 0.036 14.435 0.000 1.000 1.000
## t3_pri_con_f 0.607 0.040 15.297 0.000 1.000 1.0001.2.2.2 First-Order Model Constrained
model <- '
# create factors
t1_pri_con_f =~ 1*t1_pri_con_01 + a2*t1_pri_con_02 + a3*t1_pri_con_03 + a4*t1_pri_con_04 + a5*t1_pri_con_05 + a6*t1_pri_con_06 + a7*t1_pri_con_07 + a8*t1_pri_con_08 + a9*t1_pri_con_09
t2_pri_con_f =~ 1*t2_pri_con_01 + a2*t2_pri_con_02 + a3*t2_pri_con_03 + a4*t2_pri_con_04 + a5*t2_pri_con_05 + a6*t2_pri_con_06 + a7*t2_pri_con_07 + a8*t2_pri_con_08 + a9*t2_pri_con_09
t3_pri_con_f =~ 1*t3_pri_con_01 + a2*t3_pri_con_02 + a3*t3_pri_con_03 + a4*t3_pri_con_04 + a5*t3_pri_con_05 + a6*t3_pri_con_06 + a7*t3_pri_con_07 + a8*t3_pri_con_08 + a9*t3_pri_con_09
# error covariances
t3_pri_con_01 ~~ t2_pri_con_01 + t1_pri_con_01
t3_pri_con_02 ~~ t2_pri_con_02 + t1_pri_con_02
t3_pri_con_03 ~~ t2_pri_con_03 + t1_pri_con_03
t3_pri_con_04 ~~ t2_pri_con_04 + t1_pri_con_04
t3_pri_con_05 ~~ t2_pri_con_05 + t1_pri_con_05
t3_pri_con_06 ~~ t2_pri_con_06 + t1_pri_con_06
t3_pri_con_07 ~~ t2_pri_con_07 + t1_pri_con_07
t3_pri_con_08 ~~ t2_pri_con_08 + t1_pri_con_08
t3_pri_con_09 ~~ t2_pri_con_09 + t1_pri_con_09
t2_pri_con_01 ~~ t1_pri_con_01
t2_pri_con_02 ~~ t1_pri_con_02
t2_pri_con_03 ~~ t1_pri_con_03
t2_pri_con_04 ~~ t1_pri_con_04
t2_pri_con_05 ~~ t1_pri_con_05
t2_pri_con_06 ~~ t1_pri_con_06
t2_pri_con_07 ~~ t1_pri_con_07
t2_pri_con_08 ~~ t1_pri_con_08
t2_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t1_pri_con_f ~~ t2_pri_con_f + t3_pri_con_f
t2_pri_con_f ~~ t3_pri_con_f
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 91 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 111
## Number of equality constraints 16
##
## Number of observations 1403
## Number of missing patterns 29
##
## Model Test User Model:
##
## Test statistic 2742.286
## Degrees of freedom 310
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 29137.955
## Degrees of freedom 351
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.916
## Tucker-Lewis Index (TLI) 0.904
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -45203.335
## Loglikelihood unrestricted model (H1) -43832.192
##
## Akaike (AIC) 90596.670
## Bayesian (BIC) 91095.075
## Sample-size adjusted Bayesian (BIC) 90793.295
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.075
## 90 Percent confidence interval - lower 0.072
## 90 Percent confidence interval - upper 0.077
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.052
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pr__01 1.000 0.732 0.674
## t1_pr__02 (a2) 0.942 0.027 35.461 0.000 0.689 0.683
## t1_pr__03 (a3) 1.096 0.032 34.033 0.000 0.802 0.661
## t1_pr__04 (a4) 1.168 0.028 41.826 0.000 0.855 0.799
## t1_pr__05 (a5) 1.164 0.034 33.805 0.000 0.852 0.667
## t1_pr__06 (a6) 1.198 0.031 38.839 0.000 0.877 0.751
## t1_pr__07 (a7) 1.335 0.034 39.462 0.000 0.977 0.777
## t1_pr__08 (a8) 1.242 0.032 39.320 0.000 0.909 0.769
## t1_pr__09 (a9) 1.138 0.029 39.675 0.000 0.833 0.783
## t2_pri_con_f =~
## t2_pr__01 1.000 0.747 0.695
## t2_pr__02 (a2) 0.942 0.027 35.461 0.000 0.703 0.689
## t2_pr__03 (a3) 1.096 0.032 34.033 0.000 0.818 0.684
## t2_pr__04 (a4) 1.168 0.028 41.826 0.000 0.872 0.814
## t2_pr__05 (a5) 1.164 0.034 33.805 0.000 0.869 0.675
## t2_pr__06 (a6) 1.198 0.031 38.839 0.000 0.895 0.772
## t2_pr__07 (a7) 1.335 0.034 39.462 0.000 0.997 0.802
## t2_pr__08 (a8) 1.242 0.032 39.320 0.000 0.928 0.789
## t2_pr__09 (a9) 1.138 0.029 39.675 0.000 0.850 0.792
## t3_pri_con_f =~
## t3_pr__01 1.000 0.754 0.703
## t3_pr__02 (a2) 0.942 0.027 35.461 0.000 0.710 0.703
## t3_pr__03 (a3) 1.096 0.032 34.033 0.000 0.826 0.685
## t3_pr__04 (a4) 1.168 0.028 41.826 0.000 0.881 0.826
## t3_pr__05 (a5) 1.164 0.034 33.805 0.000 0.878 0.675
## t3_pr__06 (a6) 1.198 0.031 38.839 0.000 0.904 0.780
## t3_pr__07 (a7) 1.335 0.034 39.462 0.000 1.007 0.803
## t3_pr__08 (a8) 1.242 0.032 39.320 0.000 0.937 0.804
## t3_pr__09 (a9) 1.138 0.029 39.675 0.000 0.859 0.796
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t2_pri_con_01 ~~
## .t3_pri_con_01 0.188 0.018 10.446 0.000 0.188 0.319
## .t1_pri_con_01 ~~
## .t3_pri_con_01 0.200 0.019 10.654 0.000 0.200 0.327
## .t2_pri_con_02 ~~
## .t3_pri_con_02 0.186 0.016 11.291 0.000 0.186 0.349
## .t1_pri_con_02 ~~
## .t3_pri_con_02 0.165 0.016 10.194 0.000 0.165 0.311
## .t2_pri_con_03 ~~
## .t3_pri_con_03 0.405 0.025 16.146 0.000 0.405 0.528
## .t1_pri_con_03 ~~
## .t3_pri_con_03 0.385 0.026 14.960 0.000 0.385 0.481
## .t2_pri_con_04 ~~
## .t3_pri_con_04 0.047 0.012 3.914 0.000 0.047 0.126
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.061 0.013 4.830 0.000 0.061 0.158
## .t2_pri_con_05 ~~
## .t3_pri_con_05 0.381 0.029 13.287 0.000 0.381 0.418
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.403 0.029 13.825 0.000 0.403 0.441
## .t2_pri_con_06 ~~
## .t3_pri_con_06 0.156 0.017 9.249 0.000 0.156 0.293
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.153 0.017 8.735 0.000 0.153 0.274
## .t2_pri_con_07 ~~
## .t3_pri_con_07 0.193 0.018 10.525 0.000 0.193 0.349
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.232 0.020 11.680 0.000 0.232 0.393
## .t2_pri_con_08 ~~
## .t3_pri_con_08 0.165 0.017 9.970 0.000 0.165 0.330
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.173 0.017 10.032 0.000 0.173 0.331
## .t2_pri_con_09 ~~
## .t3_pri_con_09 0.129 0.014 9.275 0.000 0.129 0.301
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.111 0.014 8.000 0.000 0.111 0.258
## .t1_pri_con_01 ~~
## .t2_pri_con_01 0.213 0.019 11.275 0.000 0.213 0.344
## .t1_pri_con_02 ~~
## .t2_pri_con_02 0.189 0.017 11.345 0.000 0.189 0.347
## .t1_pri_con_03 ~~
## .t2_pri_con_03 0.357 0.025 14.208 0.000 0.357 0.451
## .t1_pri_con_04 ~~
## .t2_pri_con_04 0.065 0.013 5.037 0.000 0.065 0.162
## .t1_pri_con_05 ~~
## .t2_pri_con_05 0.358 0.028 12.614 0.000 0.358 0.396
## .t1_pri_con_06 ~~
## .t2_pri_con_06 0.148 0.018 8.366 0.000 0.148 0.261
## .t1_pri_con_07 ~~
## .t2_pri_con_07 0.209 0.019 10.791 0.000 0.209 0.357
## .t1_pri_con_08 ~~
## .t2_pri_con_08 0.141 0.018 8.073 0.000 0.141 0.259
## .t1_pri_con_09 ~~
## .t2_pri_con_09 0.097 0.014 7.049 0.000 0.097 0.225
## t1_pri_con_f ~~
## t2_pri_con_f 0.428 0.026 16.458 0.000 0.783 0.783
## t3_pri_con_f 0.422 0.026 16.288 0.000 0.764 0.764
## t2_pri_con_f ~~
## t3_pri_con_f 0.442 0.027 16.529 0.000 0.784 0.784
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 3.334 0.029 114.874 0.000 3.334 3.071
## .t1_pri_con_02 3.834 0.027 142.129 0.000 3.834 3.801
## .t1_pri_con_03 3.623 0.032 111.773 0.000 3.623 2.989
## .t1_pri_con_04 3.745 0.029 130.858 0.000 3.745 3.498
## .t1_pri_con_05 3.842 0.034 112.133 0.000 3.842 3.007
## .t1_pri_con_06 3.314 0.031 106.100 0.000 3.314 2.837
## .t1_pri_con_07 3.623 0.034 107.859 0.000 3.623 2.883
## .t1_pri_con_08 3.624 0.032 114.692 0.000 3.624 3.066
## .t1_pri_con_09 4.095 0.028 144.074 0.000 4.095 3.852
## .t2_pri_con_01 3.334 0.029 116.232 0.000 3.334 3.106
## .t2_pri_con_02 3.824 0.027 140.175 0.000 3.824 3.745
## .t2_pri_con_03 3.577 0.032 111.955 0.000 3.577 2.991
## .t2_pri_con_04 3.675 0.029 128.218 0.000 3.675 3.428
## .t2_pri_con_05 3.784 0.034 109.689 0.000 3.784 2.940
## .t2_pri_con_06 3.258 0.031 105.070 0.000 3.258 2.810
## .t2_pri_con_07 3.555 0.033 107.036 0.000 3.555 2.861
## .t2_pri_con_08 3.551 0.031 112.944 0.000 3.551 3.020
## .t2_pri_con_09 3.994 0.029 139.243 0.000 3.994 3.721
## .t3_pri_con_01 3.337 0.029 116.272 0.000 3.337 3.109
## .t3_pri_con_02 3.770 0.027 139.573 0.000 3.770 3.733
## .t3_pri_con_03 3.557 0.032 110.256 0.000 3.557 2.949
## .t3_pri_con_04 3.664 0.029 128.465 0.000 3.664 3.435
## .t3_pri_con_05 3.710 0.035 106.313 0.000 3.710 2.851
## .t3_pri_con_06 3.255 0.031 105.108 0.000 3.255 2.811
## .t3_pri_con_07 3.492 0.034 104.143 0.000 3.492 2.785
## .t3_pri_con_08 3.560 0.031 114.166 0.000 3.560 3.054
## .t3_pri_con_09 3.960 0.029 137.190 0.000 3.960 3.669
## t1_pri_con_f 0.000 0.000 0.000
## t2_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_01 0.643 0.026 24.529 0.000 0.643 0.546
## .t1_pri_con_02 0.543 0.022 24.367 0.000 0.543 0.533
## .t1_pri_con_03 0.827 0.034 24.399 0.000 0.827 0.563
## .t1_pri_con_04 0.415 0.019 22.280 0.000 0.415 0.362
## .t1_pri_con_05 0.907 0.037 24.315 0.000 0.907 0.556
## .t1_pri_con_06 0.595 0.025 23.518 0.000 0.595 0.436
## .t1_pri_con_07 0.625 0.028 22.703 0.000 0.625 0.396
## .t1_pri_con_08 0.571 0.025 22.838 0.000 0.571 0.408
## .t1_pri_con_09 0.437 0.019 22.697 0.000 0.437 0.386
## .t2_pri_con_01 0.595 0.024 24.560 0.000 0.595 0.516
## .t2_pri_con_02 0.548 0.022 24.479 0.000 0.548 0.526
## .t2_pri_con_03 0.760 0.031 24.346 0.000 0.760 0.532
## .t2_pri_con_04 0.388 0.017 22.340 0.000 0.388 0.338
## .t2_pri_con_05 0.901 0.037 24.475 0.000 0.901 0.544
## .t2_pri_con_06 0.543 0.023 23.449 0.000 0.543 0.404
## .t2_pri_con_07 0.550 0.024 22.548 0.000 0.550 0.356
## .t2_pri_con_08 0.522 0.023 22.707 0.000 0.522 0.378
## .t2_pri_con_09 0.430 0.019 22.703 0.000 0.430 0.373
## .t3_pri_con_01 0.583 0.024 24.323 0.000 0.583 0.506
## .t3_pri_con_02 0.516 0.021 24.116 0.000 0.516 0.506
## .t3_pri_con_03 0.772 0.032 24.254 0.000 0.772 0.531
## .t3_pri_con_04 0.361 0.016 21.902 0.000 0.361 0.318
## .t3_pri_con_05 0.923 0.038 24.588 0.000 0.923 0.545
## .t3_pri_con_06 0.525 0.022 23.386 0.000 0.525 0.391
## .t3_pri_con_07 0.559 0.025 22.459 0.000 0.559 0.355
## .t3_pri_con_08 0.481 0.022 22.322 0.000 0.481 0.354
## .t3_pri_con_09 0.427 0.019 22.773 0.000 0.427 0.367
## t1_pri_con_f 0.536 0.030 17.573 0.000 1.000 1.000
## t2_pri_con_f 0.558 0.031 17.728 0.000 1.000 1.000
## t3_pri_con_f 0.569 0.032 17.672 0.000 1.000 1.0001.2.2.3 Second-Order Model Unconstrained
We again run models in which we build sub-dimensions referring to the empirical EFA results and theoretical considerations. Resulting model fits the data better than unidimensional one.
model <- '
# create factors
t1_inf_sha_att_f =~ 1*t1_inf_sha_att_f1 + t1_inf_sha_att_f2 + t1_inf_sha_att_f3 + t1_inf_sha_att_f4 + t1_inf_sha_att_f5
t2_inf_sha_att_f =~ 1*t2_inf_sha_att_f1 + t2_inf_sha_att_f2 + t2_inf_sha_att_f3 + t2_inf_sha_att_f4 + t2_inf_sha_att_f5
t3_inf_sha_att_f =~ 1*t3_inf_sha_att_f1 + t3_inf_sha_att_f2 + t3_inf_sha_att_f3 + t3_inf_sha_att_f4 + t3_inf_sha_att_f5
t1_inf_sha_att_f1 =~ 1*t1_inf_sha_att_01 + t1_inf_sha_att_02
t1_inf_sha_att_f2 =~ 1*t1_inf_sha_att_03 + t1_inf_sha_att_04
t1_inf_sha_att_f3 =~ 1*t1_inf_sha_att_05 + t1_inf_sha_att_06
t1_inf_sha_att_f4 =~ 1*t1_inf_sha_att_07 + t1_inf_sha_att_08
t1_inf_sha_att_f5 =~ 1*t1_inf_sha_att_10 + t1_inf_sha_att_11
t2_inf_sha_att_f1 =~ 1*t2_inf_sha_att_01 + t2_inf_sha_att_02
t2_inf_sha_att_f2 =~ 1*t2_inf_sha_att_03 + t2_inf_sha_att_04
t2_inf_sha_att_f3 =~ 1*t2_inf_sha_att_05 + t2_inf_sha_att_06
t2_inf_sha_att_f4 =~ 1*t2_inf_sha_att_07 + t2_inf_sha_att_08
t2_inf_sha_att_f5 =~ 1*t2_inf_sha_att_10 + t2_inf_sha_att_11
t3_inf_sha_att_f1 =~ 1*t3_inf_sha_att_01 + t3_inf_sha_att_02
t3_inf_sha_att_f2 =~ 1*t3_inf_sha_att_03 + t3_inf_sha_att_04
t3_inf_sha_att_f3 =~ 1*t3_inf_sha_att_05 + t3_inf_sha_att_06
t3_inf_sha_att_f4 =~ 1*t3_inf_sha_att_07 + t3_inf_sha_att_08
t3_inf_sha_att_f5 =~ 1*t3_inf_sha_att_10 + t3_inf_sha_att_11
# factor covariance
t1_inf_sha_att_f ~~ t2_inf_sha_att_f + t3_inf_sha_att_f
t2_inf_sha_att_f ~~ t3_inf_sha_att_f
# item error covariance
t1_inf_sha_att_01 ~~ t2_inf_sha_att_01 + t3_inf_sha_att_01
t2_inf_sha_att_01 ~~ t3_inf_sha_att_01
t1_inf_sha_att_02 ~~ t2_inf_sha_att_02 + t3_inf_sha_att_02
t2_inf_sha_att_02 ~~ t3_inf_sha_att_02
t1_inf_sha_att_03 ~~ t2_inf_sha_att_03 + t3_inf_sha_att_03
t2_inf_sha_att_03 ~~ t3_inf_sha_att_03
t1_inf_sha_att_04 ~~ t2_inf_sha_att_04 + t3_inf_sha_att_04
t2_inf_sha_att_04 ~~ t3_inf_sha_att_04
t1_inf_sha_att_05 ~~ t2_inf_sha_att_05 + t3_inf_sha_att_05
t2_inf_sha_att_05 ~~ t3_inf_sha_att_05
t1_inf_sha_att_06 ~~ t2_inf_sha_att_06 + t3_inf_sha_att_06
t2_inf_sha_att_06 ~~ t3_inf_sha_att_06
t1_inf_sha_att_07 ~~ t2_inf_sha_att_07 + t3_inf_sha_att_07
t2_inf_sha_att_07 ~~ t3_inf_sha_att_07
t1_inf_sha_att_08 ~~ t2_inf_sha_att_08 + t3_inf_sha_att_08
t2_inf_sha_att_08 ~~ t3_inf_sha_att_08
t1_inf_sha_att_10 ~~ t2_inf_sha_att_10 + t3_inf_sha_att_10
t2_inf_sha_att_10 ~~ t3_inf_sha_att_10
t1_inf_sha_att_11 ~~ t2_inf_sha_att_11 + t3_inf_sha_att_11
t2_inf_sha_att_11 ~~ t3_inf_sha_att_11
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 182 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 138
##
## Number of observations 1403
## Number of missing patterns 43
##
## Model Test User Model:
##
## Test statistic 2673.738
## Degrees of freedom 357
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 34051.217
## Degrees of freedom 435
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.931
## Tucker-Lewis Index (TLI) 0.916
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -47028.014
## Loglikelihood unrestricted model (H1) -45691.145
##
## Akaike (AIC) 94332.028
## Bayesian (BIC) 95056.027
## Sample-size adjusted Bayesian (BIC) 94617.652
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.068
## 90 Percent confidence interval - lower 0.066
## 90 Percent confidence interval - upper 0.070
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.080
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_att_f =~
## t1_nf_sh_tt_f1 1.000 0.397 0.397
## t1_nf_sh_tt_f2 3.125 0.297 10.528 0.000 0.951 0.951
## t1_nf_sh_tt_f3 3.047 0.289 10.531 0.000 0.934 0.934
## t1_nf_sh_tt_f4 2.315 0.226 10.222 0.000 0.875 0.875
## t1_nf_sh_tt_f5 1.469 0.163 9.037 0.000 0.460 0.460
## t2_inf_sha_att_f =~
## t2_nf_sh_tt_f1 1.000 0.439 0.439
## t2_nf_sh_tt_f2 2.946 0.269 10.948 0.000 0.959 0.959
## t2_nf_sh_tt_f3 2.948 0.269 10.940 0.000 0.948 0.948
## t2_nf_sh_tt_f4 2.172 0.206 10.561 0.000 0.905 0.905
## t2_nf_sh_tt_f5 1.445 0.153 9.440 0.000 0.479 0.479
## t3_inf_sha_att_f =~
## t3_nf_sh_tt_f1 1.000 0.446 0.446
## t3_nf_sh_tt_f2 2.798 0.250 11.195 0.000 0.931 0.931
## t3_nf_sh_tt_f3 2.710 0.243 11.164 0.000 0.920 0.920
## t3_nf_sh_tt_f4 2.117 0.195 10.833 0.000 0.893 0.893
## t3_nf_sh_tt_f5 1.534 0.155 9.869 0.000 0.513 0.513
## t1_inf_sha_att_f1 =~
## t1_nf_sh_tt_01 1.000 0.779 0.700
## t1_nf_sh_tt_02 0.866 0.090 9.652 0.000 0.675 0.615
## t1_inf_sha_att_f2 =~
## t1_nf_sh_tt_03 1.000 1.018 0.923
## t1_nf_sh_tt_04 0.934 0.017 53.982 0.000 0.951 0.895
## t1_inf_sha_att_f3 =~
## t1_nf_sh_tt_05 1.000 1.010 0.944
## t1_nf_sh_tt_06 0.946 0.017 55.477 0.000 0.955 0.879
## t1_inf_sha_att_f4 =~
## t1_nf_sh_tt_07 1.000 0.820 0.747
## t1_nf_sh_tt_08 0.902 0.036 25.388 0.000 0.739 0.693
## t1_inf_sha_att_f5 =~
## t1_nf_sh_tt_10 1.000 0.988 0.936
## t1_nf_sh_tt_11 0.968 0.034 28.783 0.000 0.957 0.913
## t2_inf_sha_att_f1 =~
## t2_nf_sh_tt_01 1.000 0.739 0.650
## t2_nf_sh_tt_02 0.888 0.088 10.091 0.000 0.657 0.604
## t2_inf_sha_att_f2 =~
## t2_nf_sh_tt_03 1.000 0.996 0.917
## t2_nf_sh_tt_04 0.955 0.018 53.384 0.000 0.951 0.888
## t2_inf_sha_att_f3 =~
## t2_nf_sh_tt_05 1.000 1.008 0.946
## t2_nf_sh_tt_06 0.941 0.017 54.045 0.000 0.949 0.866
## t2_inf_sha_att_f4 =~
## t2_nf_sh_tt_07 1.000 0.778 0.719
## t2_nf_sh_tt_08 0.921 0.038 24.499 0.000 0.716 0.671
## t2_inf_sha_att_f5 =~
## t2_nf_sh_tt_10 1.000 0.978 0.940
## t2_nf_sh_tt_11 0.999 0.031 32.366 0.000 0.976 0.929
## t3_inf_sha_att_f1 =~
## t3_nf_sh_tt_01 1.000 0.744 0.657
## t3_nf_sh_tt_02 0.885 0.084 10.536 0.000 0.659 0.618
## t3_inf_sha_att_f2 =~
## t3_nf_sh_tt_03 1.000 0.998 0.933
## t3_nf_sh_tt_04 0.935 0.018 53.069 0.000 0.933 0.886
## t3_inf_sha_att_f3 =~
## t3_nf_sh_tt_05 1.000 0.978 0.934
## t3_nf_sh_tt_06 0.949 0.019 50.701 0.000 0.928 0.872
## t3_inf_sha_att_f4 =~
## t3_nf_sh_tt_07 1.000 0.787 0.752
## t3_nf_sh_tt_08 0.882 0.035 25.094 0.000 0.694 0.674
## t3_inf_sha_att_f5 =~
## t3_nf_sh_tt_10 1.000 0.993 0.950
## t3_nf_sh_tt_11 0.959 0.029 33.537 0.000 0.953 0.915
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_att_f ~~
## t2_inf_sh_tt_f 0.058 0.009 6.663 0.000 0.574 0.574
## t3_inf_sh_tt_f 0.058 0.009 6.710 0.000 0.561 0.561
## t2_inf_sha_att_f ~~
## t3_inf_sh_tt_f 0.068 0.010 6.846 0.000 0.634 0.634
## .t1_inf_sha_att_01 ~~
## .t2_nf_sh_tt_01 0.293 0.029 9.950 0.000 0.293 0.426
## .t3_nf_sh_tt_01 0.306 0.029 10.516 0.000 0.306 0.451
## .t2_inf_sha_att_01 ~~
## .t3_nf_sh_tt_01 0.339 0.031 11.031 0.000 0.339 0.460
## .t1_inf_sha_att_02 ~~
## .t2_nf_sh_tt_02 0.345 0.029 12.033 0.000 0.345 0.461
## .t3_nf_sh_tt_02 0.326 0.028 11.694 0.000 0.326 0.451
## .t2_inf_sha_att_02 ~~
## .t3_nf_sh_tt_02 0.393 0.029 13.749 0.000 0.393 0.542
## .t1_inf_sha_att_03 ~~
## .t2_nf_sh_tt_03 0.071 0.009 8.018 0.000 0.071 0.385
## .t3_nf_sh_tt_03 0.065 0.009 7.654 0.000 0.065 0.399
## .t2_inf_sha_att_03 ~~
## .t3_nf_sh_tt_03 0.067 0.009 7.888 0.000 0.067 0.405
## .t1_inf_sha_att_04 ~~
## .t2_nf_sh_tt_04 0.088 0.009 9.418 0.000 0.088 0.378
## .t3_nf_sh_tt_04 0.074 0.009 8.031 0.000 0.074 0.318
## .t2_inf_sha_att_04 ~~
## .t3_nf_sh_tt_04 0.098 0.010 10.194 0.000 0.098 0.408
## .t1_inf_sha_att_05 ~~
## .t2_nf_sh_tt_05 0.032 0.008 4.320 0.000 0.032 0.264
## .t3_nf_sh_tt_05 0.036 0.008 4.669 0.000 0.036 0.275
## .t2_inf_sha_att_05 ~~
## .t3_nf_sh_tt_05 0.027 0.008 3.518 0.000 0.027 0.207
## .t1_inf_sha_att_06 ~~
## .t2_nf_sh_tt_06 0.152 0.011 13.978 0.000 0.152 0.536
## .t3_nf_sh_tt_06 0.129 0.010 12.355 0.000 0.129 0.477
## .t2_inf_sha_att_06 ~~
## .t3_nf_sh_tt_06 0.137 0.011 12.677 0.000 0.137 0.478
## .t1_inf_sha_att_07 ~~
## .t2_nf_sh_tt_07 0.269 0.020 13.335 0.000 0.269 0.490
## .t3_nf_sh_tt_07 0.240 0.019 12.636 0.000 0.240 0.476
## .t2_inf_sha_att_07 ~~
## .t3_nf_sh_tt_07 0.279 0.020 14.312 0.000 0.279 0.537
## .t1_inf_sha_att_08 ~~
## .t2_nf_sh_tt_08 0.260 0.021 12.509 0.000 0.260 0.427
## .t3_nf_sh_tt_08 0.275 0.020 13.608 0.000 0.275 0.469
## .t2_inf_sha_att_08 ~~
## .t3_nf_sh_tt_08 0.267 0.020 13.031 0.000 0.267 0.442
## .t1_inf_sha_att_10 ~~
## .t2_nf_sh_tt_10 0.032 0.011 3.002 0.003 0.032 0.243
## .t3_nf_sh_tt_10 0.008 0.011 0.742 0.458 0.008 0.066
## .t2_inf_sha_att_10 ~~
## .t3_nf_sh_tt_10 0.006 0.010 0.543 0.587 0.006 0.049
## .t1_inf_sha_att_11 ~~
## .t2_nf_sh_tt_11 0.037 0.011 3.417 0.001 0.037 0.222
## .t3_nf_sh_tt_11 0.051 0.011 4.794 0.000 0.051 0.286
## .t2_inf_sha_att_11 ~~
## .t3_nf_sh_tt_11 0.046 0.010 4.391 0.000 0.046 0.280
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_tt_01 1.704 0.030 57.252 0.000 1.704 1.530
## .t1_nf_sh_tt_02 1.900 0.029 64.798 0.000 1.900 1.732
## .t1_nf_sh_tt_03 2.788 0.029 94.585 0.000 2.788 2.527
## .t1_nf_sh_tt_04 2.940 0.028 103.535 0.000 2.940 2.766
## .t1_nf_sh_tt_05 2.626 0.029 91.827 0.000 2.626 2.453
## .t1_nf_sh_tt_06 2.373 0.029 81.700 0.000 2.373 2.183
## .t1_nf_sh_tt_07 3.010 0.029 102.640 0.000 3.010 2.742
## .t1_nf_sh_tt_08 2.294 0.029 80.462 0.000 2.294 2.150
## .t1_nf_sh_tt_10 2.249 0.028 79.658 0.000 2.249 2.129
## .t1_nf_sh_tt_11 2.295 0.028 81.956 0.000 2.295 2.191
## .t2_nf_sh_tt_01 1.763 0.030 57.925 0.000 1.763 1.551
## .t2_nf_sh_tt_02 1.931 0.029 66.323 0.000 1.931 1.777
## .t2_nf_sh_tt_03 2.904 0.029 99.901 0.000 2.904 2.673
## .t2_nf_sh_tt_04 2.999 0.029 104.561 0.000 2.999 2.799
## .t2_nf_sh_tt_05 2.711 0.029 95.014 0.000 2.711 2.543
## .t2_nf_sh_tt_06 2.428 0.029 82.780 0.000 2.428 2.216
## .t2_nf_sh_tt_07 3.119 0.029 107.573 0.000 3.119 2.881
## .t2_nf_sh_tt_08 2.332 0.029 81.491 0.000 2.332 2.182
## .t2_nf_sh_tt_10 2.271 0.028 81.411 0.000 2.271 2.183
## .t2_nf_sh_tt_11 2.363 0.028 83.883 0.000 2.363 2.249
## .t3_nf_sh_tt_01 1.777 0.030 58.735 0.000 1.777 1.569
## .t3_nf_sh_tt_02 1.887 0.028 66.336 0.000 1.887 1.771
## .t3_nf_sh_tt_03 2.951 0.029 103.343 0.000 2.951 2.759
## .t3_nf_sh_tt_04 3.057 0.028 108.669 0.000 3.057 2.901
## .t3_nf_sh_tt_05 2.737 0.028 97.897 0.000 2.737 2.614
## .t3_nf_sh_tt_06 2.473 0.028 87.000 0.000 2.473 2.323
## .t3_nf_sh_tt_07 3.103 0.028 110.981 0.000 3.103 2.965
## .t3_nf_sh_tt_08 2.367 0.028 85.984 0.000 2.367 2.297
## .t3_nf_sh_tt_10 2.297 0.028 82.238 0.000 2.297 2.197
## .t3_nf_sh_tt_11 2.366 0.028 85.092 0.000 2.366 2.272
## t1_inf_sh_tt_f 0.000 0.000 0.000
## t2_inf_sh_tt_f 0.000 0.000 0.000
## t3_inf_sh_tt_f 0.000 0.000 0.000
## .t1_nf_sh_tt_f1 0.000 0.000 0.000
## .t1_nf_sh_tt_f2 0.000 0.000 0.000
## .t1_nf_sh_tt_f3 0.000 0.000 0.000
## .t1_nf_sh_tt_f4 0.000 0.000 0.000
## .t1_nf_sh_tt_f5 0.000 0.000 0.000
## .t2_nf_sh_tt_f1 0.000 0.000 0.000
## .t2_nf_sh_tt_f2 0.000 0.000 0.000
## .t2_nf_sh_tt_f3 0.000 0.000 0.000
## .t2_nf_sh_tt_f4 0.000 0.000 0.000
## .t2_nf_sh_tt_f5 0.000 0.000 0.000
## .t3_nf_sh_tt_f1 0.000 0.000 0.000
## .t3_nf_sh_tt_f2 0.000 0.000 0.000
## .t3_nf_sh_tt_f3 0.000 0.000 0.000
## .t3_nf_sh_tt_f4 0.000 0.000 0.000
## .t3_nf_sh_tt_f5 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_tt_01 0.633 0.067 9.405 0.000 0.633 0.510
## .t1_nf_sh_tt_02 0.748 0.055 13.493 0.000 0.748 0.621
## .t1_nf_sh_tt_03 0.181 0.013 13.828 0.000 0.181 0.148
## .t1_nf_sh_tt_04 0.225 0.013 17.462 0.000 0.225 0.199
## .t1_nf_sh_tt_05 0.125 0.012 10.754 0.000 0.125 0.109
## .t1_nf_sh_tt_06 0.268 0.014 19.042 0.000 0.268 0.227
## .t1_nf_sh_tt_07 0.533 0.029 18.143 0.000 0.533 0.442
## .t1_nf_sh_tt_08 0.591 0.029 20.714 0.000 0.591 0.520
## .t1_nf_sh_tt_10 0.139 0.031 4.444 0.000 0.139 0.125
## .t1_nf_sh_tt_11 0.182 0.029 6.191 0.000 0.182 0.166
## .t2_nf_sh_tt_01 0.746 0.062 12.115 0.000 0.746 0.577
## .t2_nf_sh_tt_02 0.750 0.052 14.432 0.000 0.750 0.635
## .t2_nf_sh_tt_03 0.188 0.013 14.749 0.000 0.188 0.159
## .t2_nf_sh_tt_04 0.243 0.013 18.270 0.000 0.243 0.212
## .t2_nf_sh_tt_05 0.120 0.011 10.654 0.000 0.120 0.106
## .t2_nf_sh_tt_06 0.300 0.015 20.340 0.000 0.300 0.250
## .t2_nf_sh_tt_07 0.567 0.030 19.101 0.000 0.567 0.483
## .t2_nf_sh_tt_08 0.628 0.029 21.368 0.000 0.628 0.550
## .t2_nf_sh_tt_10 0.127 0.027 4.711 0.000 0.127 0.117
## .t2_nf_sh_tt_11 0.151 0.027 5.620 0.000 0.151 0.137
## .t3_nf_sh_tt_01 0.730 0.060 12.180 0.000 0.730 0.569
## .t3_nf_sh_tt_02 0.701 0.050 14.131 0.000 0.701 0.618
## .t3_nf_sh_tt_03 0.148 0.013 11.737 0.000 0.148 0.129
## .t3_nf_sh_tt_04 0.239 0.013 17.962 0.000 0.239 0.215
## .t3_nf_sh_tt_05 0.140 0.013 11.159 0.000 0.140 0.127
## .t3_nf_sh_tt_06 0.273 0.015 18.789 0.000 0.273 0.240
## .t3_nf_sh_tt_07 0.476 0.027 17.545 0.000 0.476 0.435
## .t3_nf_sh_tt_08 0.580 0.027 21.640 0.000 0.580 0.546
## .t3_nf_sh_tt_10 0.107 0.026 4.062 0.000 0.107 0.098
## .t3_nf_sh_tt_11 0.176 0.025 7.192 0.000 0.176 0.163
## t1_inf_sh_tt_f 0.096 0.018 5.241 0.000 1.000 1.000
## t2_inf_sh_tt_f 0.105 0.019 5.434 0.000 1.000 1.000
## t3_inf_sh_tt_f 0.110 0.020 5.572 0.000 1.000 1.000
## .t1_nf_sh_tt_f1 0.511 0.064 7.962 0.000 0.842 0.842
## .t1_nf_sh_tt_f2 0.100 0.015 6.739 0.000 0.096 0.096
## .t1_nf_sh_tt_f3 0.130 0.015 8.721 0.000 0.127 0.127
## .t1_nf_sh_tt_f4 0.158 0.021 7.662 0.000 0.235 0.235
## .t1_nf_sh_tt_f5 0.769 0.043 17.844 0.000 0.788 0.788
## .t2_nf_sh_tt_f1 0.441 0.056 7.932 0.000 0.808 0.808
## .t2_nf_sh_tt_f2 0.080 0.013 6.130 0.000 0.081 0.081
## .t2_nf_sh_tt_f3 0.103 0.014 7.475 0.000 0.101 0.101
## .t2_nf_sh_tt_f4 0.110 0.019 5.889 0.000 0.181 0.181
## .t2_nf_sh_tt_f5 0.737 0.039 18.807 0.000 0.770 0.770
## .t3_nf_sh_tt_f1 0.444 0.054 8.242 0.000 0.801 0.801
## .t3_nf_sh_tt_f2 0.134 0.015 8.649 0.000 0.134 0.134
## .t3_nf_sh_tt_f3 0.147 0.016 9.452 0.000 0.154 0.154
## .t3_nf_sh_tt_f4 0.125 0.019 6.681 0.000 0.203 0.203
## .t3_nf_sh_tt_f5 0.727 0.039 18.732 0.000 0.737 0.7371.2.2.4 Second-Order Model at All Waves Constrained
model <- '
# create factors
t1_inf_sha_att_f =~ 1*t1_inf_sha_att_f1 + o2*t1_inf_sha_att_f2 + o3*t1_inf_sha_att_f3 + o4*t1_inf_sha_att_f4 + o5*t1_inf_sha_att_f5
t2_inf_sha_att_f =~ 1*t2_inf_sha_att_f1 + o2*t2_inf_sha_att_f2 + o3*t2_inf_sha_att_f3 + o4*t2_inf_sha_att_f4 + o5*t2_inf_sha_att_f5
t3_inf_sha_att_f =~ 1*t3_inf_sha_att_f1 + o2*t3_inf_sha_att_f2 + o3*t3_inf_sha_att_f3 + o4*t3_inf_sha_att_f4 + o5*t3_inf_sha_att_f5
t1_inf_sha_att_f1 =~ 1*t1_inf_sha_att_01 + j2*t1_inf_sha_att_02
t1_inf_sha_att_f2 =~ 1*t1_inf_sha_att_03 + k2*t1_inf_sha_att_04
t1_inf_sha_att_f3 =~ 1*t1_inf_sha_att_05 + l2*t1_inf_sha_att_06
t1_inf_sha_att_f4 =~ 1*t1_inf_sha_att_07 + m2*t1_inf_sha_att_08
t1_inf_sha_att_f5 =~ 1*t1_inf_sha_att_10 + n2*t1_inf_sha_att_11
t2_inf_sha_att_f1 =~ 1*t2_inf_sha_att_01 + j2*t2_inf_sha_att_02
t2_inf_sha_att_f2 =~ 1*t2_inf_sha_att_03 + k2*t2_inf_sha_att_04
t2_inf_sha_att_f3 =~ 1*t2_inf_sha_att_05 + l2*t2_inf_sha_att_06
t2_inf_sha_att_f4 =~ 1*t2_inf_sha_att_07 + m2*t2_inf_sha_att_08
t2_inf_sha_att_f5 =~ 1*t2_inf_sha_att_10 + n2*t2_inf_sha_att_11
t3_inf_sha_att_f1 =~ 1*t3_inf_sha_att_01 + j2*t3_inf_sha_att_02
t3_inf_sha_att_f2 =~ 1*t3_inf_sha_att_03 + k2*t3_inf_sha_att_04
t3_inf_sha_att_f3 =~ 1*t3_inf_sha_att_05 + l2*t3_inf_sha_att_06
t3_inf_sha_att_f4 =~ 1*t3_inf_sha_att_07 + m2*t3_inf_sha_att_08
t3_inf_sha_att_f5 =~ 1*t3_inf_sha_att_10 + n2*t3_inf_sha_att_11
# factor covariance
t1_inf_sha_att_f ~~ t2_inf_sha_att_f + t3_inf_sha_att_f
t2_inf_sha_att_f ~~ t3_inf_sha_att_f
# item error covariance
t1_inf_sha_att_01 ~~ t2_inf_sha_att_01 + t3_inf_sha_att_01
t2_inf_sha_att_01 ~~ t3_inf_sha_att_01
t1_inf_sha_att_02 ~~ t2_inf_sha_att_02 + t3_inf_sha_att_02
t2_inf_sha_att_02 ~~ t3_inf_sha_att_02
t1_inf_sha_att_03 ~~ t2_inf_sha_att_03 + t3_inf_sha_att_03
t2_inf_sha_att_03 ~~ t3_inf_sha_att_03
t1_inf_sha_att_04 ~~ t2_inf_sha_att_04 + t3_inf_sha_att_04
t2_inf_sha_att_04 ~~ t3_inf_sha_att_04
t1_inf_sha_att_05 ~~ t2_inf_sha_att_05 + t3_inf_sha_att_05
t2_inf_sha_att_05 ~~ t3_inf_sha_att_05
t1_inf_sha_att_06 ~~ t2_inf_sha_att_06 + t3_inf_sha_att_06
t2_inf_sha_att_06 ~~ t3_inf_sha_att_06
t1_inf_sha_att_07 ~~ t2_inf_sha_att_07 + t3_inf_sha_att_07
t2_inf_sha_att_07 ~~ t3_inf_sha_att_07
t1_inf_sha_att_08 ~~ t2_inf_sha_att_08 + t3_inf_sha_att_08
t2_inf_sha_att_08 ~~ t3_inf_sha_att_08
t1_inf_sha_att_10 ~~ t2_inf_sha_att_10 + t3_inf_sha_att_10
t2_inf_sha_att_10 ~~ t3_inf_sha_att_10
t1_inf_sha_att_11 ~~ t2_inf_sha_att_11 + t3_inf_sha_att_11
t2_inf_sha_att_11 ~~ t3_inf_sha_att_11
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 146 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 138
## Number of equality constraints 18
##
## Number of observations 1403
## Number of missing patterns 43
##
## Model Test User Model:
##
## Test statistic 2683.427
## Degrees of freedom 375
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 34051.217
## Degrees of freedom 435
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.931
## Tucker-Lewis Index (TLI) 0.920
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -47032.859
## Loglikelihood unrestricted model (H1) -45691.145
##
## Akaike (AIC) 94305.718
## Bayesian (BIC) 94935.282
## Sample-size adjusted Bayesian (BIC) 94554.087
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.066
## 90 Percent confidence interval - lower 0.064
## 90 Percent confidence interval - upper 0.069
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.080
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_att_f =~
## t1_nf___1 1.000 0.417 0.417
## t1_nf___2 (o2) 2.954 0.179 16.540 0.000 0.950 0.950
## t1_nf___3 (o3) 2.902 0.175 16.543 0.000 0.934 0.934
## t1_nf___4 (o4) 2.201 0.138 15.934 0.000 0.875 0.875
## t1_nf___5 (o5) 1.483 0.101 14.749 0.000 0.484 0.484
## t2_inf_sha_att_f =~
## t2_nf___1 1.000 0.439 0.439
## t2_nf___2 (o2) 2.954 0.179 16.540 0.000 0.960 0.960
## t2_nf___3 (o3) 2.902 0.175 16.543 0.000 0.946 0.946
## t2_nf___4 (o4) 2.201 0.138 15.934 0.000 0.907 0.907
## t2_nf___5 (o5) 1.483 0.101 14.749 0.000 0.487 0.487
## t3_inf_sha_att_f =~
## t3_nf___1 1.000 0.425 0.425
## t3_nf___2 (o2) 2.954 0.179 16.540 0.000 0.931 0.931
## t3_nf___3 (o3) 2.902 0.175 16.543 0.000 0.924 0.924
## t3_nf___4 (o4) 2.201 0.138 15.934 0.000 0.891 0.891
## t3_nf___5 (o5) 1.483 0.101 14.749 0.000 0.481 0.481
## t1_inf_sha_att_f1 =~
## t1_n___01 1.000 0.780 0.698
## t1_n___02 (j2) 0.881 0.062 14.292 0.000 0.687 0.624
## t1_inf_sha_att_f2 =~
## t1_n___03 1.000 1.012 0.921
## t1_n___04 (k2) 0.941 0.012 77.226 0.000 0.952 0.896
## t1_inf_sha_att_f3 =~
## t1_n___05 1.000 1.011 0.944
## t1_n___06 (l2) 0.945 0.012 75.718 0.000 0.955 0.879
## t1_inf_sha_att_f4 =~
## t1_n___07 1.000 0.819 0.747
## t1_n___08 (m2) 0.901 0.026 35.176 0.000 0.737 0.692
## t1_inf_sha_att_f5 =~
## t1_n___10 1.000 0.997 0.934
## t1_n___11 (n2) 0.976 0.020 49.065 0.000 0.973 0.918
## t2_inf_sha_att_f1 =~
## t2_n___01 1.000 0.743 0.653
## t2_n___02 (j2) 0.881 0.062 14.292 0.000 0.654 0.602
## t2_inf_sha_att_f2 =~
## t2_n___03 1.000 1.004 0.919
## t2_n___04 (k2) 0.941 0.012 77.226 0.000 0.945 0.886
## t2_inf_sha_att_f3 =~
## t2_n___05 1.000 1.001 0.944
## t2_n___06 (l2) 0.945 0.012 75.718 0.000 0.946 0.866
## t2_inf_sha_att_f4 =~
## t2_n___07 1.000 0.792 0.726
## t2_n___08 (m2) 0.901 0.026 35.176 0.000 0.713 0.668
## t2_inf_sha_att_f5 =~
## t2_n___10 1.000 0.994 0.949
## t2_n___11 (n2) 0.976 0.020 49.065 0.000 0.969 0.921
## t3_inf_sha_att_f1 =~
## t3_n___01 1.000 0.739 0.655
## t3_n___02 (j2) 0.881 0.062 14.292 0.000 0.651 0.613
## t3_inf_sha_att_f2 =~
## t3_n___03 1.000 0.997 0.933
## t3_n___04 (k2) 0.941 0.012 77.226 0.000 0.939 0.887
## t3_inf_sha_att_f3 =~
## t3_n___05 1.000 0.987 0.936
## t3_n___06 (l2) 0.945 0.012 75.718 0.000 0.933 0.872
## t3_inf_sha_att_f4 =~
## t3_n___07 1.000 0.776 0.746
## t3_n___08 (m2) 0.901 0.026 35.176 0.000 0.699 0.677
## t3_inf_sha_att_f5 =~
## t3_n___10 1.000 0.968 0.942
## t3_n___11 (n2) 0.976 0.020 49.065 0.000 0.944 0.919
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_att_f ~~
## t2_inf_sh_tt_f 0.061 0.008 7.555 0.000 0.574 0.574
## t3_inf_sh_tt_f 0.057 0.008 7.535 0.000 0.561 0.561
## t2_inf_sha_att_f ~~
## t3_inf_sh_tt_f 0.065 0.008 7.664 0.000 0.634 0.634
## .t1_inf_sha_att_01 ~~
## .t2_nf_sh_tt_01 0.292 0.029 9.940 0.000 0.292 0.423
## .t3_nf_sh_tt_01 0.306 0.029 10.517 0.000 0.306 0.449
## .t2_inf_sha_att_01 ~~
## .t3_nf_sh_tt_01 0.339 0.031 11.038 0.000 0.339 0.462
## .t1_inf_sha_att_02 ~~
## .t2_nf_sh_tt_02 0.345 0.029 12.034 0.000 0.345 0.462
## .t3_nf_sh_tt_02 0.326 0.028 11.683 0.000 0.326 0.451
## .t2_inf_sha_att_02 ~~
## .t3_nf_sh_tt_02 0.393 0.029 13.745 0.000 0.393 0.540
## .t1_inf_sha_att_03 ~~
## .t2_nf_sh_tt_03 0.071 0.009 7.984 0.000 0.071 0.384
## .t3_nf_sh_tt_03 0.065 0.009 7.655 0.000 0.065 0.395
## .t2_inf_sha_att_03 ~~
## .t3_nf_sh_tt_03 0.067 0.009 7.854 0.000 0.067 0.404
## .t1_inf_sha_att_04 ~~
## .t2_nf_sh_tt_04 0.088 0.009 9.414 0.000 0.088 0.377
## .t3_nf_sh_tt_04 0.074 0.009 8.046 0.000 0.074 0.321
## .t2_inf_sha_att_04 ~~
## .t3_nf_sh_tt_04 0.098 0.010 10.200 0.000 0.098 0.407
## .t1_inf_sha_att_05 ~~
## .t2_nf_sh_tt_05 0.033 0.008 4.332 0.000 0.033 0.264
## .t3_nf_sh_tt_05 0.037 0.008 4.697 0.000 0.037 0.278
## .t2_inf_sha_att_05 ~~
## .t3_nf_sh_tt_05 0.027 0.008 3.517 0.000 0.027 0.207
## .t1_inf_sha_att_06 ~~
## .t2_nf_sh_tt_06 0.152 0.011 13.980 0.000 0.152 0.537
## .t3_nf_sh_tt_06 0.129 0.010 12.344 0.000 0.129 0.476
## .t2_inf_sha_att_06 ~~
## .t3_nf_sh_tt_06 0.137 0.011 12.677 0.000 0.137 0.478
## .t1_inf_sha_att_07 ~~
## .t2_nf_sh_tt_07 0.268 0.020 13.318 0.000 0.268 0.491
## .t3_nf_sh_tt_07 0.241 0.019 12.677 0.000 0.241 0.475
## .t2_inf_sha_att_07 ~~
## .t3_nf_sh_tt_07 0.279 0.019 14.313 0.000 0.279 0.536
## .t1_inf_sha_att_08 ~~
## .t2_nf_sh_tt_08 0.260 0.021 12.518 0.000 0.260 0.426
## .t3_nf_sh_tt_08 0.275 0.020 13.608 0.000 0.275 0.470
## .t2_inf_sha_att_08 ~~
## .t3_nf_sh_tt_08 0.267 0.020 13.034 0.000 0.267 0.442
## .t1_inf_sha_att_10 ~~
## .t2_nf_sh_tt_10 0.031 0.011 2.932 0.003 0.031 0.250
## .t3_nf_sh_tt_10 0.009 0.011 0.833 0.405 0.009 0.069
## .t2_inf_sha_att_10 ~~
## .t3_nf_sh_tt_10 0.006 0.010 0.554 0.579 0.006 0.051
## .t1_inf_sha_att_11 ~~
## .t2_nf_sh_tt_11 0.038 0.011 3.499 0.000 0.038 0.218
## .t3_nf_sh_tt_11 0.051 0.011 4.737 0.000 0.051 0.297
## .t2_inf_sha_att_11 ~~
## .t3_nf_sh_tt_11 0.046 0.010 4.387 0.000 0.046 0.275
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_tt_01 1.704 0.030 57.045 0.000 1.704 1.524
## .t1_nf_sh_tt_02 1.900 0.029 64.555 0.000 1.900 1.726
## .t1_nf_sh_tt_03 2.788 0.029 95.014 0.000 2.788 2.538
## .t1_nf_sh_tt_04 2.940 0.028 103.517 0.000 2.940 2.765
## .t1_nf_sh_tt_05 2.626 0.029 91.815 0.000 2.626 2.453
## .t1_nf_sh_tt_06 2.373 0.029 81.724 0.000 2.373 2.184
## .t1_nf_sh_tt_07 3.010 0.029 102.744 0.000 3.010 2.745
## .t1_nf_sh_tt_08 2.294 0.028 80.559 0.000 2.294 2.153
## .t1_nf_sh_tt_10 2.249 0.029 78.816 0.000 2.249 2.107
## .t1_nf_sh_tt_11 2.295 0.028 81.021 0.000 2.295 2.166
## .t2_nf_sh_tt_01 1.763 0.030 57.906 0.000 1.763 1.551
## .t2_nf_sh_tt_02 1.931 0.029 66.338 0.000 1.931 1.777
## .t2_nf_sh_tt_03 2.904 0.029 99.355 0.000 2.904 2.659
## .t2_nf_sh_tt_04 2.999 0.029 105.004 0.000 2.999 2.811
## .t2_nf_sh_tt_05 2.711 0.028 95.577 0.000 2.711 2.558
## .t2_nf_sh_tt_06 2.428 0.029 83.016 0.000 2.428 2.222
## .t2_nf_sh_tt_07 3.119 0.029 106.837 0.000 3.119 2.861
## .t2_nf_sh_tt_08 2.332 0.029 81.536 0.000 2.332 2.183
## .t2_nf_sh_tt_10 2.271 0.028 80.899 0.000 2.271 2.169
## .t2_nf_sh_tt_11 2.363 0.028 83.753 0.000 2.363 2.245
## .t3_nf_sh_tt_01 1.777 0.030 58.962 0.000 1.777 1.575
## .t3_nf_sh_tt_02 1.887 0.028 66.581 0.000 1.887 1.778
## .t3_nf_sh_tt_03 2.951 0.029 103.374 0.000 2.951 2.760
## .t3_nf_sh_tt_04 3.057 0.028 108.245 0.000 3.057 2.890
## .t3_nf_sh_tt_05 2.737 0.028 97.145 0.000 2.737 2.594
## .t3_nf_sh_tt_06 2.473 0.029 86.630 0.000 2.473 2.313
## .t3_nf_sh_tt_07 3.103 0.028 111.586 0.000 3.103 2.981
## .t3_nf_sh_tt_08 2.367 0.028 85.840 0.000 2.367 2.293
## .t3_nf_sh_tt_10 2.297 0.027 83.630 0.000 2.297 2.234
## .t3_nf_sh_tt_11 2.366 0.027 86.179 0.000 2.366 2.301
## t1_inf_sh_tt_f 0.000 0.000 0.000
## t2_inf_sh_tt_f 0.000 0.000 0.000
## t3_inf_sh_tt_f 0.000 0.000 0.000
## .t1_nf_sh_tt_f1 0.000 0.000 0.000
## .t1_nf_sh_tt_f2 0.000 0.000 0.000
## .t1_nf_sh_tt_f3 0.000 0.000 0.000
## .t1_nf_sh_tt_f4 0.000 0.000 0.000
## .t1_nf_sh_tt_f5 0.000 0.000 0.000
## .t2_nf_sh_tt_f1 0.000 0.000 0.000
## .t2_nf_sh_tt_f2 0.000 0.000 0.000
## .t2_nf_sh_tt_f3 0.000 0.000 0.000
## .t2_nf_sh_tt_f4 0.000 0.000 0.000
## .t2_nf_sh_tt_f5 0.000 0.000 0.000
## .t3_nf_sh_tt_f1 0.000 0.000 0.000
## .t3_nf_sh_tt_f2 0.000 0.000 0.000
## .t3_nf_sh_tt_f3 0.000 0.000 0.000
## .t3_nf_sh_tt_f4 0.000 0.000 0.000
## .t3_nf_sh_tt_f5 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_tt_01 0.641 0.053 11.993 0.000 0.641 0.513
## .t1_nf_sh_tt_02 0.740 0.047 15.886 0.000 0.740 0.611
## .t1_nf_sh_tt_03 0.183 0.013 14.444 0.000 0.183 0.151
## .t1_nf_sh_tt_04 0.223 0.013 17.744 0.000 0.223 0.198
## .t1_nf_sh_tt_05 0.125 0.011 11.153 0.000 0.125 0.109
## .t1_nf_sh_tt_06 0.269 0.014 19.433 0.000 0.269 0.228
## .t1_nf_sh_tt_07 0.532 0.029 18.583 0.000 0.532 0.443
## .t1_nf_sh_tt_08 0.591 0.028 21.016 0.000 0.591 0.521
## .t1_nf_sh_tt_10 0.145 0.022 6.677 0.000 0.145 0.127
## .t1_nf_sh_tt_11 0.176 0.021 8.457 0.000 0.176 0.157
## .t2_nf_sh_tt_01 0.742 0.053 14.027 0.000 0.742 0.574
## .t2_nf_sh_tt_02 0.753 0.045 16.555 0.000 0.753 0.638
## .t2_nf_sh_tt_03 0.185 0.012 14.846 0.000 0.185 0.155
## .t2_nf_sh_tt_04 0.245 0.013 18.747 0.000 0.245 0.216
## .t2_nf_sh_tt_05 0.121 0.011 11.118 0.000 0.121 0.108
## .t2_nf_sh_tt_06 0.299 0.015 20.526 0.000 0.299 0.251
## .t2_nf_sh_tt_07 0.562 0.029 19.212 0.000 0.562 0.473
## .t2_nf_sh_tt_08 0.632 0.029 21.753 0.000 0.632 0.554
## .t2_nf_sh_tt_10 0.109 0.021 5.281 0.000 0.109 0.099
## .t2_nf_sh_tt_11 0.168 0.020 8.300 0.000 0.168 0.152
## .t3_nf_sh_tt_01 0.728 0.052 13.883 0.000 0.728 0.571
## .t3_nf_sh_tt_02 0.703 0.044 15.940 0.000 0.703 0.624
## .t3_nf_sh_tt_03 0.149 0.012 12.426 0.000 0.149 0.130
## .t3_nf_sh_tt_04 0.238 0.013 18.434 0.000 0.238 0.213
## .t3_nf_sh_tt_05 0.139 0.012 11.682 0.000 0.139 0.125
## .t3_nf_sh_tt_06 0.273 0.014 19.345 0.000 0.273 0.239
## .t3_nf_sh_tt_07 0.481 0.026 18.238 0.000 0.481 0.444
## .t3_nf_sh_tt_08 0.577 0.027 21.748 0.000 0.577 0.541
## .t3_nf_sh_tt_10 0.119 0.021 5.768 0.000 0.119 0.113
## .t3_nf_sh_tt_11 0.165 0.020 8.276 0.000 0.165 0.156
## t1_inf_sh_tt_f 0.106 0.013 7.964 0.000 1.000 1.000
## t2_inf_sh_tt_f 0.106 0.013 7.966 0.000 1.000 1.000
## t3_inf_sh_tt_f 0.099 0.012 7.950 0.000 1.000 1.000
## .t1_nf_sh_tt_f1 0.502 0.050 10.036 0.000 0.826 0.826
## .t1_nf_sh_tt_f2 0.100 0.014 7.293 0.000 0.098 0.098
## .t1_nf_sh_tt_f3 0.131 0.014 9.214 0.000 0.128 0.128
## .t1_nf_sh_tt_f4 0.158 0.020 7.918 0.000 0.235 0.235
## .t1_nf_sh_tt_f5 0.761 0.037 20.692 0.000 0.766 0.766
## .t2_nf_sh_tt_f1 0.445 0.046 9.577 0.000 0.807 0.807
## .t2_nf_sh_tt_f2 0.080 0.013 6.275 0.000 0.079 0.079
## .t2_nf_sh_tt_f3 0.106 0.013 8.100 0.000 0.106 0.106
## .t2_nf_sh_tt_f4 0.111 0.019 5.994 0.000 0.177 0.177
## .t2_nf_sh_tt_f5 0.753 0.036 20.917 0.000 0.763 0.763
## .t3_nf_sh_tt_f1 0.447 0.046 9.745 0.000 0.819 0.819
## .t3_nf_sh_tt_f2 0.133 0.014 9.181 0.000 0.134 0.134
## .t3_nf_sh_tt_f3 0.143 0.015 9.645 0.000 0.147 0.147
## .t3_nf_sh_tt_f4 0.124 0.018 6.981 0.000 0.206 0.206
## .t3_nf_sh_tt_f5 0.720 0.035 20.713 0.000 0.768 0.7681.2.3 Reliability
reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t1", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.817 0.877 0.924reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t2", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.824 0.888 0.920reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t3", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.812 0.875 0.9201.2.4 Longitudinal Invariance
(anova(get(paste("fit", name, no - 1, sep = "_")), get(paste("fit", name, no, sep = "_"))))1.3 Online Sharing of Personal Information
1.3.1 EFA
no <- 0
name <- "inf_sha_beh"
d_tmp <- select(d_wide, contains(paste0("t1_", name)), -contains("_m"))
model <- fa.parallel(d_tmp, fa = "fa", fm = "ml")
## Parallel analysis suggests that the number of factors = 4 and the number of components = NAfactan <- fa(d_tmp, fm = "ml", nfactors = model$nfact, rotate = "promax")
print(factan, sort = TRUE, cut = 0.3)## Factor Analysis using method = ml
## Call: fa(r = d_tmp, nfactors = model$nfact, rotate = "promax", fm = "ml")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item ML1 ML2 ML4 ML3 h2 u2 com
## t1_inf_sha_beh_03 4 1.03 0.94 0.0591 1.0
## t1_inf_sha_beh_04 5 1.02 0.94 0.0555 1.0
## t1_inf_sha_beh_05 6 0.89 0.43 1.00 0.0049 1.5
## t1_inf_sha_beh_fs 1 0.83 1.00 0.0039 1.2
## t1_inf_sha_beh_07 8 0.82 0.72 0.2835 1.0
## t1_inf_sha_beh_06 7 0.81 0.33 0.82 0.1771 1.3
## t1_inf_sha_beh_08 9 0.52 0.48 0.5224 1.4
## t1_inf_sha_beh_10 11 1.07 1.00 0.0050 1.0
## t1_inf_sha_beh_11 12 0.79 0.65 0.3544 1.0
## t1_inf_sha_beh_09 10 0.42 0.22 0.7824 1.0
## t1_inf_sha_beh_01 2 0.81 0.63 0.3750 1.0
## t1_inf_sha_beh_02 3 0.49 0.24 0.7597 1.1
##
## ML1 ML2 ML4 ML3
## SS loadings 5.31 1.98 0.89 0.44
## Proportion Var 0.44 0.17 0.07 0.04
## Cumulative Var 0.44 0.61 0.68 0.72
## Proportion Explained 0.62 0.23 0.10 0.05
## Cumulative Proportion 0.62 0.85 0.95 1.00
##
## With factor correlations of
## ML1 ML2 ML4 ML3
## ML1 1.00 0.56 0.47 0.18
## ML2 0.56 1.00 0.41 0.12
## ML4 0.47 0.41 1.00 0.27
## ML3 0.18 0.12 0.27 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 4 factors are sufficient.
##
## The degrees of freedom for the null model are 66 and the objective function was 15.1 with Chi Square of 21047
## The degrees of freedom for the model are 24 and the objective function was 1.85
##
## The root mean square of the residuals (RMSR) is 0.03
## The df corrected root mean square of the residuals is 0.05
##
## The harmonic number of observations is 1398 with the empirical chi square 198 with prob < 2.9e-29
## The total number of observations was 1403 with Likelihood Chi Square = 2575 with prob < 0
##
## Tucker Lewis Index of factoring reliability = 0.665
## RMSEA index = 0.275 and the 90 % confidence intervals are 0.266 0.284
## BIC = 2401
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## ML1 ML2 ML4 ML3
## Correlation of (regression) scores with factors 1.00 1.00 0.89 0.95
## Multiple R square of scores with factors 0.99 0.99 0.79 0.91
## Minimum correlation of possible factor scores 0.98 0.99 0.58 0.821.3.2 CFA
1.3.2.1 First-Order Model Unconstrained
First-order model shows poor fit. Needs to be adapted (see second order model).
model <- '
# create factors
t1_inf_sha_beh_f =~ 1*t1_inf_sha_beh_01 + t1_inf_sha_beh_02 + t1_inf_sha_beh_03 + t1_inf_sha_beh_04 + t1_inf_sha_beh_05 + t1_inf_sha_beh_06 + t1_inf_sha_beh_07 + t1_inf_sha_beh_08 + t1_inf_sha_beh_09 + t1_inf_sha_beh_10 + t1_inf_sha_beh_11
t2_inf_sha_beh_f =~ 1*t2_inf_sha_beh_01 + t2_inf_sha_beh_02 + t2_inf_sha_beh_03 + t2_inf_sha_beh_04 + t2_inf_sha_beh_05 + t2_inf_sha_beh_06 + t2_inf_sha_beh_07 + t2_inf_sha_beh_08 + t2_inf_sha_beh_09 + t2_inf_sha_beh_10 + t2_inf_sha_beh_11
t3_inf_sha_beh_f =~ 1*t3_inf_sha_beh_01 + t3_inf_sha_beh_02 + t3_inf_sha_beh_03 + t3_inf_sha_beh_04 + t3_inf_sha_beh_05 + t3_inf_sha_beh_06 + t3_inf_sha_beh_07 + t3_inf_sha_beh_08 + t3_inf_sha_beh_09 + t3_inf_sha_beh_10 + t3_inf_sha_beh_11
# factor covariance
t1_inf_sha_beh_f ~~ t2_inf_sha_beh_f + t3_inf_sha_beh_f
t2_inf_sha_beh_f ~~ t3_inf_sha_beh_f
# item error covariance
t1_inf_sha_beh_01 ~~ t2_inf_sha_beh_01 + t3_inf_sha_beh_01
t2_inf_sha_beh_01 ~~ t3_inf_sha_beh_01
t1_inf_sha_beh_02 ~~ t2_inf_sha_beh_02 + t3_inf_sha_beh_02
t2_inf_sha_beh_02 ~~ t3_inf_sha_beh_02
t1_inf_sha_beh_03 ~~ t2_inf_sha_beh_03 + t3_inf_sha_beh_03
t2_inf_sha_beh_03 ~~ t3_inf_sha_beh_03
t1_inf_sha_beh_04 ~~ t2_inf_sha_beh_04 + t3_inf_sha_beh_04
t2_inf_sha_beh_04 ~~ t3_inf_sha_beh_04
t1_inf_sha_beh_05 ~~ t2_inf_sha_beh_05 + t3_inf_sha_beh_05
t2_inf_sha_beh_05 ~~ t3_inf_sha_beh_05
t1_inf_sha_beh_06 ~~ t2_inf_sha_beh_06 + t3_inf_sha_beh_06
t2_inf_sha_beh_06 ~~ t3_inf_sha_beh_06
t1_inf_sha_beh_07 ~~ t2_inf_sha_beh_07 + t3_inf_sha_beh_07
t2_inf_sha_beh_07 ~~ t3_inf_sha_beh_07
t1_inf_sha_beh_08 ~~ t2_inf_sha_beh_08 + t3_inf_sha_beh_08
t2_inf_sha_beh_08 ~~ t3_inf_sha_beh_08
t1_inf_sha_beh_09 ~~ t2_inf_sha_beh_09 + t3_inf_sha_beh_09
t2_inf_sha_beh_09 ~~ t3_inf_sha_beh_09
t1_inf_sha_beh_10 ~~ t2_inf_sha_beh_10 + t3_inf_sha_beh_10
t2_inf_sha_beh_10 ~~ t3_inf_sha_beh_10
t1_inf_sha_beh_11 ~~ t2_inf_sha_beh_11 + t3_inf_sha_beh_11
t2_inf_sha_beh_11 ~~ t3_inf_sha_beh_11
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 194 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 135
##
## Number of observations 1403
## Number of missing patterns 40
##
## Model Test User Model:
##
## Test statistic 8471.050
## Degrees of freedom 459
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 41941.362
## Degrees of freedom 528
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.807
## Tucker-Lewis Index (TLI) 0.777
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -43502.943
## Loglikelihood unrestricted model (H1) -39267.418
##
## Akaike (AIC) 87275.886
## Bayesian (BIC) 87984.145
## Sample-size adjusted Bayesian (BIC) 87555.300
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.112
## 90 Percent confidence interval - lower 0.109
## 90 Percent confidence interval - upper 0.114
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.092
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f =~
## t1_nf_sh_bh_01 1.000 0.316 0.291
## t1_nf_sh_bh_02 0.353 0.056 6.286 0.000 0.111 0.189
## t1_nf_sh_bh_03 3.219 0.267 12.046 0.000 1.016 0.953
## t1_nf_sh_bh_04 3.198 0.266 12.042 0.000 1.010 0.951
## t1_nf_sh_bh_05 2.843 0.237 12.007 0.000 0.898 0.910
## t1_nf_sh_bh_06 2.633 0.221 11.933 0.000 0.832 0.850
## t1_nf_sh_bh_07 2.683 0.227 11.829 0.000 0.847 0.811
## t1_nf_sh_bh_08 1.902 0.167 11.364 0.000 0.601 0.634
## t1_nf_sh_bh_09 0.560 0.068 8.189 0.000 0.177 0.252
## t1_nf_sh_bh_10 1.228 0.119 10.312 0.000 0.388 0.442
## t1_nf_sh_bh_11 1.092 0.108 10.123 0.000 0.345 0.409
## t2_inf_sha_beh_f =~
## t2_nf_sh_bh_01 1.000 0.319 0.299
## t2_nf_sh_bh_02 0.269 0.044 6.058 0.000 0.086 0.177
## t2_nf_sh_bh_03 3.078 0.245 12.537 0.000 0.982 0.947
## t2_nf_sh_bh_04 3.103 0.248 12.521 0.000 0.991 0.938
## t2_nf_sh_bh_05 2.684 0.216 12.438 0.000 0.857 0.887
## t2_nf_sh_bh_06 2.488 0.201 12.358 0.000 0.794 0.829
## t2_nf_sh_bh_07 2.590 0.211 12.256 0.000 0.827 0.798
## t2_nf_sh_bh_08 1.907 0.162 11.790 0.000 0.609 0.636
## t2_nf_sh_bh_09 0.557 0.066 8.499 0.000 0.178 0.256
## t2_nf_sh_bh_10 1.285 0.118 10.897 0.000 0.410 0.478
## t2_nf_sh_bh_11 1.041 0.101 10.346 0.000 0.332 0.406
## t3_inf_sha_beh_f =~
## t3_nf_sh_bh_01 1.000 0.301 0.282
## t3_nf_sh_bh_02 0.320 0.051 6.264 0.000 0.096 0.188
## t3_nf_sh_bh_03 3.136 0.266 11.796 0.000 0.943 0.953
## t3_nf_sh_bh_04 3.161 0.268 11.776 0.000 0.951 0.938
## t3_nf_sh_bh_05 2.820 0.240 11.732 0.000 0.848 0.906
## t3_nf_sh_bh_06 2.551 0.219 11.643 0.000 0.767 0.836
## t3_nf_sh_bh_07 2.613 0.227 11.487 0.000 0.786 0.770
## t3_nf_sh_bh_08 1.890 0.170 11.090 0.000 0.569 0.622
## t3_nf_sh_bh_09 0.543 0.069 7.850 0.000 0.163 0.232
## t3_nf_sh_bh_10 1.217 0.121 10.064 0.000 0.366 0.429
## t3_nf_sh_bh_11 0.931 0.099 9.410 0.000 0.280 0.358
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f ~~
## t2_inf_sh_bh_f 0.061 0.008 7.330 0.000 0.606 0.606
## t3_inf_sh_bh_f 0.057 0.008 7.168 0.000 0.595 0.595
## t2_inf_sha_beh_f ~~
## t3_inf_sh_bh_f 0.058 0.008 7.171 0.000 0.609 0.609
## .t1_inf_sha_beh_01 ~~
## .t2_nf_sh_bh_01 0.415 0.031 13.580 0.000 0.415 0.393
## .t3_nf_sh_bh_01 0.396 0.030 13.017 0.000 0.396 0.373
## .t2_inf_sha_beh_01 ~~
## .t3_nf_sh_bh_01 0.455 0.031 14.844 0.000 0.455 0.436
## .t1_inf_sha_beh_02 ~~
## .t2_nf_sh_bh_02 0.069 0.008 9.056 0.000 0.069 0.250
## .t3_nf_sh_bh_02 0.069 0.008 8.593 0.000 0.069 0.237
## .t2_inf_sha_beh_02 ~~
## .t3_nf_sh_bh_02 0.069 0.007 10.315 0.000 0.069 0.287
## .t1_inf_sha_beh_03 ~~
## .t2_nf_sh_bh_03 0.030 0.005 6.400 0.000 0.030 0.279
## .t3_nf_sh_bh_03 0.029 0.004 6.769 0.000 0.029 0.305
## .t2_inf_sha_beh_03 ~~
## .t3_nf_sh_bh_03 0.044 0.005 9.416 0.000 0.044 0.440
## .t1_inf_sha_beh_04 ~~
## .t2_nf_sh_bh_04 0.043 0.005 8.559 0.000 0.043 0.361
## .t3_nf_sh_bh_04 0.034 0.005 7.150 0.000 0.034 0.298
## .t2_inf_sha_beh_04 ~~
## .t3_nf_sh_bh_04 0.062 0.005 11.292 0.000 0.062 0.478
## .t1_inf_sha_beh_05 ~~
## .t2_nf_sh_bh_05 0.043 0.006 6.814 0.000 0.043 0.235
## .t3_nf_sh_bh_05 0.046 0.006 8.030 0.000 0.046 0.287
## .t2_inf_sha_beh_05 ~~
## .t3_nf_sh_bh_05 0.038 0.006 6.087 0.000 0.038 0.215
## .t1_inf_sha_beh_06 ~~
## .t2_nf_sh_bh_06 0.114 0.009 12.443 0.000 0.114 0.412
## .t3_nf_sh_bh_06 0.104 0.009 12.156 0.000 0.104 0.401
## .t2_inf_sha_beh_06 ~~
## .t3_nf_sh_bh_06 0.104 0.009 11.697 0.000 0.104 0.387
## .t1_inf_sha_beh_07 ~~
## .t2_nf_sh_bh_07 0.137 0.012 11.642 0.000 0.137 0.359
## .t3_nf_sh_bh_07 0.110 0.012 9.292 0.000 0.110 0.277
## .t2_inf_sha_beh_07 ~~
## .t3_nf_sh_bh_07 0.105 0.012 8.542 0.000 0.105 0.259
## .t1_inf_sha_beh_08 ~~
## .t2_nf_sh_bh_08 0.210 0.016 13.060 0.000 0.210 0.388
## .t3_nf_sh_bh_08 0.175 0.015 11.442 0.000 0.175 0.334
## .t2_inf_sha_beh_08 ~~
## .t3_nf_sh_bh_08 0.200 0.016 12.776 0.000 0.200 0.379
## .t1_inf_sha_beh_09 ~~
## .t2_nf_sh_bh_09 0.232 0.014 16.841 0.000 0.232 0.507
## .t3_nf_sh_bh_09 0.238 0.014 16.895 0.000 0.238 0.512
## .t2_inf_sha_beh_09 ~~
## .t3_nf_sh_bh_09 0.258 0.014 18.225 0.000 0.258 0.562
## .t1_inf_sha_beh_10 ~~
## .t2_nf_sh_bh_10 0.232 0.017 13.425 0.000 0.232 0.392
## .t3_nf_sh_bh_10 0.236 0.018 13.329 0.000 0.236 0.390
## .t2_inf_sha_beh_10 ~~
## .t3_nf_sh_bh_10 0.240 0.017 14.007 0.000 0.240 0.412
## .t1_inf_sha_beh_11 ~~
## .t2_nf_sh_bh_11 0.266 0.017 15.515 0.000 0.266 0.462
## .t3_nf_sh_bh_11 0.235 0.016 14.234 0.000 0.235 0.418
## .t2_inf_sha_beh_11 ~~
## .t3_nf_sh_bh_11 0.221 0.016 13.844 0.000 0.221 0.404
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 1.713 0.029 59.112 0.000 1.713 1.579
## .t1_nf_sh_bh_02 1.244 0.016 78.926 0.000 1.244 2.109
## .t1_nf_sh_bh_03 2.671 0.028 93.816 0.000 2.671 2.505
## .t1_nf_sh_bh_04 2.725 0.028 96.157 0.000 2.725 2.567
## .t1_nf_sh_bh_05 2.546 0.026 96.663 0.000 2.546 2.581
## .t1_nf_sh_bh_06 2.431 0.026 93.023 0.000 2.431 2.484
## .t1_nf_sh_bh_07 2.878 0.028 103.197 0.000 2.878 2.755
## .t1_nf_sh_bh_08 2.194 0.025 86.676 0.000 2.194 2.317
## .t1_nf_sh_bh_09 1.408 0.019 75.047 0.000 1.408 2.004
## .t1_nf_sh_bh_10 1.793 0.023 76.561 0.000 1.793 2.046
## .t1_nf_sh_bh_11 1.738 0.023 77.086 0.000 1.738 2.060
## .t2_nf_sh_bh_01 1.712 0.029 59.960 0.000 1.712 1.604
## .t2_nf_sh_bh_02 1.214 0.013 93.688 0.000 1.214 2.503
## .t2_nf_sh_bh_03 2.682 0.028 96.818 0.000 2.682 2.586
## .t2_nf_sh_bh_04 2.765 0.028 98.003 0.000 2.765 2.618
## .t2_nf_sh_bh_05 2.558 0.026 99.193 0.000 2.558 2.650
## .t2_nf_sh_bh_06 2.434 0.026 95.109 0.000 2.434 2.541
## .t2_nf_sh_bh_07 2.923 0.028 105.656 0.000 2.923 2.822
## .t2_nf_sh_bh_08 2.239 0.026 87.551 0.000 2.239 2.339
## .t2_nf_sh_bh_09 1.415 0.019 76.180 0.000 1.415 2.036
## .t2_nf_sh_bh_10 1.806 0.023 78.643 0.000 1.806 2.102
## .t2_nf_sh_bh_11 1.734 0.022 79.224 0.000 1.734 2.117
## .t3_nf_sh_bh_01 1.702 0.028 59.727 0.000 1.702 1.595
## .t3_nf_sh_bh_02 1.227 0.014 89.831 0.000 1.227 2.400
## .t3_nf_sh_bh_03 2.627 0.026 99.428 0.000 2.627 2.654
## .t3_nf_sh_bh_04 2.692 0.027 99.520 0.000 2.692 2.657
## .t3_nf_sh_bh_05 2.510 0.025 100.439 0.000 2.510 2.682
## .t3_nf_sh_bh_06 2.395 0.025 97.705 0.000 2.395 2.609
## .t3_nf_sh_bh_07 2.864 0.027 105.061 0.000 2.864 2.806
## .t3_nf_sh_bh_08 2.177 0.024 89.089 0.000 2.177 2.382
## .t3_nf_sh_bh_09 1.418 0.019 75.548 0.000 1.418 2.018
## .t3_nf_sh_bh_10 1.777 0.023 77.948 0.000 1.777 2.082
## .t3_nf_sh_bh_11 1.713 0.021 82.030 0.000 1.713 2.192
## t1_inf_sh_bh_f 0.000 0.000 0.000
## t2_inf_sh_bh_f 0.000 0.000 0.000
## t3_inf_sh_bh_f 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 1.076 0.041 26.354 0.000 1.076 0.915
## .t1_nf_sh_bh_02 0.336 0.013 26.424 0.000 0.336 0.964
## .t1_nf_sh_bh_03 0.104 0.006 16.331 0.000 0.104 0.091
## .t1_nf_sh_bh_04 0.107 0.006 16.489 0.000 0.107 0.095
## .t1_nf_sh_bh_05 0.166 0.008 20.107 0.000 0.166 0.171
## .t1_nf_sh_bh_06 0.266 0.012 22.561 0.000 0.266 0.278
## .t1_nf_sh_bh_07 0.373 0.015 24.535 0.000 0.373 0.342
## .t1_nf_sh_bh_08 0.536 0.021 25.573 0.000 0.536 0.598
## .t1_nf_sh_bh_09 0.462 0.018 26.371 0.000 0.462 0.937
## .t1_nf_sh_bh_10 0.618 0.024 26.095 0.000 0.618 0.804
## .t1_nf_sh_bh_11 0.592 0.023 26.147 0.000 0.592 0.833
## .t2_nf_sh_bh_01 1.038 0.040 26.268 0.000 1.038 0.911
## .t2_nf_sh_bh_02 0.228 0.009 26.435 0.000 0.228 0.969
## .t2_nf_sh_bh_03 0.110 0.007 16.487 0.000 0.110 0.103
## .t2_nf_sh_bh_04 0.134 0.007 17.962 0.000 0.134 0.120
## .t2_nf_sh_bh_05 0.198 0.009 21.058 0.000 0.198 0.213
## .t2_nf_sh_bh_06 0.286 0.013 22.827 0.000 0.286 0.312
## .t2_nf_sh_bh_07 0.389 0.016 24.287 0.000 0.389 0.363
## .t2_nf_sh_bh_08 0.546 0.021 25.491 0.000 0.546 0.596
## .t2_nf_sh_bh_09 0.452 0.017 26.275 0.000 0.452 0.935
## .t2_nf_sh_bh_10 0.570 0.022 26.023 0.000 0.570 0.772
## .t2_nf_sh_bh_11 0.561 0.021 26.183 0.000 0.561 0.836
## .t3_nf_sh_bh_01 1.048 0.040 26.367 0.000 1.048 0.921
## .t3_nf_sh_bh_02 0.252 0.010 26.425 0.000 0.252 0.964
## .t3_nf_sh_bh_03 0.089 0.006 15.523 0.000 0.089 0.091
## .t3_nf_sh_bh_04 0.123 0.007 17.878 0.000 0.123 0.120
## .t3_nf_sh_bh_05 0.156 0.008 20.002 0.000 0.156 0.179
## .t3_nf_sh_bh_06 0.254 0.011 22.708 0.000 0.254 0.301
## .t3_nf_sh_bh_07 0.425 0.017 24.845 0.000 0.425 0.407
## .t3_nf_sh_bh_08 0.512 0.020 25.550 0.000 0.512 0.613
## .t3_nf_sh_bh_09 0.467 0.018 26.339 0.000 0.467 0.946
## .t3_nf_sh_bh_10 0.594 0.023 26.140 0.000 0.594 0.816
## .t3_nf_sh_bh_11 0.533 0.020 26.248 0.000 0.533 0.872
## t1_inf_sh_bh_f 0.100 0.017 5.906 0.000 1.000 1.000
## t2_inf_sh_bh_f 0.102 0.017 6.136 0.000 1.000 1.000
## t3_inf_sh_bh_f 0.090 0.016 5.784 0.000 1.000 1.0001.3.2.2 First-Order Model Constrained
model <- '
# create factors
t1_inf_sha_beh_f =~ 1*t1_inf_sha_beh_01 + c2*t1_inf_sha_beh_02 + c3*t1_inf_sha_beh_03 + c4*t1_inf_sha_beh_04 + c5*t1_inf_sha_beh_05 + c6*t1_inf_sha_beh_06 + c7*t1_inf_sha_beh_07 + c8*t1_inf_sha_beh_08 + c9*t1_inf_sha_beh_09 + c10*t1_inf_sha_beh_10 + c11*t1_inf_sha_beh_11
t2_inf_sha_beh_f =~ 1*t2_inf_sha_beh_01 + c2*t2_inf_sha_beh_02 + c3*t2_inf_sha_beh_03 + c4*t2_inf_sha_beh_04 + c5*t2_inf_sha_beh_05 + c6*t2_inf_sha_beh_06 + c7*t2_inf_sha_beh_07 + c8*t2_inf_sha_beh_08 + c9*t2_inf_sha_beh_09 + c10*t2_inf_sha_beh_10 + c11*t2_inf_sha_beh_11
t3_inf_sha_beh_f =~ 1*t3_inf_sha_beh_01 + c2*t3_inf_sha_beh_02 + c3*t3_inf_sha_beh_03 + c4*t3_inf_sha_beh_04 + c5*t3_inf_sha_beh_05 + c6*t3_inf_sha_beh_06 + c7*t3_inf_sha_beh_07 + c8*t3_inf_sha_beh_08 + c9*t3_inf_sha_beh_09 + c10*t3_inf_sha_beh_10 + c11*t3_inf_sha_beh_11
# factor covariance
t1_inf_sha_beh_f ~~ t2_inf_sha_beh_f + t3_inf_sha_beh_f
t2_inf_sha_beh_f ~~ t3_inf_sha_beh_f
# item error covariance
t1_inf_sha_beh_01 ~~ t2_inf_sha_beh_01 + t3_inf_sha_beh_01
t2_inf_sha_beh_01 ~~ t3_inf_sha_beh_01
t1_inf_sha_beh_02 ~~ t2_inf_sha_beh_02 + t3_inf_sha_beh_02
t2_inf_sha_beh_02 ~~ t3_inf_sha_beh_02
t1_inf_sha_beh_03 ~~ t2_inf_sha_beh_03 + t3_inf_sha_beh_03
t2_inf_sha_beh_03 ~~ t3_inf_sha_beh_03
t1_inf_sha_beh_04 ~~ t2_inf_sha_beh_04 + t3_inf_sha_beh_04
t2_inf_sha_beh_04 ~~ t3_inf_sha_beh_04
t1_inf_sha_beh_05 ~~ t2_inf_sha_beh_05 + t3_inf_sha_beh_05
t2_inf_sha_beh_05 ~~ t3_inf_sha_beh_05
t1_inf_sha_beh_06 ~~ t2_inf_sha_beh_06 + t3_inf_sha_beh_06
t2_inf_sha_beh_06 ~~ t3_inf_sha_beh_06
t1_inf_sha_beh_07 ~~ t2_inf_sha_beh_07 + t3_inf_sha_beh_07
t2_inf_sha_beh_07 ~~ t3_inf_sha_beh_07
t1_inf_sha_beh_08 ~~ t2_inf_sha_beh_08 + t3_inf_sha_beh_08
t2_inf_sha_beh_08 ~~ t3_inf_sha_beh_08
t1_inf_sha_beh_09 ~~ t2_inf_sha_beh_09 + t3_inf_sha_beh_09
t2_inf_sha_beh_09 ~~ t3_inf_sha_beh_09
t1_inf_sha_beh_10 ~~ t2_inf_sha_beh_10 + t3_inf_sha_beh_10
t2_inf_sha_beh_10 ~~ t3_inf_sha_beh_10
t1_inf_sha_beh_11 ~~ t2_inf_sha_beh_11 + t3_inf_sha_beh_11
t2_inf_sha_beh_11 ~~ t3_inf_sha_beh_11
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 148 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 135
## Number of equality constraints 20
##
## Number of observations 1403
## Number of missing patterns 40
##
## Model Test User Model:
##
## Test statistic 8485.780
## Degrees of freedom 479
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 41941.362
## Degrees of freedom 528
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.807
## Tucker-Lewis Index (TLI) 0.787
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -43510.308
## Loglikelihood unrestricted model (H1) -39267.418
##
## Akaike (AIC) 87250.615
## Bayesian (BIC) 87853.948
## Sample-size adjusted Bayesian (BIC) 87488.635
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.109
## 90 Percent confidence interval - lower 0.107
## 90 Percent confidence interval - upper 0.111
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.092
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f =~
## t1____01 1.000 0.322 0.297
## t1____02 (c2) 0.309 0.033 9.310 0.000 0.099 0.169
## t1____03 (c3) 3.144 0.179 17.589 0.000 1.013 0.953
## t1____04 (c4) 3.151 0.179 17.568 0.000 1.015 0.952
## t1____05 (c5) 2.784 0.159 17.523 0.000 0.897 0.910
## t1____06 (c6) 2.559 0.147 17.387 0.000 0.824 0.847
## t1____07 (c7) 2.629 0.153 17.236 0.000 0.847 0.811
## t1____08 (c8) 1.898 0.114 16.588 0.000 0.612 0.641
## t1____09 (c9) 0.553 0.048 11.623 0.000 0.178 0.254
## t1____10 (c10) 1.245 0.082 15.123 0.000 0.401 0.455
## t1____11 (c11) 1.022 0.071 14.406 0.000 0.329 0.393
## t2_inf_sha_beh_f =~
## t2____01 1.000 0.313 0.294
## t2____02 (c2) 0.309 0.033 9.310 0.000 0.097 0.198
## t2____03 (c3) 3.144 0.179 17.589 0.000 0.984 0.947
## t2____04 (c4) 3.151 0.179 17.568 0.000 0.986 0.937
## t2____05 (c5) 2.784 0.159 17.523 0.000 0.871 0.891
## t2____06 (c6) 2.559 0.147 17.387 0.000 0.801 0.832
## t2____07 (c7) 2.629 0.153 17.236 0.000 0.823 0.796
## t2____08 (c8) 1.898 0.114 16.588 0.000 0.594 0.626
## t2____09 (c9) 0.553 0.048 11.623 0.000 0.173 0.249
## t2____10 (c10) 1.245 0.082 15.123 0.000 0.390 0.458
## t2____11 (c11) 1.022 0.071 14.406 0.000 0.320 0.392
## t3_inf_sha_beh_f =~
## t3____01 1.000 0.301 0.282
## t3____02 (c2) 0.309 0.033 9.310 0.000 0.093 0.182
## t3____03 (c3) 3.144 0.179 17.589 0.000 0.946 0.954
## t3____04 (c4) 3.151 0.179 17.568 0.000 0.948 0.938
## t3____05 (c5) 2.784 0.159 17.523 0.000 0.837 0.904
## t3____06 (c6) 2.559 0.147 17.387 0.000 0.770 0.836
## t3____07 (c7) 2.629 0.153 17.236 0.000 0.791 0.772
## t3____08 (c8) 1.898 0.114 16.588 0.000 0.571 0.624
## t3____09 (c9) 0.553 0.048 11.623 0.000 0.166 0.237
## t3____10 (c10) 1.245 0.082 15.123 0.000 0.375 0.437
## t3____11 (c11) 1.022 0.071 14.406 0.000 0.307 0.389
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f ~~
## t2_inf_sh_bh_f 0.061 0.008 8.007 0.000 0.606 0.606
## t3_inf_sh_bh_f 0.058 0.007 7.989 0.000 0.595 0.595
## t2_inf_sha_beh_f ~~
## t3_inf_sh_bh_f 0.057 0.007 8.006 0.000 0.609 0.609
## .t1_inf_sha_beh_01 ~~
## .t2_nf_sh_bh_01 0.415 0.031 13.585 0.000 0.415 0.393
## .t3_nf_sh_bh_01 0.396 0.030 13.015 0.000 0.396 0.373
## .t2_inf_sha_beh_01 ~~
## .t3_nf_sh_bh_01 0.456 0.031 14.867 0.000 0.456 0.437
## .t1_inf_sha_beh_02 ~~
## .t2_nf_sh_bh_02 0.069 0.008 9.060 0.000 0.069 0.250
## .t3_nf_sh_bh_02 0.069 0.008 8.575 0.000 0.069 0.236
## .t2_inf_sha_beh_02 ~~
## .t3_nf_sh_bh_02 0.069 0.007 10.295 0.000 0.069 0.287
## .t1_inf_sha_beh_03 ~~
## .t2_nf_sh_bh_03 0.030 0.005 6.382 0.000 0.030 0.278
## .t3_nf_sh_bh_03 0.029 0.004 6.769 0.000 0.029 0.304
## .t2_inf_sha_beh_03 ~~
## .t3_nf_sh_bh_03 0.044 0.005 9.390 0.000 0.044 0.441
## .t1_inf_sha_beh_04 ~~
## .t2_nf_sh_bh_04 0.044 0.005 8.605 0.000 0.044 0.363
## .t3_nf_sh_bh_04 0.034 0.005 7.186 0.000 0.034 0.299
## .t2_inf_sha_beh_04 ~~
## .t3_nf_sh_bh_04 0.062 0.005 11.317 0.000 0.062 0.477
## .t1_inf_sha_beh_05 ~~
## .t2_nf_sh_bh_05 0.042 0.006 6.760 0.000 0.042 0.234
## .t3_nf_sh_bh_05 0.047 0.006 8.113 0.000 0.047 0.288
## .t2_inf_sha_beh_05 ~~
## .t3_nf_sh_bh_05 0.037 0.006 6.016 0.000 0.037 0.212
## .t1_inf_sha_beh_06 ~~
## .t2_nf_sh_bh_06 0.114 0.009 12.446 0.000 0.114 0.413
## .t3_nf_sh_bh_06 0.104 0.009 12.179 0.000 0.104 0.401
## .t2_inf_sha_beh_06 ~~
## .t3_nf_sh_bh_06 0.104 0.009 11.675 0.000 0.104 0.386
## .t1_inf_sha_beh_07 ~~
## .t2_nf_sh_bh_07 0.137 0.012 11.699 0.000 0.137 0.360
## .t3_nf_sh_bh_07 0.110 0.012 9.303 0.000 0.110 0.277
## .t2_inf_sha_beh_07 ~~
## .t3_nf_sh_bh_07 0.106 0.012 8.622 0.000 0.106 0.260
## .t1_inf_sha_beh_08 ~~
## .t2_nf_sh_bh_08 0.210 0.016 13.062 0.000 0.210 0.387
## .t3_nf_sh_bh_08 0.174 0.015 11.418 0.000 0.174 0.333
## .t2_inf_sha_beh_08 ~~
## .t3_nf_sh_bh_08 0.201 0.016 12.815 0.000 0.201 0.380
## .t1_inf_sha_beh_09 ~~
## .t2_nf_sh_bh_09 0.232 0.014 16.859 0.000 0.232 0.508
## .t3_nf_sh_bh_09 0.238 0.014 16.904 0.000 0.238 0.512
## .t2_inf_sha_beh_09 ~~
## .t3_nf_sh_bh_09 0.258 0.014 18.254 0.000 0.258 0.562
## .t1_inf_sha_beh_10 ~~
## .t2_nf_sh_bh_10 0.232 0.017 13.427 0.000 0.232 0.391
## .t3_nf_sh_bh_10 0.234 0.018 13.302 0.000 0.234 0.388
## .t2_inf_sha_beh_10 ~~
## .t3_nf_sh_bh_10 0.241 0.017 14.051 0.000 0.241 0.413
## .t1_inf_sha_beh_11 ~~
## .t2_nf_sh_bh_11 0.268 0.017 15.563 0.000 0.268 0.463
## .t3_nf_sh_bh_11 0.235 0.016 14.255 0.000 0.235 0.418
## .t2_inf_sha_beh_11 ~~
## .t3_nf_sh_bh_11 0.220 0.016 13.813 0.000 0.220 0.403
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 1.713 0.029 59.015 0.000 1.713 1.577
## .t1_nf_sh_bh_02 1.244 0.016 79.196 0.000 1.244 2.116
## .t1_nf_sh_bh_03 2.671 0.028 94.126 0.000 2.671 2.513
## .t1_nf_sh_bh_04 2.725 0.028 95.736 0.000 2.725 2.556
## .t1_nf_sh_bh_05 2.546 0.026 96.720 0.000 2.546 2.583
## .t1_nf_sh_bh_06 2.431 0.026 93.573 0.000 2.431 2.499
## .t1_nf_sh_bh_07 2.878 0.028 103.235 0.000 2.878 2.756
## .t1_nf_sh_bh_08 2.194 0.025 86.068 0.000 2.194 2.301
## .t1_nf_sh_bh_09 1.408 0.019 75.010 0.000 1.408 2.003
## .t1_nf_sh_bh_10 1.793 0.024 76.090 0.000 1.793 2.034
## .t1_nf_sh_bh_11 1.738 0.022 77.564 0.000 1.738 2.073
## .t2_nf_sh_bh_01 1.712 0.029 60.055 0.000 1.712 1.606
## .t2_nf_sh_bh_02 1.214 0.013 93.290 0.000 1.214 2.492
## .t2_nf_sh_bh_03 2.682 0.028 96.694 0.000 2.682 2.583
## .t2_nf_sh_bh_04 2.765 0.028 98.365 0.000 2.765 2.627
## .t2_nf_sh_bh_05 2.558 0.026 98.002 0.000 2.558 2.618
## .t2_nf_sh_bh_06 2.434 0.026 94.691 0.000 2.434 2.530
## .t2_nf_sh_bh_07 2.923 0.028 105.941 0.000 2.923 2.830
## .t2_nf_sh_bh_08 2.239 0.025 88.343 0.000 2.239 2.360
## .t2_nf_sh_bh_09 1.415 0.019 76.256 0.000 1.415 2.038
## .t2_nf_sh_bh_10 1.806 0.023 79.384 0.000 1.806 2.122
## .t2_nf_sh_bh_11 1.734 0.022 79.611 0.000 1.734 2.127
## .t3_nf_sh_bh_01 1.702 0.028 59.728 0.000 1.702 1.595
## .t3_nf_sh_bh_02 1.226 0.014 89.943 0.000 1.226 2.403
## .t3_nf_sh_bh_03 2.627 0.026 99.211 0.000 2.627 2.649
## .t3_nf_sh_bh_04 2.692 0.027 99.785 0.000 2.692 2.664
## .t3_nf_sh_bh_05 2.510 0.025 101.426 0.000 2.510 2.708
## .t3_nf_sh_bh_06 2.395 0.025 97.478 0.000 2.395 2.603
## .t3_nf_sh_bh_07 2.864 0.027 104.702 0.000 2.864 2.796
## .t3_nf_sh_bh_08 2.177 0.024 88.954 0.000 2.177 2.379
## .t3_nf_sh_bh_09 1.418 0.019 75.487 0.000 1.418 2.017
## .t3_nf_sh_bh_10 1.777 0.023 77.681 0.000 1.777 2.075
## .t3_nf_sh_bh_11 1.713 0.021 81.057 0.000 1.713 2.166
## t1_inf_sh_bh_f 0.000 0.000 0.000
## t2_inf_sh_bh_f 0.000 0.000 0.000
## t3_inf_sh_bh_f 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 1.076 0.041 26.370 0.000 1.076 0.912
## .t1_nf_sh_bh_02 0.336 0.013 26.427 0.000 0.336 0.971
## .t1_nf_sh_bh_03 0.104 0.006 16.704 0.000 0.104 0.092
## .t1_nf_sh_bh_04 0.106 0.006 16.721 0.000 0.106 0.093
## .t1_nf_sh_bh_05 0.167 0.008 20.487 0.000 0.167 0.172
## .t1_nf_sh_bh_06 0.267 0.012 22.813 0.000 0.267 0.282
## .t1_nf_sh_bh_07 0.373 0.015 24.662 0.000 0.373 0.342
## .t1_nf_sh_bh_08 0.536 0.021 25.638 0.000 0.536 0.589
## .t1_nf_sh_bh_09 0.462 0.018 26.398 0.000 0.462 0.936
## .t1_nf_sh_bh_10 0.617 0.024 26.174 0.000 0.617 0.793
## .t1_nf_sh_bh_11 0.594 0.023 26.186 0.000 0.594 0.846
## .t2_nf_sh_bh_01 1.038 0.039 26.297 0.000 1.038 0.914
## .t2_nf_sh_bh_02 0.228 0.009 26.425 0.000 0.228 0.961
## .t2_nf_sh_bh_03 0.111 0.007 16.632 0.000 0.111 0.103
## .t2_nf_sh_bh_04 0.136 0.007 18.215 0.000 0.136 0.122
## .t2_nf_sh_bh_05 0.196 0.009 21.123 0.000 0.196 0.206
## .t2_nf_sh_bh_06 0.284 0.012 22.881 0.000 0.284 0.307
## .t2_nf_sh_bh_07 0.391 0.016 24.460 0.000 0.391 0.366
## .t2_nf_sh_bh_08 0.547 0.021 25.574 0.000 0.547 0.608
## .t2_nf_sh_bh_09 0.452 0.017 26.321 0.000 0.452 0.938
## .t2_nf_sh_bh_10 0.572 0.022 26.064 0.000 0.572 0.790
## .t2_nf_sh_bh_11 0.563 0.021 26.216 0.000 0.563 0.846
## .t3_nf_sh_bh_01 1.048 0.040 26.380 0.000 1.048 0.921
## .t3_nf_sh_bh_02 0.252 0.010 26.426 0.000 0.252 0.967
## .t3_nf_sh_bh_03 0.089 0.006 15.822 0.000 0.089 0.091
## .t3_nf_sh_bh_04 0.123 0.007 18.263 0.000 0.123 0.120
## .t3_nf_sh_bh_05 0.157 0.008 20.520 0.000 0.157 0.183
## .t3_nf_sh_bh_06 0.255 0.011 22.955 0.000 0.255 0.301
## .t3_nf_sh_bh_07 0.424 0.017 24.942 0.000 0.424 0.404
## .t3_nf_sh_bh_08 0.512 0.020 25.612 0.000 0.512 0.611
## .t3_nf_sh_bh_09 0.467 0.018 26.349 0.000 0.467 0.944
## .t3_nf_sh_bh_10 0.593 0.023 26.181 0.000 0.593 0.809
## .t3_nf_sh_bh_11 0.531 0.020 26.267 0.000 0.531 0.849
## t1_inf_sh_bh_f 0.104 0.012 8.373 0.000 1.000 1.000
## t2_inf_sh_bh_f 0.098 0.012 8.369 0.000 1.000 1.000
## t3_inf_sh_bh_f 0.090 0.011 8.370 0.000 1.000 1.0001.3.2.3 Second-Order Model Unconstrained
Second-order model shows much improved fit.
model <- '
# create factors
t1_inf_sha_beh_f =~ 1*t1_inf_sha_beh_f1 + t1_inf_sha_beh_f2 + t1_inf_sha_beh_f3 + t1_inf_sha_beh_f4 + t1_inf_sha_beh_f5
t2_inf_sha_beh_f =~ 1*t2_inf_sha_beh_f1 + t2_inf_sha_beh_f2 + t2_inf_sha_beh_f3 + t2_inf_sha_beh_f4 + t2_inf_sha_beh_f5
t3_inf_sha_beh_f =~ 1*t3_inf_sha_beh_f1 + t3_inf_sha_beh_f2 + t3_inf_sha_beh_f3 + t3_inf_sha_beh_f4 + t3_inf_sha_beh_f5
t1_inf_sha_beh_f1 =~ 1*t1_inf_sha_beh_01 + t1_inf_sha_beh_02
t1_inf_sha_beh_f2 =~ 1*t1_inf_sha_beh_03 + t1_inf_sha_beh_04
t1_inf_sha_beh_f3 =~ 1*t1_inf_sha_beh_05 + t1_inf_sha_beh_06
t1_inf_sha_beh_f4 =~ 1*t1_inf_sha_beh_07 + t1_inf_sha_beh_08
t1_inf_sha_beh_f5 =~ 1*t1_inf_sha_beh_10 + t1_inf_sha_beh_11
t2_inf_sha_beh_f1 =~ 1*t2_inf_sha_beh_01 + t2_inf_sha_beh_02
t2_inf_sha_beh_f2 =~ 1*t2_inf_sha_beh_03 + t2_inf_sha_beh_04
t2_inf_sha_beh_f3 =~ 1*t2_inf_sha_beh_05 + t2_inf_sha_beh_06
t2_inf_sha_beh_f4 =~ 1*t2_inf_sha_beh_07 + t2_inf_sha_beh_08
t2_inf_sha_beh_f5 =~ 1*t2_inf_sha_beh_10 + t2_inf_sha_beh_11
t3_inf_sha_beh_f1 =~ 1*t3_inf_sha_beh_01 + t3_inf_sha_beh_02
t3_inf_sha_beh_f2 =~ 1*t3_inf_sha_beh_03 + t3_inf_sha_beh_04
t3_inf_sha_beh_f3 =~ 1*t3_inf_sha_beh_05 + t3_inf_sha_beh_06
t3_inf_sha_beh_f4 =~ 1*t3_inf_sha_beh_07 + t3_inf_sha_beh_08
t3_inf_sha_beh_f5 =~ 1*t3_inf_sha_beh_10 + t3_inf_sha_beh_11
# factor covariance
t1_inf_sha_beh_f ~~ t2_inf_sha_beh_f + t3_inf_sha_beh_f
t2_inf_sha_beh_f ~~ t3_inf_sha_beh_f
# item error covariance
t1_inf_sha_beh_01 ~~ t2_inf_sha_beh_01 + t3_inf_sha_beh_01
t2_inf_sha_beh_01 ~~ t3_inf_sha_beh_01
t1_inf_sha_beh_02 ~~ t2_inf_sha_beh_02 + t3_inf_sha_beh_02
t2_inf_sha_beh_02 ~~ t3_inf_sha_beh_02
t1_inf_sha_beh_03 ~~ t2_inf_sha_beh_03 + t3_inf_sha_beh_03
t2_inf_sha_beh_03 ~~ t3_inf_sha_beh_03
t1_inf_sha_beh_04 ~~ t2_inf_sha_beh_04 + t3_inf_sha_beh_04
t2_inf_sha_beh_04 ~~ t3_inf_sha_beh_04
t1_inf_sha_beh_05 ~~ t2_inf_sha_beh_05 + t3_inf_sha_beh_05
t2_inf_sha_beh_05 ~~ t3_inf_sha_beh_05
t1_inf_sha_beh_06 ~~ t2_inf_sha_beh_06 + t3_inf_sha_beh_06
t2_inf_sha_beh_06 ~~ t3_inf_sha_beh_06
t1_inf_sha_beh_07 ~~ t2_inf_sha_beh_07 + t3_inf_sha_beh_07
t2_inf_sha_beh_07 ~~ t3_inf_sha_beh_07
t1_inf_sha_beh_08 ~~ t2_inf_sha_beh_08 + t3_inf_sha_beh_08
t2_inf_sha_beh_08 ~~ t3_inf_sha_beh_08
t1_inf_sha_beh_10 ~~ t2_inf_sha_beh_10 + t3_inf_sha_beh_10
t2_inf_sha_beh_10 ~~ t3_inf_sha_beh_10
t1_inf_sha_beh_11 ~~ t2_inf_sha_beh_11 + t3_inf_sha_beh_11
t2_inf_sha_beh_11 ~~ t3_inf_sha_beh_11
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 234 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 138
##
## Number of observations 1403
## Number of missing patterns 38
##
## Model Test User Model:
##
## Test statistic 2510.346
## Degrees of freedom 357
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 39663.809
## Degrees of freedom 435
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.945
## Tucker-Lewis Index (TLI) 0.933
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -37156.335
## Loglikelihood unrestricted model (H1) -35901.162
##
## Akaike (AIC) 74588.669
## Bayesian (BIC) 75312.668
## Sample-size adjusted Bayesian (BIC) 74874.293
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.066
## 90 Percent confidence interval - lower 0.063
## 90 Percent confidence interval - upper 0.068
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.062
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f =~
## t1_nf_sh_bh_f1 1.000 0.465 0.465
## t1_nf_sh_bh_f2 2.974 0.241 12.321 0.000 0.961 0.961
## t1_nf_sh_bh_f3 2.734 0.221 12.346 0.000 0.941 0.941
## t1_nf_sh_bh_f4 2.627 0.216 12.188 0.000 0.957 0.957
## t1_nf_sh_bh_f5 1.298 0.122 10.626 0.000 0.537 0.537
## t2_inf_sha_beh_f =~
## t2_nf_sh_bh_f1 1.000 0.539 0.539
## t2_nf_sh_bh_f2 2.845 0.222 12.832 0.000 0.964 0.964
## t2_nf_sh_bh_f3 2.564 0.200 12.788 0.000 0.920 0.920
## t2_nf_sh_bh_f4 2.539 0.201 12.662 0.000 0.947 0.947
## t2_nf_sh_bh_f5 1.311 0.118 11.131 0.000 0.543 0.543
## t3_inf_sha_beh_f =~
## t3_nf_sh_bh_f1 1.000 0.465 0.465
## t3_nf_sh_bh_f2 2.893 0.239 12.094 0.000 0.956 0.956
## t3_nf_sh_bh_f3 2.715 0.225 12.067 0.000 0.939 0.939
## t3_nf_sh_bh_f4 2.556 0.215 11.862 0.000 0.930 0.930
## t3_nf_sh_bh_f5 1.252 0.122 10.306 0.000 0.483 0.483
## t1_inf_sha_beh_f1 =~
## t1_nf_sh_bh_01 1.000 0.712 0.659
## t1_nf_sh_bh_02 0.346 0.047 7.302 0.000 0.246 0.421
## t1_inf_sha_beh_f2 =~
## t1_nf_sh_bh_03 1.000 1.025 0.965
## t1_nf_sh_bh_04 0.992 0.010 94.723 0.000 1.017 0.964
## t1_inf_sha_beh_f3 =~
## t1_nf_sh_bh_05 1.000 0.962 0.974
## t1_nf_sh_bh_06 0.920 0.013 70.754 0.000 0.884 0.907
## t1_inf_sha_beh_f4 =~
## t1_nf_sh_bh_07 1.000 0.909 0.860
## t1_nf_sh_bh_08 0.722 0.023 30.797 0.000 0.656 0.688
## t1_inf_sha_beh_f5 =~
## t1_nf_sh_bh_10 1.000 0.801 0.907
## t1_nf_sh_bh_11 0.888 0.034 25.947 0.000 0.711 0.848
## t2_inf_sha_beh_f1 =~
## t2_nf_sh_bh_01 1.000 0.621 0.584
## t2_nf_sh_bh_02 0.268 0.039 6.801 0.000 0.167 0.344
## t2_inf_sha_beh_f2 =~
## t2_nf_sh_bh_03 1.000 0.987 0.958
## t2_nf_sh_bh_04 1.006 0.012 84.635 0.000 0.992 0.949
## t2_inf_sha_beh_f3 =~
## t2_nf_sh_bh_05 1.000 0.932 0.965
## t2_nf_sh_bh_06 0.926 0.014 64.893 0.000 0.863 0.904
## t2_inf_sha_beh_f4 =~
## t2_nf_sh_bh_07 1.000 0.896 0.857
## t2_nf_sh_bh_08 0.749 0.024 30.868 0.000 0.671 0.692
## t2_inf_sha_beh_f5 =~
## t2_nf_sh_bh_10 1.000 0.807 0.942
## t2_nf_sh_bh_11 0.818 0.031 26.022 0.000 0.660 0.817
## t3_inf_sha_beh_f1 =~
## t3_nf_sh_bh_01 1.000 0.677 0.642
## t3_nf_sh_bh_02 0.316 0.043 7.265 0.000 0.214 0.419
## t3_inf_sha_beh_f2 =~
## t3_nf_sh_bh_03 1.000 0.953 0.967
## t3_nf_sh_bh_04 1.002 0.011 89.521 0.000 0.955 0.949
## t3_inf_sha_beh_f3 =~
## t3_nf_sh_bh_05 1.000 0.910 0.972
## t3_nf_sh_bh_06 0.900 0.014 65.819 0.000 0.819 0.898
## t3_inf_sha_beh_f4 =~
## t3_nf_sh_bh_07 1.000 0.865 0.839
## t3_nf_sh_bh_08 0.739 0.025 29.436 0.000 0.639 0.693
## t3_inf_sha_beh_f5 =~
## t3_nf_sh_bh_10 1.000 0.817 0.962
## t3_nf_sh_bh_11 0.784 0.032 24.681 0.000 0.640 0.827
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f ~~
## t2_inf_sh_bh_f 0.070 0.009 7.506 0.000 0.634 0.634
## t3_inf_sh_bh_f 0.065 0.009 7.370 0.000 0.623 0.623
## t2_inf_sha_beh_f ~~
## t3_inf_sh_bh_f 0.067 0.009 7.348 0.000 0.642 0.642
## .t1_inf_sha_beh_01 ~~
## .t2_nf_sh_bh_01 0.388 0.029 13.343 0.000 0.388 0.553
## .t3_nf_sh_bh_01 0.353 0.028 12.458 0.000 0.353 0.536
## .t2_inf_sha_beh_01 ~~
## .t3_nf_sh_bh_01 0.424 0.029 14.607 0.000 0.424 0.606
## .t1_inf_sha_beh_02 ~~
## .t2_nf_sh_bh_02 0.060 0.007 8.248 0.000 0.060 0.249
## .t3_nf_sh_bh_02 0.058 0.008 7.677 0.000 0.058 0.234
## .t2_inf_sha_beh_02 ~~
## .t3_nf_sh_bh_02 0.065 0.006 10.151 0.000 0.065 0.309
## .t1_inf_sha_beh_03 ~~
## .t2_nf_sh_bh_03 0.028 0.004 6.407 0.000 0.028 0.340
## .t3_nf_sh_bh_03 0.032 0.004 8.046 0.000 0.032 0.459
## .t2_inf_sha_beh_03 ~~
## .t3_nf_sh_bh_03 0.041 0.004 9.282 0.000 0.041 0.557
## .t1_inf_sha_beh_04 ~~
## .t2_nf_sh_bh_04 0.042 0.005 9.001 0.000 0.042 0.445
## .t3_nf_sh_bh_04 0.031 0.004 7.293 0.000 0.031 0.351
## .t2_inf_sha_beh_04 ~~
## .t3_nf_sh_bh_04 0.055 0.005 10.873 0.000 0.055 0.522
## .t1_inf_sha_beh_05 ~~
## .t2_nf_sh_bh_05 0.016 0.004 3.659 0.000 0.016 0.287
## .t3_nf_sh_bh_05 0.020 0.004 4.884 0.000 0.020 0.409
## .t2_inf_sha_beh_05 ~~
## .t3_nf_sh_bh_05 0.012 0.004 2.701 0.007 0.012 0.216
## .t1_inf_sha_beh_06 ~~
## .t2_nf_sh_bh_06 0.078 0.006 12.530 0.000 0.078 0.466
## .t3_nf_sh_bh_06 0.064 0.006 10.955 0.000 0.064 0.391
## .t2_inf_sha_beh_06 ~~
## .t3_nf_sh_bh_06 0.073 0.006 12.165 0.000 0.073 0.446
## .t1_inf_sha_beh_07 ~~
## .t2_nf_sh_bh_07 0.142 0.012 12.280 0.000 0.142 0.489
## .t3_nf_sh_bh_07 0.119 0.012 10.125 0.000 0.119 0.393
## .t2_inf_sha_beh_07 ~~
## .t3_nf_sh_bh_07 0.119 0.012 9.841 0.000 0.119 0.393
## .t1_inf_sha_beh_08 ~~
## .t2_nf_sh_bh_08 0.200 0.015 13.031 0.000 0.200 0.412
## .t3_nf_sh_bh_08 0.171 0.015 11.738 0.000 0.171 0.370
## .t2_inf_sha_beh_08 ~~
## .t3_nf_sh_bh_08 0.204 0.015 13.550 0.000 0.204 0.437
## .t1_inf_sha_beh_10 ~~
## .t2_nf_sh_bh_10 0.021 0.009 2.259 0.024 0.021 0.198
## .t3_nf_sh_bh_10 0.034 0.009 3.789 0.000 0.034 0.396
## .t2_inf_sha_beh_10 ~~
## .t3_nf_sh_bh_10 0.057 0.009 6.680 0.000 0.057 0.865
## .t1_inf_sha_beh_11 ~~
## .t2_nf_sh_bh_11 0.071 0.009 8.058 0.000 0.071 0.340
## .t3_nf_sh_bh_11 0.044 0.008 5.393 0.000 0.044 0.228
## .t2_inf_sha_beh_11 ~~
## .t3_nf_sh_bh_11 0.036 0.008 4.516 0.000 0.036 0.177
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 1.712 0.029 59.284 0.000 1.712 1.584
## .t1_nf_sh_bh_02 1.244 0.016 79.577 0.000 1.244 2.126
## .t1_nf_sh_bh_03 2.672 0.028 94.195 0.000 2.672 2.515
## .t1_nf_sh_bh_04 2.725 0.028 96.736 0.000 2.725 2.583
## .t1_nf_sh_bh_05 2.545 0.026 96.580 0.000 2.545 2.579
## .t1_nf_sh_bh_06 2.431 0.026 93.391 0.000 2.431 2.494
## .t1_nf_sh_bh_07 2.878 0.028 101.990 0.000 2.878 2.723
## .t1_nf_sh_bh_08 2.194 0.025 86.085 0.000 2.194 2.301
## .t1_nf_sh_bh_10 1.794 0.024 75.976 0.000 1.794 2.031
## .t1_nf_sh_bh_11 1.739 0.022 77.543 0.000 1.739 2.072
## .t2_nf_sh_bh_01 1.712 0.028 60.234 0.000 1.712 1.611
## .t2_nf_sh_bh_02 1.214 0.013 93.902 0.000 1.214 2.508
## .t2_nf_sh_bh_03 2.682 0.028 97.488 0.000 2.682 2.604
## .t2_nf_sh_bh_04 2.764 0.028 98.933 0.000 2.764 2.643
## .t2_nf_sh_bh_05 2.558 0.026 99.185 0.000 2.558 2.649
## .t2_nf_sh_bh_06 2.434 0.026 95.404 0.000 2.434 2.549
## .t2_nf_sh_bh_07 2.923 0.028 104.656 0.000 2.923 2.795
## .t2_nf_sh_bh_08 2.239 0.026 86.402 0.000 2.239 2.308
## .t2_nf_sh_bh_10 1.805 0.023 78.878 0.000 1.805 2.108
## .t2_nf_sh_bh_11 1.735 0.022 80.298 0.000 1.735 2.145
## .t3_nf_sh_bh_01 1.702 0.028 60.385 0.000 1.702 1.613
## .t3_nf_sh_bh_02 1.227 0.014 90.023 0.000 1.227 2.405
## .t3_nf_sh_bh_03 2.627 0.026 99.825 0.000 2.627 2.665
## .t3_nf_sh_bh_04 2.692 0.027 100.265 0.000 2.692 2.677
## .t3_nf_sh_bh_05 2.509 0.025 100.441 0.000 2.509 2.682
## .t3_nf_sh_bh_06 2.395 0.024 98.403 0.000 2.395 2.628
## .t3_nf_sh_bh_07 2.864 0.028 104.096 0.000 2.864 2.780
## .t3_nf_sh_bh_08 2.178 0.025 88.269 0.000 2.178 2.360
## .t3_nf_sh_bh_10 1.776 0.023 78.316 0.000 1.776 2.092
## .t3_nf_sh_bh_11 1.715 0.021 82.955 0.000 1.715 2.216
## t1_inf_sh_bh_f 0.000 0.000 0.000
## t2_inf_sh_bh_f 0.000 0.000 0.000
## t3_inf_sh_bh_f 0.000 0.000 0.000
## .t1_nf_sh_bh_f1 0.000 0.000 0.000
## .t1_nf_sh_bh_f2 0.000 0.000 0.000
## .t1_nf_sh_bh_f3 0.000 0.000 0.000
## .t1_nf_sh_bh_f4 0.000 0.000 0.000
## .t1_nf_sh_bh_f5 0.000 0.000 0.000
## .t2_nf_sh_bh_f1 0.000 0.000 0.000
## .t2_nf_sh_bh_f2 0.000 0.000 0.000
## .t2_nf_sh_bh_f3 0.000 0.000 0.000
## .t2_nf_sh_bh_f4 0.000 0.000 0.000
## .t2_nf_sh_bh_f5 0.000 0.000 0.000
## .t3_nf_sh_bh_f1 0.000 0.000 0.000
## .t3_nf_sh_bh_f2 0.000 0.000 0.000
## .t3_nf_sh_bh_f3 0.000 0.000 0.000
## .t3_nf_sh_bh_f4 0.000 0.000 0.000
## .t3_nf_sh_bh_f5 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 0.662 0.075 8.863 0.000 0.662 0.566
## .t1_nf_sh_bh_02 0.281 0.013 21.026 0.000 0.281 0.823
## .t1_nf_sh_bh_03 0.078 0.006 13.449 0.000 0.078 0.069
## .t1_nf_sh_bh_04 0.079 0.006 13.720 0.000 0.079 0.071
## .t1_nf_sh_bh_05 0.050 0.007 7.567 0.000 0.050 0.051
## .t1_nf_sh_bh_06 0.168 0.008 20.668 0.000 0.168 0.177
## .t1_nf_sh_bh_07 0.291 0.019 15.143 0.000 0.291 0.261
## .t1_nf_sh_bh_08 0.479 0.020 23.684 0.000 0.479 0.527
## .t1_nf_sh_bh_10 0.139 0.022 6.200 0.000 0.139 0.178
## .t1_nf_sh_bh_11 0.198 0.019 10.641 0.000 0.198 0.282
## .t2_nf_sh_bh_01 0.745 0.067 11.112 0.000 0.745 0.659
## .t2_nf_sh_bh_02 0.207 0.009 23.266 0.000 0.207 0.882
## .t2_nf_sh_bh_03 0.087 0.007 13.044 0.000 0.087 0.082
## .t2_nf_sh_bh_04 0.110 0.007 15.106 0.000 0.110 0.100
## .t2_nf_sh_bh_05 0.064 0.007 8.561 0.000 0.064 0.069
## .t2_nf_sh_bh_06 0.167 0.009 19.166 0.000 0.167 0.183
## .t2_nf_sh_bh_07 0.291 0.019 14.921 0.000 0.291 0.266
## .t2_nf_sh_bh_08 0.491 0.021 23.560 0.000 0.491 0.522
## .t2_nf_sh_bh_10 0.082 0.022 3.694 0.000 0.082 0.112
## .t2_nf_sh_bh_11 0.218 0.017 13.197 0.000 0.218 0.333
## .t3_nf_sh_bh_01 0.655 0.069 9.474 0.000 0.655 0.588
## .t3_nf_sh_bh_02 0.214 0.010 21.037 0.000 0.214 0.824
## .t3_nf_sh_bh_03 0.064 0.006 11.384 0.000 0.064 0.065
## .t3_nf_sh_bh_04 0.100 0.006 15.955 0.000 0.100 0.099
## .t3_nf_sh_bh_05 0.048 0.007 7.310 0.000 0.048 0.055
## .t3_nf_sh_bh_06 0.161 0.008 20.827 0.000 0.161 0.193
## .t3_nf_sh_bh_07 0.314 0.020 15.452 0.000 0.314 0.295
## .t3_nf_sh_bh_08 0.443 0.019 22.956 0.000 0.443 0.520
## .t3_nf_sh_bh_10 0.053 0.025 2.168 0.030 0.053 0.074
## .t3_nf_sh_bh_11 0.189 0.016 11.637 0.000 0.189 0.316
## t1_inf_sh_bh_f 0.110 0.018 6.071 0.000 1.000 1.000
## t2_inf_sh_bh_f 0.112 0.018 6.317 0.000 1.000 1.000
## t3_inf_sh_bh_f 0.099 0.017 5.957 0.000 1.000 1.000
## .t1_nf_sh_bh_f1 0.398 0.070 5.707 0.000 0.784 0.784
## .t1_nf_sh_bh_f2 0.080 0.009 9.037 0.000 0.076 0.076
## .t1_nf_sh_bh_f3 0.105 0.009 11.092 0.000 0.114 0.114
## .t1_nf_sh_bh_f4 0.069 0.016 4.421 0.000 0.084 0.084
## .t1_nf_sh_bh_f5 0.457 0.029 15.986 0.000 0.712 0.712
## .t2_nf_sh_bh_f1 0.273 0.059 4.673 0.000 0.710 0.710
## .t2_nf_sh_bh_f2 0.070 0.009 7.583 0.000 0.071 0.071
## .t2_nf_sh_bh_f3 0.134 0.010 12.782 0.000 0.154 0.154
## .t2_nf_sh_bh_f4 0.083 0.016 5.251 0.000 0.103 0.103
## .t2_nf_sh_bh_f5 0.459 0.029 15.984 0.000 0.705 0.705
## .t3_nf_sh_bh_f1 0.360 0.063 5.697 0.000 0.784 0.784
## .t3_nf_sh_bh_f2 0.079 0.009 9.168 0.000 0.087 0.087
## .t3_nf_sh_bh_f3 0.097 0.009 10.421 0.000 0.117 0.117
## .t3_nf_sh_bh_f4 0.101 0.016 6.127 0.000 0.135 0.135
## .t3_nf_sh_bh_f5 0.512 0.032 16.139 0.000 0.767 0.7671.3.2.4 Second-Order Model Constrained
model <- '
# create factors
t1_inf_sha_beh_f =~ 1*t1_inf_sha_beh_f1 + o2*t1_inf_sha_beh_f2 + o3*t1_inf_sha_beh_f3 + o4*t1_inf_sha_beh_f4 + o5*t1_inf_sha_beh_f5
t2_inf_sha_beh_f =~ 1*t2_inf_sha_beh_f1 + o2*t2_inf_sha_beh_f2 + o3*t2_inf_sha_beh_f3 + o4*t2_inf_sha_beh_f4 + o5*t2_inf_sha_beh_f5
t3_inf_sha_beh_f =~ 1*t3_inf_sha_beh_f1 + o2*t3_inf_sha_beh_f2 + o3*t3_inf_sha_beh_f3 + o4*t3_inf_sha_beh_f4 + o5*t3_inf_sha_beh_f5
t1_inf_sha_beh_f1 =~ 1*t1_inf_sha_beh_01 + j2*t1_inf_sha_beh_02
t1_inf_sha_beh_f2 =~ 1*t1_inf_sha_beh_03 + k2*t1_inf_sha_beh_04
t1_inf_sha_beh_f3 =~ 1*t1_inf_sha_beh_05 + l2*t1_inf_sha_beh_06
t1_inf_sha_beh_f4 =~ 1*t1_inf_sha_beh_07 + m2*t1_inf_sha_beh_08
t1_inf_sha_beh_f5 =~ 1*t1_inf_sha_beh_10 + n2*t1_inf_sha_beh_11
t2_inf_sha_beh_f1 =~ 1*t2_inf_sha_beh_01 + j2*t2_inf_sha_beh_02
t2_inf_sha_beh_f2 =~ 1*t2_inf_sha_beh_03 + k2*t2_inf_sha_beh_04
t2_inf_sha_beh_f3 =~ 1*t2_inf_sha_beh_05 + l2*t2_inf_sha_beh_06
t2_inf_sha_beh_f4 =~ 1*t2_inf_sha_beh_07 + m2*t2_inf_sha_beh_08
t2_inf_sha_beh_f5 =~ 1*t2_inf_sha_beh_10 + n2*t2_inf_sha_beh_11
t3_inf_sha_beh_f1 =~ 1*t3_inf_sha_beh_01 + j2*t3_inf_sha_beh_02
t3_inf_sha_beh_f2 =~ 1*t3_inf_sha_beh_03 + k2*t3_inf_sha_beh_04
t3_inf_sha_beh_f3 =~ 1*t3_inf_sha_beh_05 + l2*t3_inf_sha_beh_06
t3_inf_sha_beh_f4 =~ 1*t3_inf_sha_beh_07 + m2*t3_inf_sha_beh_08
t3_inf_sha_beh_f5 =~ 1*t3_inf_sha_beh_10 + n2*t3_inf_sha_beh_11
# factor covariance
t1_inf_sha_beh_f ~~ t2_inf_sha_beh_f + t3_inf_sha_beh_f
t2_inf_sha_beh_f ~~ t3_inf_sha_beh_f
# item error covariance
t1_inf_sha_beh_01 ~~ t2_inf_sha_beh_01 + t3_inf_sha_beh_01
t2_inf_sha_beh_01 ~~ t3_inf_sha_beh_01
t1_inf_sha_beh_02 ~~ t2_inf_sha_beh_02 + t3_inf_sha_beh_02
t2_inf_sha_beh_02 ~~ t3_inf_sha_beh_02
t1_inf_sha_beh_03 ~~ t2_inf_sha_beh_03 + t3_inf_sha_beh_03
t2_inf_sha_beh_03 ~~ t3_inf_sha_beh_03
t1_inf_sha_beh_04 ~~ t2_inf_sha_beh_04 + t3_inf_sha_beh_04
t2_inf_sha_beh_04 ~~ t3_inf_sha_beh_04
t1_inf_sha_beh_05 ~~ t2_inf_sha_beh_05 + t3_inf_sha_beh_05
t2_inf_sha_beh_05 ~~ t3_inf_sha_beh_05
t1_inf_sha_beh_06 ~~ t2_inf_sha_beh_06 + t3_inf_sha_beh_06
t2_inf_sha_beh_06 ~~ t3_inf_sha_beh_06
t1_inf_sha_beh_07 ~~ t2_inf_sha_beh_07 + t3_inf_sha_beh_07
t2_inf_sha_beh_07 ~~ t3_inf_sha_beh_07
t1_inf_sha_beh_08 ~~ t2_inf_sha_beh_08 + t3_inf_sha_beh_08
t2_inf_sha_beh_08 ~~ t3_inf_sha_beh_08
t1_inf_sha_beh_10 ~~ t2_inf_sha_beh_10 + t3_inf_sha_beh_10
t2_inf_sha_beh_10 ~~ t3_inf_sha_beh_10
t1_inf_sha_beh_11 ~~ t2_inf_sha_beh_11 + t3_inf_sha_beh_11
t2_inf_sha_beh_11 ~~ t3_inf_sha_beh_11
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 184 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 138
## Number of equality constraints 18
##
## Number of observations 1403
## Number of missing patterns 38
##
## Model Test User Model:
##
## Test statistic 2527.695
## Degrees of freedom 375
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 39663.809
## Degrees of freedom 435
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.945
## Tucker-Lewis Index (TLI) 0.936
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -37165.009
## Loglikelihood unrestricted model (H1) -35901.162
##
## Akaike (AIC) 74570.018
## Bayesian (BIC) 75199.583
## Sample-size adjusted Bayesian (BIC) 74818.387
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.064
## 90 Percent confidence interval - lower 0.062
## 90 Percent confidence interval - upper 0.066
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.063
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f =~
## t1_nf___1 1.000 0.449 0.449
## t1_nf___2 (o2) 2.913 0.163 17.902 0.000 0.961 0.961
## t1_nf___3 (o3) 2.681 0.150 17.926 0.000 0.941 0.941
## t1_nf___4 (o4) 2.582 0.146 17.666 0.000 0.958 0.958
## t1_nf___5 (o5) 1.292 0.081 15.942 0.000 0.528 0.528
## t2_inf_sha_beh_f =~
## t2_nf___1 1.000 0.556 0.556
## t2_nf___2 (o2) 2.913 0.163 17.902 0.000 0.963 0.963
## t2_nf___3 (o3) 2.681 0.150 17.926 0.000 0.923 0.923
## t2_nf___4 (o4) 2.582 0.146 17.666 0.000 0.944 0.944
## t2_nf___5 (o5) 1.292 0.081 15.942 0.000 0.530 0.530
## t3_inf_sha_beh_f =~
## t3_nf___1 1.000 0.459 0.459
## t3_nf___2 (o2) 2.913 0.163 17.902 0.000 0.956 0.956
## t3_nf___3 (o3) 2.681 0.150 17.926 0.000 0.938 0.938
## t3_nf___4 (o4) 2.582 0.146 17.666 0.000 0.931 0.931
## t3_nf___5 (o5) 1.292 0.081 15.942 0.000 0.504 0.504
## t1_inf_sha_beh_f1 =~
## t1_n___01 1.000 0.750 0.693
## t1_n___02 (j2) 0.307 0.029 10.437 0.000 0.230 0.395
## t1_inf_sha_beh_f2 =~
## t1_n___03 1.000 1.021 0.964
## t1_n___04 (k2) 0.999 0.008 125.373 0.000 1.020 0.964
## t1_inf_sha_beh_f3 =~
## t1_n___05 1.000 0.960 0.974
## t1_n___06 (l2) 0.916 0.010 95.266 0.000 0.879 0.906
## t1_inf_sha_beh_f4 =~
## t1_n___07 1.000 0.908 0.859
## t1_n___08 (m2) 0.735 0.017 43.185 0.000 0.668 0.695
## t1_inf_sha_beh_f5 =~
## t1_n___10 1.000 0.825 0.931
## t1_n___11 (n2) 0.827 0.022 38.213 0.000 0.682 0.822
## t2_inf_sha_beh_f1 =~
## t2_n___01 1.000 0.587 0.553
## t2_n___02 (j2) 0.307 0.029 10.437 0.000 0.180 0.371
## t2_inf_sha_beh_f2 =~
## t2_n___03 1.000 0.987 0.959
## t2_n___04 (k2) 0.999 0.008 125.373 0.000 0.986 0.948
## t2_inf_sha_beh_f3 =~
## t2_n___05 1.000 0.948 0.967
## t2_n___06 (l2) 0.916 0.010 95.266 0.000 0.868 0.904
## t2_inf_sha_beh_f4 =~
## t2_n___07 1.000 0.892 0.856
## t2_n___08 (m2) 0.735 0.017 43.185 0.000 0.656 0.683
## t2_inf_sha_beh_f5 =~
## t2_n___10 1.000 0.796 0.937
## t2_n___11 (n2) 0.827 0.022 38.213 0.000 0.658 0.818
## t3_inf_sha_beh_f1 =~
## t3_n___01 1.000 0.684 0.648
## t3_n___02 (j2) 0.307 0.029 10.437 0.000 0.210 0.413
## t3_inf_sha_beh_f2 =~
## t3_n___03 1.000 0.956 0.967
## t3_n___04 (k2) 0.999 0.008 125.373 0.000 0.955 0.949
## t3_inf_sha_beh_f3 =~
## t3_n___05 1.000 0.897 0.970
## t3_n___06 (l2) 0.916 0.010 95.266 0.000 0.822 0.900
## t3_inf_sha_beh_f4 =~
## t3_n___07 1.000 0.870 0.841
## t3_n___08 (m2) 0.735 0.017 43.185 0.000 0.640 0.693
## t3_inf_sha_beh_f5 =~
## t3_n___10 1.000 0.806 0.943
## t3_n___11 (n2) 0.827 0.022 38.213 0.000 0.666 0.849
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_inf_sha_beh_f ~~
## t2_inf_sh_bh_f 0.070 0.009 8.178 0.000 0.634 0.634
## t3_inf_sh_bh_f 0.066 0.008 8.160 0.000 0.624 0.624
## t2_inf_sha_beh_f ~~
## t3_inf_sh_bh_f 0.066 0.008 8.180 0.000 0.642 0.642
## .t1_inf_sha_beh_01 ~~
## .t2_nf_sh_bh_01 0.389 0.029 13.353 0.000 0.389 0.563
## .t3_nf_sh_bh_01 0.352 0.028 12.450 0.000 0.352 0.561
## .t2_inf_sha_beh_01 ~~
## .t3_nf_sh_bh_01 0.424 0.029 14.629 0.000 0.424 0.598
## .t1_inf_sha_beh_02 ~~
## .t2_nf_sh_bh_02 0.060 0.007 8.257 0.000 0.060 0.248
## .t3_nf_sh_bh_02 0.057 0.007 7.651 0.000 0.057 0.231
## .t2_inf_sha_beh_02 ~~
## .t3_nf_sh_bh_02 0.065 0.006 10.141 0.000 0.065 0.311
## .t1_inf_sha_beh_03 ~~
## .t2_nf_sh_bh_03 0.028 0.004 6.384 0.000 0.028 0.338
## .t3_nf_sh_bh_03 0.032 0.004 8.013 0.000 0.032 0.456
## .t2_inf_sha_beh_03 ~~
## .t3_nf_sh_bh_03 0.041 0.004 9.275 0.000 0.041 0.563
## .t1_inf_sha_beh_04 ~~
## .t2_nf_sh_bh_04 0.042 0.005 9.055 0.000 0.042 0.448
## .t3_nf_sh_bh_04 0.031 0.004 7.313 0.000 0.031 0.353
## .t2_inf_sha_beh_04 ~~
## .t3_nf_sh_bh_04 0.055 0.005 10.882 0.000 0.055 0.519
## .t1_inf_sha_beh_05 ~~
## .t2_nf_sh_bh_05 0.016 0.004 3.615 0.000 0.016 0.290
## .t3_nf_sh_bh_05 0.020 0.004 4.946 0.000 0.020 0.404
## .t2_inf_sha_beh_05 ~~
## .t3_nf_sh_bh_05 0.012 0.004 2.647 0.008 0.012 0.209
## .t1_inf_sha_beh_06 ~~
## .t2_nf_sh_bh_06 0.078 0.006 12.532 0.000 0.078 0.462
## .t3_nf_sh_bh_06 0.064 0.006 10.977 0.000 0.064 0.393
## .t2_inf_sha_beh_06 ~~
## .t3_nf_sh_bh_06 0.073 0.006 12.172 0.000 0.073 0.448
## .t1_inf_sha_beh_07 ~~
## .t2_nf_sh_bh_07 0.143 0.012 12.309 0.000 0.143 0.490
## .t3_nf_sh_bh_07 0.119 0.012 10.131 0.000 0.119 0.392
## .t2_inf_sha_beh_07 ~~
## .t3_nf_sh_bh_07 0.119 0.012 9.873 0.000 0.119 0.395
## .t1_inf_sha_beh_08 ~~
## .t2_nf_sh_bh_08 0.200 0.015 13.020 0.000 0.200 0.412
## .t3_nf_sh_bh_08 0.170 0.015 11.732 0.000 0.170 0.370
## .t2_inf_sha_beh_08 ~~
## .t3_nf_sh_bh_08 0.204 0.015 13.564 0.000 0.204 0.437
## .t1_inf_sha_beh_10 ~~
## .t2_nf_sh_bh_10 0.020 0.009 2.185 0.029 0.020 0.214
## .t3_nf_sh_bh_10 0.033 0.009 3.712 0.000 0.033 0.364
## .t2_inf_sha_beh_10 ~~
## .t3_nf_sh_bh_10 0.058 0.009 6.777 0.000 0.058 0.692
## .t1_inf_sha_beh_11 ~~
## .t2_nf_sh_bh_11 0.071 0.009 8.116 0.000 0.071 0.325
## .t3_nf_sh_bh_11 0.044 0.008 5.438 0.000 0.044 0.227
## .t2_inf_sha_beh_11 ~~
## .t3_nf_sh_bh_11 0.035 0.008 4.432 0.000 0.035 0.184
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 1.712 0.029 59.200 0.000 1.712 1.582
## .t1_nf_sh_bh_02 1.244 0.016 79.843 0.000 1.244 2.134
## .t1_nf_sh_bh_03 2.672 0.028 94.456 0.000 2.672 2.522
## .t1_nf_sh_bh_04 2.725 0.028 96.494 0.000 2.725 2.576
## .t1_nf_sh_bh_05 2.545 0.026 96.751 0.000 2.545 2.584
## .t1_nf_sh_bh_06 2.431 0.026 93.828 0.000 2.431 2.506
## .t1_nf_sh_bh_07 2.878 0.028 101.995 0.000 2.878 2.723
## .t1_nf_sh_bh_08 2.194 0.026 85.417 0.000 2.194 2.283
## .t1_nf_sh_bh_10 1.794 0.024 75.745 0.000 1.794 2.024
## .t1_nf_sh_bh_11 1.739 0.022 78.360 0.000 1.739 2.094
## .t2_nf_sh_bh_01 1.713 0.028 60.347 0.000 1.713 1.614
## .t2_nf_sh_bh_02 1.214 0.013 93.495 0.000 1.214 2.498
## .t2_nf_sh_bh_03 2.682 0.028 97.502 0.000 2.682 2.605
## .t2_nf_sh_bh_04 2.764 0.028 99.447 0.000 2.764 2.656
## .t2_nf_sh_bh_05 2.558 0.026 97.716 0.000 2.558 2.610
## .t2_nf_sh_bh_06 2.434 0.026 94.906 0.000 2.434 2.536
## .t2_nf_sh_bh_07 2.923 0.028 105.038 0.000 2.923 2.805
## .t2_nf_sh_bh_08 2.239 0.026 87.237 0.000 2.239 2.331
## .t2_nf_sh_bh_10 1.805 0.023 79.573 0.000 1.805 2.127
## .t2_nf_sh_bh_11 1.735 0.021 80.683 0.000 1.735 2.156
## .t3_nf_sh_bh_01 1.702 0.028 60.409 0.000 1.702 1.613
## .t3_nf_sh_bh_02 1.227 0.014 90.119 0.000 1.227 2.408
## .t3_nf_sh_bh_03 2.627 0.026 99.497 0.000 2.627 2.656
## .t3_nf_sh_bh_04 2.692 0.027 100.168 0.000 2.692 2.674
## .t3_nf_sh_bh_05 2.509 0.025 101.544 0.000 2.509 2.712
## .t3_nf_sh_bh_06 2.395 0.024 98.240 0.000 2.395 2.623
## .t3_nf_sh_bh_07 2.864 0.028 103.672 0.000 2.864 2.768
## .t3_nf_sh_bh_08 2.178 0.025 88.164 0.000 2.178 2.357
## .t3_nf_sh_bh_10 1.776 0.023 77.831 0.000 1.776 2.079
## .t3_nf_sh_bh_11 1.715 0.021 81.806 0.000 1.715 2.186
## t1_inf_sh_bh_f 0.000 0.000 0.000
## t2_inf_sh_bh_f 0.000 0.000 0.000
## t3_inf_sh_bh_f 0.000 0.000 0.000
## .t1_nf_sh_bh_f1 0.000 0.000 0.000
## .t1_nf_sh_bh_f2 0.000 0.000 0.000
## .t1_nf_sh_bh_f3 0.000 0.000 0.000
## .t1_nf_sh_bh_f4 0.000 0.000 0.000
## .t1_nf_sh_bh_f5 0.000 0.000 0.000
## .t2_nf_sh_bh_f1 0.000 0.000 0.000
## .t2_nf_sh_bh_f2 0.000 0.000 0.000
## .t2_nf_sh_bh_f3 0.000 0.000 0.000
## .t2_nf_sh_bh_f4 0.000 0.000 0.000
## .t2_nf_sh_bh_f5 0.000 0.000 0.000
## .t3_nf_sh_bh_f1 0.000 0.000 0.000
## .t3_nf_sh_bh_f2 0.000 0.000 0.000
## .t3_nf_sh_bh_f3 0.000 0.000 0.000
## .t3_nf_sh_bh_f4 0.000 0.000 0.000
## .t3_nf_sh_bh_f5 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_nf_sh_bh_01 0.610 0.068 8.905 0.000 0.610 0.520
## .t1_nf_sh_bh_02 0.287 0.012 23.112 0.000 0.287 0.844
## .t1_nf_sh_bh_03 0.079 0.006 13.880 0.000 0.079 0.070
## .t1_nf_sh_bh_04 0.078 0.006 13.799 0.000 0.078 0.070
## .t1_nf_sh_bh_05 0.049 0.006 7.703 0.000 0.049 0.050
## .t1_nf_sh_bh_06 0.169 0.008 20.948 0.000 0.169 0.179
## .t1_nf_sh_bh_07 0.293 0.019 15.634 0.000 0.293 0.262
## .t1_nf_sh_bh_08 0.478 0.020 23.725 0.000 0.478 0.517
## .t1_nf_sh_bh_10 0.105 0.019 5.520 0.000 0.105 0.133
## .t1_nf_sh_bh_11 0.224 0.015 14.581 0.000 0.224 0.325
## .t2_nf_sh_bh_01 0.782 0.055 14.339 0.000 0.782 0.694
## .t2_nf_sh_bh_02 0.204 0.009 23.425 0.000 0.204 0.863
## .t2_nf_sh_bh_03 0.086 0.006 13.249 0.000 0.086 0.081
## .t2_nf_sh_bh_04 0.111 0.007 15.662 0.000 0.111 0.102
## .t2_nf_sh_bh_05 0.062 0.007 8.728 0.000 0.062 0.065
## .t2_nf_sh_bh_06 0.169 0.009 19.784 0.000 0.169 0.183
## .t2_nf_sh_bh_07 0.289 0.019 14.967 0.000 0.289 0.266
## .t2_nf_sh_bh_08 0.492 0.021 23.740 0.000 0.492 0.533
## .t2_nf_sh_bh_10 0.087 0.018 4.933 0.000 0.087 0.121
## .t2_nf_sh_bh_11 0.214 0.014 15.355 0.000 0.214 0.331
## .t3_nf_sh_bh_01 0.645 0.060 10.816 0.000 0.645 0.580
## .t3_nf_sh_bh_02 0.215 0.010 22.592 0.000 0.215 0.830
## .t3_nf_sh_bh_03 0.063 0.005 11.587 0.000 0.063 0.064
## .t3_nf_sh_bh_04 0.100 0.006 16.362 0.000 0.100 0.099
## .t3_nf_sh_bh_05 0.051 0.006 8.155 0.000 0.051 0.059
## .t3_nf_sh_bh_06 0.159 0.008 20.879 0.000 0.159 0.190
## .t3_nf_sh_bh_07 0.313 0.020 15.774 0.000 0.313 0.292
## .t3_nf_sh_bh_08 0.444 0.019 23.161 0.000 0.444 0.520
## .t3_nf_sh_bh_10 0.081 0.018 4.577 0.000 0.081 0.110
## .t3_nf_sh_bh_11 0.172 0.013 13.322 0.000 0.172 0.279
## t1_inf_sh_bh_f 0.114 0.013 8.535 0.000 1.000 1.000
## t2_inf_sh_bh_f 0.106 0.012 8.530 0.000 1.000 1.000
## t3_inf_sh_bh_f 0.099 0.012 8.528 0.000 1.000 1.000
## .t1_nf_sh_bh_f1 0.449 0.064 6.976 0.000 0.798 0.798
## .t1_nf_sh_bh_f2 0.080 0.009 9.386 0.000 0.077 0.077
## .t1_nf_sh_bh_f3 0.106 0.009 11.509 0.000 0.115 0.115
## .t1_nf_sh_bh_f4 0.067 0.015 4.436 0.000 0.081 0.081
## .t1_nf_sh_bh_f5 0.491 0.027 18.022 0.000 0.721 0.721
## .t2_nf_sh_bh_f1 0.238 0.043 5.486 0.000 0.691 0.691
## .t2_nf_sh_bh_f2 0.071 0.009 8.074 0.000 0.073 0.073
## .t2_nf_sh_bh_f3 0.133 0.010 12.994 0.000 0.148 0.148
## .t2_nf_sh_bh_f4 0.087 0.016 5.533 0.000 0.109 0.109
## .t2_nf_sh_bh_f5 0.455 0.025 18.012 0.000 0.719 0.719
## .t3_nf_sh_bh_f1 0.370 0.053 6.967 0.000 0.789 0.789
## .t3_nf_sh_bh_f2 0.078 0.008 9.489 0.000 0.086 0.086
## .t3_nf_sh_bh_f3 0.097 0.009 11.039 0.000 0.120 0.120
## .t3_nf_sh_bh_f4 0.100 0.016 6.221 0.000 0.132 0.132
## .t3_nf_sh_bh_f5 0.485 0.026 18.702 0.000 0.746 0.7461.3.3 Reliability
reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t1", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.879 0.913 0.946reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t2", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.877 0.922 0.940reliabilityL2(get(paste("fit", name, no, sep = "_")), paste("t3", name, "f", sep = "_"))## omegaL1 omegaL2 partialOmegaL1
## 0.868 0.905 0.9411.3.4 Longitudinal Invariance
(anova(get(paste("fit", name, no - 1, sep = "_")), get(paste("fit", name, no, sep = "_"))))1.4 Baseline Model
1.4.1 Second Order
name <- "all_vars"
no <- 0
model <- '
# Privacy Concerns
# create factors
t1_pri_con_f =~ 1*t1_pri_con_f1 + a2*t1_pri_con_f2
t2_pri_con_f =~ 1*t2_pri_con_f1 + a2*t2_pri_con_f2
t3_pri_con_f =~ 1*t3_pri_con_f1 + a2*t3_pri_con_f2
t1_pri_con_f1 =~ 1*t1_pri_con_04 + b2*t1_pri_con_05 + b3*t1_pri_con_06
t1_pri_con_f2 =~ 1*t1_pri_con_07 + c2*t1_pri_con_08 + c3*t1_pri_con_09
t2_pri_con_f1 =~ 1*t2_pri_con_04 + b2*t2_pri_con_05 + b3*t2_pri_con_06
t2_pri_con_f2 =~ 1*t2_pri_con_07 + c2*t2_pri_con_08 + c3*t2_pri_con_09
t3_pri_con_f1 =~ 1*t3_pri_con_04 + b2*t3_pri_con_05 + b3*t3_pri_con_06
t3_pri_con_f2 =~ 1*t3_pri_con_07 + c2*t3_pri_con_08 + c3*t3_pri_con_09
# error covariances
t3_pri_con_04 ~~ t2_pri_con_04 + t1_pri_con_04
t3_pri_con_05 ~~ t2_pri_con_05 + t1_pri_con_05
t3_pri_con_06 ~~ t2_pri_con_06 + t1_pri_con_06
t3_pri_con_07 ~~ t2_pri_con_07 + t1_pri_con_07
t3_pri_con_08 ~~ t2_pri_con_08 + t1_pri_con_08
t3_pri_con_09 ~~ t2_pri_con_09 + t1_pri_con_09
t2_pri_con_04 ~~ t1_pri_con_04
t2_pri_con_05 ~~ t1_pri_con_05
t2_pri_con_06 ~~ t1_pri_con_06
t2_pri_con_07 ~~ t1_pri_con_07
t2_pri_con_08 ~~ t1_pri_con_08
t2_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t1_pri_con_f ~~ t2_pri_con_f + t3_pri_con_f
t2_pri_con_f ~~ t3_pri_con_f
# Information Sharing Attitude
# create factors
t1_inf_sha_att_f =~ 1*t1_inf_sha_att_f1 + d2*t1_inf_sha_att_f2 + d3*t1_inf_sha_att_f3 + d4*t1_inf_sha_att_f4 + d5*t1_inf_sha_att_f5
t2_inf_sha_att_f =~ 1*t2_inf_sha_att_f1 + d2*t2_inf_sha_att_f2 + d3*t2_inf_sha_att_f3 + d4*t2_inf_sha_att_f4 + d5*t2_inf_sha_att_f5
t3_inf_sha_att_f =~ 1*t3_inf_sha_att_f1 + d2*t3_inf_sha_att_f2 + d3*t3_inf_sha_att_f3 + d4*t3_inf_sha_att_f4 + d5*t3_inf_sha_att_f5
t1_inf_sha_att_f1 =~ 1*t1_inf_sha_att_01 + e*t1_inf_sha_att_02
t1_inf_sha_att_f2 =~ 1*t1_inf_sha_att_03 + f*t1_inf_sha_att_04
t1_inf_sha_att_f3 =~ 1*t1_inf_sha_att_05 + g*t1_inf_sha_att_06
t1_inf_sha_att_f4 =~ 1*t1_inf_sha_att_07 + h*t1_inf_sha_att_08
t1_inf_sha_att_f5 =~ 1*t1_inf_sha_att_10 + i*t1_inf_sha_att_11
t2_inf_sha_att_f1 =~ 1*t2_inf_sha_att_01 + e*t2_inf_sha_att_02
t2_inf_sha_att_f2 =~ 1*t2_inf_sha_att_03 + f*t2_inf_sha_att_04
t2_inf_sha_att_f3 =~ 1*t2_inf_sha_att_05 + g*t2_inf_sha_att_06
t2_inf_sha_att_f4 =~ 1*t2_inf_sha_att_07 + h*t2_inf_sha_att_08
t2_inf_sha_att_f5 =~ 1*t2_inf_sha_att_10 + i*t2_inf_sha_att_11
t3_inf_sha_att_f1 =~ 1*t3_inf_sha_att_01 + e*t3_inf_sha_att_02
t3_inf_sha_att_f2 =~ 1*t3_inf_sha_att_03 + f*t3_inf_sha_att_04
t3_inf_sha_att_f3 =~ 1*t3_inf_sha_att_05 + g*t3_inf_sha_att_06
t3_inf_sha_att_f4 =~ 1*t3_inf_sha_att_07 + h*t3_inf_sha_att_08
t3_inf_sha_att_f5 =~ 1*t3_inf_sha_att_10 + i*t3_inf_sha_att_11
# factor covariance
t1_inf_sha_att_f ~~ t2_inf_sha_att_f + t3_inf_sha_att_f
t2_inf_sha_att_f ~~ t3_inf_sha_att_f
# item error covariance
t1_inf_sha_att_01 ~~ t2_inf_sha_att_01 + t3_inf_sha_att_01
t2_inf_sha_att_01 ~~ t3_inf_sha_att_01
t1_inf_sha_att_02 ~~ t2_inf_sha_att_02 + t3_inf_sha_att_02
t2_inf_sha_att_02 ~~ t3_inf_sha_att_02
t1_inf_sha_att_03 ~~ t2_inf_sha_att_03 + t3_inf_sha_att_03
t2_inf_sha_att_03 ~~ t3_inf_sha_att_03
t1_inf_sha_att_04 ~~ t2_inf_sha_att_04 + t3_inf_sha_att_04
t2_inf_sha_att_04 ~~ t3_inf_sha_att_04
t1_inf_sha_att_05 ~~ t2_inf_sha_att_05 + t3_inf_sha_att_05
t2_inf_sha_att_05 ~~ t3_inf_sha_att_05
t1_inf_sha_att_06 ~~ t2_inf_sha_att_06 + t3_inf_sha_att_06
t2_inf_sha_att_06 ~~ t3_inf_sha_att_06
t1_inf_sha_att_07 ~~ t2_inf_sha_att_07 + t3_inf_sha_att_07
t2_inf_sha_att_07 ~~ t3_inf_sha_att_07
t1_inf_sha_att_08 ~~ t2_inf_sha_att_08 + t3_inf_sha_att_08
t2_inf_sha_att_08 ~~ t3_inf_sha_att_08
t1_inf_sha_att_10 ~~ t2_inf_sha_att_10 + t3_inf_sha_att_10
t2_inf_sha_att_10 ~~ t3_inf_sha_att_10
t1_inf_sha_att_11 ~~ t2_inf_sha_att_11 + t3_inf_sha_att_11
t2_inf_sha_att_11 ~~ t3_inf_sha_att_11
# information sharing behavior
# create factors
t1_inf_sha_beh_f =~ 1*t1_inf_sha_beh_f1 + o2*t1_inf_sha_beh_f2 + o3*t1_inf_sha_beh_f3 + o4*t1_inf_sha_beh_f4 + o5*t1_inf_sha_beh_f5
t2_inf_sha_beh_f =~ 1*t2_inf_sha_beh_f1 + o2*t2_inf_sha_beh_f2 + o3*t2_inf_sha_beh_f3 + o4*t2_inf_sha_beh_f4 + o5*t2_inf_sha_beh_f5
t3_inf_sha_beh_f =~ 1*t3_inf_sha_beh_f1 + o2*t3_inf_sha_beh_f2 + o3*t3_inf_sha_beh_f3 + o4*t3_inf_sha_beh_f4 + o5*t3_inf_sha_beh_f5
t1_inf_sha_beh_f1 =~ 1*t1_inf_sha_beh_01 + j2*t1_inf_sha_beh_02
t1_inf_sha_beh_f2 =~ 1*t1_inf_sha_beh_03 + k2*t1_inf_sha_beh_04
t1_inf_sha_beh_f3 =~ 1*t1_inf_sha_beh_05 + l2*t1_inf_sha_beh_06
t1_inf_sha_beh_f4 =~ 1*t1_inf_sha_beh_07 + m2*t1_inf_sha_beh_08
t1_inf_sha_beh_f5 =~ 1*t1_inf_sha_beh_10 + n2*t1_inf_sha_beh_11
t2_inf_sha_beh_f1 =~ 1*t2_inf_sha_beh_01 + j2*t2_inf_sha_beh_02
t2_inf_sha_beh_f2 =~ 1*t2_inf_sha_beh_03 + k2*t2_inf_sha_beh_04
t2_inf_sha_beh_f3 =~ 1*t2_inf_sha_beh_05 + l2*t2_inf_sha_beh_06
t2_inf_sha_beh_f4 =~ 1*t2_inf_sha_beh_07 + m2*t2_inf_sha_beh_08
t2_inf_sha_beh_f5 =~ 1*t2_inf_sha_beh_10 + n2*t2_inf_sha_beh_11
t3_inf_sha_beh_f1 =~ 1*t3_inf_sha_beh_01 + j2*t3_inf_sha_beh_02
t3_inf_sha_beh_f2 =~ 1*t3_inf_sha_beh_03 + k2*t3_inf_sha_beh_04
t3_inf_sha_beh_f3 =~ 1*t3_inf_sha_beh_05 + l2*t3_inf_sha_beh_06
t3_inf_sha_beh_f4 =~ 1*t3_inf_sha_beh_07 + m2*t3_inf_sha_beh_08
t3_inf_sha_beh_f5 =~ 1*t3_inf_sha_beh_10 + n2*t3_inf_sha_beh_11
# factor covariance
t1_inf_sha_beh_f ~~ t2_inf_sha_beh_f + t3_inf_sha_beh_f
t2_inf_sha_beh_f ~~ t3_inf_sha_beh_f
# item error covariance
t1_inf_sha_beh_01 ~~ t2_inf_sha_beh_01 + t3_inf_sha_beh_01
t2_inf_sha_beh_01 ~~ t3_inf_sha_beh_01
t1_inf_sha_beh_02 ~~ t2_inf_sha_beh_02 + t3_inf_sha_beh_02
t2_inf_sha_beh_02 ~~ t3_inf_sha_beh_02
t1_inf_sha_beh_03 ~~ t2_inf_sha_beh_03 + t3_inf_sha_beh_03
t2_inf_sha_beh_03 ~~ t3_inf_sha_beh_03
t1_inf_sha_beh_04 ~~ t2_inf_sha_beh_04 + t3_inf_sha_beh_04
t2_inf_sha_beh_04 ~~ t3_inf_sha_beh_04
t1_inf_sha_beh_05 ~~ t2_inf_sha_beh_05 + t3_inf_sha_beh_05
t2_inf_sha_beh_05 ~~ t3_inf_sha_beh_05
t1_inf_sha_beh_06 ~~ t2_inf_sha_beh_06 + t3_inf_sha_beh_06
t2_inf_sha_beh_06 ~~ t3_inf_sha_beh_06
t1_inf_sha_beh_07 ~~ t2_inf_sha_beh_07 + t3_inf_sha_beh_07
t2_inf_sha_beh_07 ~~ t3_inf_sha_beh_07
t1_inf_sha_beh_08 ~~ t2_inf_sha_beh_08 + t3_inf_sha_beh_08
t2_inf_sha_beh_08 ~~ t3_inf_sha_beh_08
t1_inf_sha_beh_10 ~~ t2_inf_sha_beh_10 + t3_inf_sha_beh_10
t2_inf_sha_beh_10 ~~ t3_inf_sha_beh_10
t1_inf_sha_beh_11 ~~ t2_inf_sha_beh_11 + t3_inf_sha_beh_11
t2_inf_sha_beh_11 ~~ t3_inf_sha_beh_11
## Correlations Attitude and Behavior-Items
t1_inf_sha_beh_01 ~~ t1_inf_sha_att_01
t1_inf_sha_beh_02 ~~ t1_inf_sha_att_02
t1_inf_sha_beh_03 ~~ t1_inf_sha_att_03
t1_inf_sha_beh_04 ~~ t1_inf_sha_att_04
t1_inf_sha_beh_05 ~~ t1_inf_sha_att_05
t1_inf_sha_beh_06 ~~ t1_inf_sha_att_06
t1_inf_sha_beh_07 ~~ t1_inf_sha_att_07
t1_inf_sha_beh_08 ~~ t1_inf_sha_att_08
t1_inf_sha_beh_10 ~~ t1_inf_sha_att_10
t1_inf_sha_beh_11 ~~ t1_inf_sha_att_11
t2_inf_sha_beh_01 ~~ t2_inf_sha_att_01
t2_inf_sha_beh_02 ~~ t2_inf_sha_att_02
t2_inf_sha_beh_03 ~~ t2_inf_sha_att_03
t2_inf_sha_beh_04 ~~ t2_inf_sha_att_04
t2_inf_sha_beh_05 ~~ t2_inf_sha_att_05
t2_inf_sha_beh_06 ~~ t2_inf_sha_att_06
t2_inf_sha_beh_07 ~~ t2_inf_sha_att_07
t2_inf_sha_beh_08 ~~ t2_inf_sha_att_08
t2_inf_sha_beh_10 ~~ t2_inf_sha_att_10
t2_inf_sha_beh_11 ~~ t2_inf_sha_att_11
t3_inf_sha_beh_01 ~~ t3_inf_sha_att_01
t3_inf_sha_beh_02 ~~ t3_inf_sha_att_02
t3_inf_sha_beh_03 ~~ t3_inf_sha_att_03
t3_inf_sha_beh_04 ~~ t3_inf_sha_att_04
t3_inf_sha_beh_05 ~~ t3_inf_sha_att_05
t3_inf_sha_beh_06 ~~ t3_inf_sha_att_06
t3_inf_sha_beh_07 ~~ t3_inf_sha_att_07
t3_inf_sha_beh_08 ~~ t3_inf_sha_att_08
t3_inf_sha_beh_10 ~~ t3_inf_sha_att_10
t3_inf_sha_beh_11 ~~ t3_inf_sha_att_11
'
no <- no + 1
assign(paste("fit", name, no, sep = "_"), cfa(model, d_wide, missing = "ML"))
summary(get(paste("fit", name, no, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 339 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 414
## Number of equality constraints 46
##
## Number of observations 1403
## Number of missing patterns 109
##
## Model Test User Model:
##
## Test statistic 11028.436
## Degrees of freedom 2791
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 99651.877
## Degrees of freedom 3003
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.915
## Tucker-Lewis Index (TLI) 0.908
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -113455.861
## Loglikelihood unrestricted model (H1) -107941.643
##
## Akaike (AIC) 227647.721
## Bayesian (BIC) 229578.385
## Sample-size adjusted Bayesian (BIC) 228409.385
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.046
## 90 Percent confidence interval - lower 0.045
## 90 Percent confidence interval - upper 0.047
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.066
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pr_c_1 1.000 0.943 0.943
## t1_pr_c_2 (a2) 1.207 0.031 38.919 0.000 0.950 0.950
## t2_pri_con_f =~
## t2_pr_c_1 1.000 0.966 0.966
## t2_pr_c_2 (a2) 1.207 0.031 38.919 0.000 0.952 0.952
## t3_pri_con_f =~
## t3_pr_c_1 1.000 0.986 0.986
## t3_pr_c_2 (a2) 1.207 0.031 38.919 0.000 0.954 0.954
## t1_pri_con_f1 =~
## t1_pr__04 1.000 0.846 0.790
## t1_pr__05 (b2) 1.024 0.028 37.035 0.000 0.866 0.674
## t1_pr__06 (b3) 1.086 0.024 44.576 0.000 0.919 0.779
## t1_pri_con_f2 =~
## t1_pr__07 1.000 1.013 0.816
## t1_pr__08 (c2) 0.972 0.018 55.068 0.000 0.984 0.841
## t1_pr__09 (c3) 0.859 0.016 52.493 0.000 0.871 0.827
## t2_pri_con_f1 =~
## t2_pr__04 1.000 0.847 0.798
## t2_pr__05 (b2) 1.024 0.028 37.035 0.000 0.868 0.672
## t2_pr__06 (b3) 1.086 0.024 44.576 0.000 0.921 0.791
## t2_pri_con_f2 =~
## t2_pr__07 1.000 1.039 0.839
## t2_pr__08 (c2) 0.972 0.018 55.068 0.000 1.009 0.855
## t2_pr__09 (c3) 0.859 0.016 52.493 0.000 0.892 0.834
## t3_pri_con_f1 =~
## t3_pr__04 1.000 0.835 0.791
## t3_pr__05 (b2) 1.024 0.028 37.035 0.000 0.855 0.658
## t3_pr__06 (b3) 1.086 0.024 44.576 0.000 0.907 0.791
## t3_pri_con_f2 =~
## t3_pr__07 1.000 1.042 0.843
## t3_pr__08 (c2) 0.972 0.018 55.068 0.000 1.012 0.869
## t3_pr__09 (c3) 0.859 0.016 52.493 0.000 0.895 0.831
## t1_inf_sha_att_f =~
## t1_nf___1 1.000 0.427 0.427
## t1_nf___2 (d2) 2.922 0.169 17.338 0.000 0.957 0.957
## t1_nf___3 (d3) 2.849 0.164 17.339 0.000 0.929 0.929
## t1_nf___4 (d4) 2.196 0.131 16.707 0.000 0.883 0.883
## t1_nf___5 (d5) 1.474 0.096 15.365 0.000 0.489 0.489
## t2_inf_sha_att_f =~
## t2_nf___1 1.000 0.450 0.450
## t2_nf___2 (d2) 2.922 0.169 17.338 0.000 0.962 0.962
## t2_nf___3 (d3) 2.849 0.164 17.339 0.000 0.942 0.942
## t2_nf___4 (d4) 2.196 0.131 16.707 0.000 0.917 0.917
## t2_nf___5 (d5) 1.474 0.096 15.365 0.000 0.492 0.492
## t3_inf_sha_att_f =~
## t3_nf___1 1.000 0.443 0.443
## t3_nf___2 (d2) 2.922 0.169 17.338 0.000 0.935 0.935
## t3_nf___3 (d3) 2.849 0.164 17.339 0.000 0.923 0.923
## t3_nf___4 (d4) 2.196 0.131 16.707 0.000 0.901 0.901
## t3_nf___5 (d5) 1.474 0.096 15.365 0.000 0.485 0.485
## t1_inf_sha_att_f1 =~
## t1_n___01 1.000 0.771 0.698
## t1_n___02 (e) 0.870 0.059 14.673 0.000 0.671 0.615
## t1_inf_sha_att_f2 =~
## t1_n___03 1.000 1.006 0.920
## t1_n___04 (f) 0.953 0.012 81.166 0.000 0.959 0.901
## t1_inf_sha_att_f3 =~
## t1_n___05 1.000 1.010 0.944
## t1_n___06 (g) 0.942 0.012 77.141 0.000 0.952 0.881
## t1_inf_sha_att_f4 =~
## t1_n___07 1.000 0.819 0.751
## t1_n___08 (h) 0.883 0.024 36.334 0.000 0.724 0.687
## t1_inf_sha_att_f5 =~
## t1_n___10 1.000 0.993 0.930
## t1_n___11 (i) 0.976 0.020 49.884 0.000 0.969 0.920
## t2_inf_sha_att_f1 =~
## t2_n___01 1.000 0.734 0.656
## t2_n___02 (e) 0.870 0.059 14.673 0.000 0.639 0.594
## t2_inf_sha_att_f2 =~
## t2_n___03 1.000 1.003 0.920
## t2_n___04 (f) 0.953 0.012 81.166 0.000 0.956 0.893
## t2_inf_sha_att_f3 =~
## t2_n___05 1.000 0.999 0.946
## t2_n___06 (g) 0.942 0.012 77.141 0.000 0.941 0.867
## t2_inf_sha_att_f4 =~
## t2_n___07 1.000 0.792 0.731
## t2_n___08 (h) 0.883 0.024 36.334 0.000 0.699 0.664
## t2_inf_sha_att_f5 =~
## t2_n___10 1.000 0.990 0.948
## t2_n___11 (i) 0.976 0.020 49.884 0.000 0.967 0.921
## t3_inf_sha_att_f1 =~
## t3_n___01 1.000 0.718 0.647
## t3_n___02 (e) 0.870 0.059 14.673 0.000 0.625 0.598
## t3_inf_sha_att_f2 =~
## t3_n___03 1.000 0.996 0.933
## t3_n___04 (f) 0.953 0.012 81.166 0.000 0.949 0.895
## t3_inf_sha_att_f3 =~
## t3_n___05 1.000 0.984 0.936
## t3_n___06 (g) 0.942 0.012 77.141 0.000 0.927 0.872
## t3_inf_sha_att_f4 =~
## t3_n___07 1.000 0.777 0.753
## t3_n___08 (h) 0.883 0.024 36.334 0.000 0.686 0.675
## t3_inf_sha_att_f5 =~
## t3_n___10 1.000 0.967 0.944
## t3_n___11 (i) 0.976 0.020 49.884 0.000 0.944 0.917
## t1_inf_sha_beh_f =~
## t1_nf___1 1.000 0.476 0.476
## t1_nf___2 (o2) 2.866 0.153 18.734 0.000 0.961 0.961
## t1_nf___3 (o3) 2.651 0.141 18.753 0.000 0.943 0.943
## t1_nf___4 (o4) 2.555 0.138 18.482 0.000 0.969 0.969
## t1_nf___5 (o5) 1.280 0.077 16.568 0.000 0.532 0.532
## t2_inf_sha_beh_f =~
## t2_nf___1 1.000 0.586 0.586
## t2_nf___2 (o2) 2.866 0.153 18.734 0.000 0.961 0.961
## t2_nf___3 (o3) 2.651 0.141 18.753 0.000 0.925 0.925
## t2_nf___4 (o4) 2.555 0.138 18.482 0.000 0.956 0.956
## t2_nf___5 (o5) 1.280 0.077 16.568 0.000 0.533 0.533
## t3_inf_sha_beh_f =~
## t3_nf___1 1.000 0.498 0.498
## t3_nf___2 (o2) 2.866 0.153 18.734 0.000 0.954 0.954
## t3_nf___3 (o3) 2.651 0.141 18.753 0.000 0.942 0.942
## t3_nf___4 (o4) 2.555 0.138 18.482 0.000 0.944 0.944
## t3_nf___5 (o5) 1.280 0.077 16.568 0.000 0.507 0.507
## t1_inf_sha_beh_f1 =~
## t1_n___01 1.000 0.718 0.673
## t1_n___02 (j2) 0.305 0.028 10.729 0.000 0.219 0.378
## t1_inf_sha_beh_f2 =~
## t1_n___03 1.000 1.019 0.964
## t1_n___04 (k2) 0.999 0.008 129.856 0.000 1.017 0.965
## t1_inf_sha_beh_f3 =~
## t1_n___05 1.000 0.960 0.974
## t1_n___06 (l2) 0.919 0.009 98.441 0.000 0.883 0.910
## t1_inf_sha_beh_f4 =~
## t1_n___07 1.000 0.901 0.854
## t1_n___08 (m2) 0.738 0.016 44.897 0.000 0.664 0.697
## t1_inf_sha_beh_f5 =~
## t1_n___10 1.000 0.822 0.926
## t1_n___11 (n2) 0.828 0.021 38.714 0.000 0.680 0.825
## t2_inf_sha_beh_f1 =~
## t2_n___01 1.000 0.564 0.539
## t2_n___02 (j2) 0.305 0.028 10.729 0.000 0.172 0.358
## t2_inf_sha_beh_f2 =~
## t2_n___03 1.000 0.986 0.961
## t2_n___04 (k2) 0.999 0.008 129.856 0.000 0.985 0.949
## t2_inf_sha_beh_f3 =~
## t2_n___05 1.000 0.947 0.966
## t2_n___06 (l2) 0.919 0.009 98.441 0.000 0.871 0.908
## t2_inf_sha_beh_f4 =~
## t2_n___07 1.000 0.884 0.849
## t2_n___08 (m2) 0.738 0.016 44.897 0.000 0.652 0.689
## t2_inf_sha_beh_f5 =~
## t2_n___10 1.000 0.794 0.938
## t2_n___11 (n2) 0.828 0.021 38.714 0.000 0.657 0.817
## t3_inf_sha_beh_f1 =~
## t3_n___01 1.000 0.638 0.615
## t3_n___02 (j2) 0.305 0.028 10.729 0.000 0.195 0.387
## t3_inf_sha_beh_f2 =~
## t3_n___03 1.000 0.956 0.968
## t3_n___04 (k2) 0.999 0.008 129.856 0.000 0.955 0.951
## t3_inf_sha_beh_f3 =~
## t3_n___05 1.000 0.895 0.969
## t3_n___06 (l2) 0.919 0.009 98.441 0.000 0.823 0.903
## t3_inf_sha_beh_f4 =~
## t3_n___07 1.000 0.861 0.836
## t3_n___08 (m2) 0.738 0.016 44.897 0.000 0.635 0.697
## t3_inf_sha_beh_f5 =~
## t3_n___10 1.000 0.803 0.946
## t3_n___11 (n2) 0.828 0.021 38.714 0.000 0.665 0.846
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t2_pri_con_04 ~~
## .t3_pri_con_04 0.071 0.014 4.983 0.000 0.071 0.172
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.093 0.015 6.240 0.000 0.093 0.220
## .t2_pri_con_05 ~~
## .t3_pri_con_05 0.433 0.031 14.121 0.000 0.433 0.464
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.454 0.031 14.638 0.000 0.454 0.490
## .t2_pri_con_06 ~~
## .t3_pri_con_06 0.166 0.018 9.427 0.000 0.166 0.332
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.160 0.018 8.820 0.000 0.160 0.308
## .t2_pri_con_07 ~~
## .t3_pri_con_07 0.157 0.017 9.461 0.000 0.157 0.349
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.171 0.018 9.754 0.000 0.171 0.359
## .t2_pri_con_08 ~~
## .t3_pri_con_08 0.109 0.014 8.049 0.000 0.109 0.310
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.099 0.014 7.174 0.000 0.099 0.272
## .t2_pri_con_09 ~~
## .t3_pri_con_09 0.109 0.013 8.564 0.000 0.109 0.307
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.070 0.012 5.586 0.000 0.070 0.197
## .t1_pri_con_04 ~~
## .t2_pri_con_04 0.087 0.015 5.844 0.000 0.087 0.208
## .t1_pri_con_05 ~~
## .t2_pri_con_05 0.401 0.030 13.351 0.000 0.401 0.442
## .t1_pri_con_06 ~~
## .t2_pri_con_06 0.157 0.019 8.492 0.000 0.157 0.299
## .t1_pri_con_07 ~~
## .t2_pri_con_07 0.158 0.018 8.984 0.000 0.158 0.326
## .t1_pri_con_08 ~~
## .t2_pri_con_08 0.092 0.014 6.441 0.000 0.092 0.239
## .t1_pri_con_09 ~~
## .t2_pri_con_09 0.075 0.012 6.055 0.000 0.075 0.215
## t1_pri_con_f ~~
## t2_pri_con_f 0.514 0.030 17.198 0.000 0.787 0.787
## t3_pri_con_f 0.507 0.029 17.201 0.000 0.772 0.772
## t2_pri_con_f ~~
## t3_pri_con_f 0.530 0.030 17.387 0.000 0.786 0.786
## t1_inf_sha_att_f ~~
## t2_inf_sh_tt_f 0.063 0.008 7.861 0.000 0.577 0.577
## t3_inf_sh_tt_f 0.059 0.008 7.841 0.000 0.563 0.563
## t2_inf_sha_att_f ~~
## t3_inf_sh_tt_f 0.067 0.008 7.984 0.000 0.636 0.636
## .t1_inf_sha_att_01 ~~
## .t2_nf_sh_tt_01 0.240 0.028 8.508 0.000 0.240 0.359
## .t3_nf_sh_tt_01 0.259 0.028 9.248 0.000 0.259 0.387
## .t2_inf_sha_att_01 ~~
## .t3_nf_sh_tt_01 0.279 0.030 9.411 0.000 0.279 0.390
## .t1_inf_sha_att_02 ~~
## .t2_nf_sh_tt_02 0.311 0.028 11.136 0.000 0.311 0.419
## .t3_nf_sh_tt_02 0.292 0.027 10.816 0.000 0.292 0.406
## .t2_inf_sha_att_02 ~~
## .t3_nf_sh_tt_02 0.348 0.028 12.567 0.000 0.348 0.481
## .t1_inf_sha_att_03 ~~
## .t2_nf_sh_tt_03 0.057 0.008 6.793 0.000 0.057 0.313
## .t3_nf_sh_tt_03 0.055 0.008 6.778 0.000 0.055 0.336
## .t2_inf_sha_att_03 ~~
## .t3_nf_sh_tt_03 0.057 0.008 7.047 0.000 0.057 0.347
## .t1_inf_sha_att_04 ~~
## .t2_nf_sh_tt_04 0.070 0.009 7.824 0.000 0.070 0.315
## .t3_nf_sh_tt_04 0.053 0.009 6.106 0.000 0.053 0.243
## .t2_inf_sha_att_04 ~~
## .t3_nf_sh_tt_04 0.075 0.009 8.011 0.000 0.075 0.327
## .t1_inf_sha_att_05 ~~
## .t2_nf_sh_tt_05 0.026 0.007 3.493 0.000 0.026 0.213
## .t3_nf_sh_tt_05 0.031 0.008 4.025 0.000 0.031 0.234
## .t2_inf_sha_att_05 ~~
## .t3_nf_sh_tt_05 0.024 0.007 3.319 0.001 0.024 0.191
## .t1_inf_sha_att_06 ~~
## .t2_nf_sh_tt_06 0.136 0.011 12.653 0.000 0.136 0.493
## .t3_nf_sh_tt_06 0.116 0.010 11.249 0.000 0.116 0.434
## .t2_inf_sha_att_06 ~~
## .t3_nf_sh_tt_06 0.122 0.011 11.493 0.000 0.122 0.432
## .t1_inf_sha_att_07 ~~
## .t2_nf_sh_tt_07 0.238 0.019 12.350 0.000 0.238 0.449
## .t3_nf_sh_tt_07 0.198 0.018 11.046 0.000 0.198 0.406
## .t2_inf_sha_att_07 ~~
## .t3_nf_sh_tt_07 0.232 0.018 12.645 0.000 0.232 0.464
## .t1_inf_sha_att_08 ~~
## .t2_nf_sh_tt_08 0.216 0.020 10.682 0.000 0.216 0.358
## .t3_nf_sh_tt_08 0.227 0.019 11.705 0.000 0.227 0.396
## .t2_inf_sha_att_08 ~~
## .t3_nf_sh_tt_08 0.208 0.020 10.514 0.000 0.208 0.353
## .t1_inf_sha_att_10 ~~
## .t2_nf_sh_tt_10 0.032 0.011 2.975 0.003 0.032 0.247
## .t3_nf_sh_tt_10 0.006 0.011 0.577 0.564 0.006 0.048
## .t2_inf_sha_att_10 ~~
## .t3_nf_sh_tt_10 0.001 0.011 0.126 0.899 0.001 0.012
## .t1_inf_sha_att_11 ~~
## .t2_nf_sh_tt_11 0.034 0.011 3.117 0.002 0.034 0.199
## .t3_nf_sh_tt_11 0.049 0.011 4.519 0.000 0.049 0.286
## .t2_inf_sha_att_11 ~~
## .t3_nf_sh_tt_11 0.045 0.011 4.218 0.000 0.045 0.266
## t1_inf_sha_beh_f ~~
## t2_inf_sh_bh_f 0.072 0.008 8.496 0.000 0.635 0.635
## t3_inf_sh_bh_f 0.068 0.008 8.474 0.000 0.625 0.625
## t2_inf_sha_beh_f ~~
## t3_inf_sh_bh_f 0.068 0.008 8.501 0.000 0.645 0.645
## .t1_inf_sha_beh_01 ~~
## .t2_nf_sh_bh_01 0.335 0.028 12.002 0.000 0.335 0.482
## .t3_nf_sh_bh_01 0.301 0.027 11.039 0.000 0.301 0.465
## .t2_inf_sha_beh_01 ~~
## .t3_nf_sh_bh_01 0.362 0.028 12.926 0.000 0.362 0.503
## .t1_inf_sha_beh_02 ~~
## .t2_nf_sh_bh_02 0.052 0.007 7.332 0.000 0.052 0.217
## .t3_nf_sh_bh_02 0.049 0.007 6.703 0.000 0.049 0.198
## .t2_inf_sha_beh_02 ~~
## .t3_nf_sh_bh_02 0.056 0.006 8.944 0.000 0.056 0.269
## .t1_inf_sha_beh_03 ~~
## .t2_nf_sh_bh_03 0.022 0.004 5.260 0.000 0.022 0.276
## .t3_nf_sh_bh_03 0.028 0.004 7.164 0.000 0.028 0.404
## .t2_inf_sha_beh_03 ~~
## .t3_nf_sh_bh_03 0.036 0.004 8.666 0.000 0.036 0.521
## .t1_inf_sha_beh_04 ~~
## .t2_nf_sh_bh_04 0.035 0.004 7.812 0.000 0.035 0.386
## .t3_nf_sh_bh_04 0.025 0.004 6.033 0.000 0.025 0.290
## .t2_inf_sha_beh_04 ~~
## .t3_nf_sh_bh_04 0.047 0.005 9.691 0.000 0.047 0.462
## .t1_inf_sha_beh_05 ~~
## .t2_nf_sh_bh_05 0.013 0.004 2.898 0.004 0.013 0.224
## .t3_nf_sh_bh_05 0.018 0.004 4.567 0.000 0.018 0.353
## .t2_inf_sha_beh_05 ~~
## .t3_nf_sh_bh_05 0.010 0.004 2.446 0.014 0.010 0.180
## .t1_inf_sha_beh_06 ~~
## .t2_nf_sh_bh_06 0.068 0.006 11.042 0.000 0.068 0.417
## .t3_nf_sh_bh_06 0.053 0.006 9.326 0.000 0.053 0.338
## .t2_inf_sha_beh_06 ~~
## .t3_nf_sh_bh_06 0.064 0.006 10.982 0.000 0.064 0.406
## .t1_inf_sha_beh_07 ~~
## .t2_nf_sh_bh_07 0.130 0.011 11.534 0.000 0.130 0.432
## .t3_nf_sh_bh_07 0.095 0.011 8.326 0.000 0.095 0.305
## .t2_inf_sha_beh_07 ~~
## .t3_nf_sh_bh_07 0.097 0.012 8.235 0.000 0.097 0.312
## .t1_inf_sha_beh_08 ~~
## .t2_nf_sh_bh_08 0.165 0.015 11.268 0.000 0.165 0.351
## .t3_nf_sh_bh_08 0.129 0.014 9.277 0.000 0.129 0.290
## .t2_inf_sha_beh_08 ~~
## .t3_nf_sh_bh_08 0.151 0.014 10.575 0.000 0.151 0.338
## .t1_inf_sha_beh_10 ~~
## .t2_nf_sh_bh_10 0.019 0.009 2.001 0.045 0.019 0.192
## .t3_nf_sh_bh_10 0.030 0.009 3.350 0.001 0.030 0.329
## .t2_inf_sha_beh_10 ~~
## .t3_nf_sh_bh_10 0.053 0.009 6.220 0.000 0.053 0.662
## .t1_inf_sha_beh_11 ~~
## .t2_nf_sh_bh_11 0.066 0.009 7.546 0.000 0.066 0.306
## .t3_nf_sh_bh_11 0.041 0.008 4.985 0.000 0.041 0.210
## .t2_inf_sha_beh_11 ~~
## .t3_nf_sh_bh_11 0.034 0.008 4.131 0.000 0.034 0.174
## .t1_inf_sha_att_01 ~~
## .t1_nf_sh_bh_01 0.163 0.024 6.782 0.000 0.163 0.262
## .t1_inf_sha_att_02 ~~
## .t1_nf_sh_bh_02 0.062 0.014 4.593 0.000 0.062 0.135
## .t1_inf_sha_att_03 ~~
## .t1_nf_sh_bh_03 0.018 0.005 3.431 0.001 0.018 0.153
## .t1_inf_sha_att_04 ~~
## .t1_nf_sh_bh_04 0.027 0.005 5.004 0.000 0.027 0.213
## .t1_inf_sha_att_05 ~~
## .t1_nf_sh_bh_05 0.008 0.005 1.557 0.119 0.008 0.102
## .t1_inf_sha_att_06 ~~
## .t1_nf_sh_bh_06 0.033 0.006 5.065 0.000 0.033 0.160
## .t1_inf_sha_att_07 ~~
## .t1_nf_sh_bh_07 0.071 0.012 5.790 0.000 0.071 0.180
## .t1_inf_sha_att_08 ~~
## .t1_nf_sh_bh_08 0.109 0.015 7.318 0.000 0.109 0.209
## .t1_inf_sha_att_10 ~~
## .t1_nf_sh_bh_10 0.003 0.010 0.267 0.789 0.003 0.021
## .t1_inf_sha_att_11 ~~
## .t1_nf_sh_bh_11 0.040 0.009 4.197 0.000 0.040 0.207
## .t2_inf_sha_att_01 ~~
## .t2_nf_sh_bh_01 0.163 0.024 6.708 0.000 0.163 0.219
## .t2_inf_sha_att_02 ~~
## .t2_nf_sh_bh_02 0.063 0.011 5.644 0.000 0.063 0.163
## .t2_inf_sha_att_03 ~~
## .t2_nf_sh_bh_03 0.032 0.005 6.112 0.000 0.032 0.264
## .t2_inf_sha_att_04 ~~
## .t2_nf_sh_bh_04 0.026 0.006 4.403 0.000 0.026 0.162
## .t2_inf_sha_att_05 ~~
## .t2_nf_sh_bh_05 0.020 0.005 3.643 0.000 0.020 0.225
## .t2_inf_sha_att_06 ~~
## .t2_nf_sh_bh_06 0.031 0.007 4.667 0.000 0.031 0.143
## .t2_inf_sha_att_07 ~~
## .t2_nf_sh_bh_07 0.076 0.012 6.141 0.000 0.076 0.187
## .t2_inf_sha_att_08 ~~
## .t2_nf_sh_bh_08 0.117 0.015 7.573 0.000 0.117 0.217
## .t2_inf_sha_att_10 ~~
## .t2_nf_sh_bh_10 0.020 0.009 2.188 0.029 0.020 0.205
## .t2_inf_sha_att_11 ~~
## .t2_nf_sh_bh_11 0.011 0.009 1.163 0.245 0.011 0.056
## .t3_inf_sha_att_01 ~~
## .t3_nf_sh_bh_01 0.168 0.024 6.949 0.000 0.168 0.242
## .t3_inf_sha_att_02 ~~
## .t3_nf_sh_bh_02 0.068 0.011 5.940 0.000 0.068 0.174
## .t3_inf_sha_att_03 ~~
## .t3_nf_sh_bh_03 0.020 0.005 4.326 0.000 0.020 0.214
## .t3_inf_sha_att_04 ~~
## .t3_nf_sh_bh_04 0.032 0.006 5.720 0.000 0.032 0.215
## .t3_inf_sha_att_05 ~~
## .t3_nf_sh_bh_05 0.024 0.005 4.627 0.000 0.024 0.282
## .t3_inf_sha_att_06 ~~
## .t3_nf_sh_bh_06 0.035 0.006 5.457 0.000 0.035 0.173
## .t3_inf_sha_att_07 ~~
## .t3_nf_sh_bh_07 0.090 0.013 7.108 0.000 0.090 0.235
## .t3_inf_sha_att_08 ~~
## .t3_nf_sh_bh_08 0.115 0.015 7.931 0.000 0.115 0.236
## .t3_inf_sha_att_10 ~~
## .t3_nf_sh_bh_10 0.026 0.009 2.870 0.004 0.026 0.277
## .t3_inf_sha_att_11 ~~
## .t3_nf_sh_bh_11 -0.003 0.009 -0.299 0.765 -0.003 -0.015
## t1_pri_con_f ~~
## t1_inf_sh_tt_f -0.051 0.009 -5.953 0.000 -0.196 -0.196
## t2_inf_sh_tt_f -0.056 0.009 -6.342 0.000 -0.211 -0.211
## t3_inf_sh_tt_f -0.044 0.008 -5.376 0.000 -0.175 -0.175
## t1_inf_sh_bh_f -0.031 0.008 -3.728 0.000 -0.114 -0.114
## t2_inf_sh_bh_f -0.021 0.008 -2.682 0.007 -0.081 -0.081
## t3_inf_sh_bh_f -0.017 0.008 -2.241 0.025 -0.068 -0.068
## t2_pri_con_f ~~
## t1_inf_sh_tt_f -0.049 0.009 -5.616 0.000 -0.181 -0.181
## t2_inf_sh_tt_f -0.058 0.009 -6.464 0.000 -0.213 -0.213
## t3_inf_sh_tt_f -0.046 0.008 -5.447 0.000 -0.175 -0.175
## t1_inf_sh_bh_f -0.029 0.008 -3.407 0.001 -0.102 -0.102
## t2_inf_sh_bh_f -0.022 0.008 -2.680 0.007 -0.080 -0.080
## t3_inf_sh_bh_f -0.019 0.008 -2.379 0.017 -0.071 -0.071
## t3_pri_con_f ~~
## t1_inf_sh_tt_f -0.046 0.009 -5.347 0.000 -0.170 -0.170
## t2_inf_sh_tt_f -0.055 0.009 -6.172 0.000 -0.201 -0.201
## t3_inf_sh_tt_f -0.045 0.008 -5.419 0.000 -0.173 -0.173
## t1_inf_sh_bh_f -0.028 0.008 -3.354 0.001 -0.100 -0.100
## t2_inf_sh_bh_f -0.026 0.008 -3.177 0.001 -0.095 -0.095
## t3_inf_sh_bh_f -0.018 0.008 -2.365 0.018 -0.070 -0.070
## t1_inf_sha_att_f ~~
## t1_inf_sh_bh_f 0.048 0.005 9.308 0.000 0.430 0.430
## t2_inf_sh_bh_f 0.037 0.004 8.408 0.000 0.342 0.342
## t3_inf_sh_bh_f 0.041 0.005 8.923 0.000 0.389 0.389
## t2_inf_sha_att_f ~~
## t1_inf_sh_bh_f 0.043 0.005 8.870 0.000 0.383 0.383
## t2_inf_sh_bh_f 0.047 0.005 9.319 0.000 0.432 0.432
## t3_inf_sh_bh_f 0.044 0.005 9.198 0.000 0.418 0.418
## t3_inf_sha_att_f ~~
## t1_inf_sh_bh_f 0.042 0.005 8.878 0.000 0.386 0.386
## t2_inf_sh_bh_f 0.046 0.005 9.329 0.000 0.434 0.434
## t3_inf_sh_bh_f 0.053 0.005 9.945 0.000 0.524 0.524
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 3.745 0.029 130.880 0.000 3.745 3.499
## .t1_pri_con_05 3.842 0.034 111.483 0.000 3.842 2.990
## .t1_pri_con_06 3.314 0.032 105.108 0.000 3.314 2.810
## .t1_pri_con_07 3.623 0.033 109.196 0.000 3.623 2.919
## .t1_pri_con_08 3.624 0.031 115.840 0.000 3.624 3.097
## .t1_pri_con_09 4.095 0.028 145.553 0.000 4.095 3.892
## .t2_pri_con_04 3.675 0.028 129.336 0.000 3.675 3.458
## .t2_pri_con_05 3.784 0.035 109.357 0.000 3.784 2.931
## .t2_pri_con_06 3.258 0.031 104.665 0.000 3.258 2.799
## .t2_pri_con_07 3.556 0.033 107.462 0.000 3.556 2.873
## .t2_pri_con_08 3.551 0.032 112.597 0.000 3.551 3.010
## .t2_pri_con_09 3.994 0.029 139.686 0.000 3.994 3.733
## .t3_pri_con_04 3.664 0.028 129.793 0.000 3.664 3.471
## .t3_pri_con_05 3.709 0.035 106.540 0.000 3.709 2.857
## .t3_pri_con_06 3.256 0.031 106.187 0.000 3.256 2.839
## .t3_pri_con_07 3.492 0.033 105.643 0.000 3.492 2.825
## .t3_pri_con_08 3.560 0.031 114.265 0.000 3.560 3.056
## .t3_pri_con_09 3.959 0.029 137.482 0.000 3.959 3.677
## .t1_nf_sh_tt_01 1.704 0.029 57.766 0.000 1.704 1.543
## .t1_nf_sh_tt_02 1.900 0.029 65.212 0.000 1.900 1.744
## .t1_nf_sh_tt_03 2.788 0.029 95.482 0.000 2.788 2.551
## .t1_nf_sh_tt_04 2.940 0.028 103.429 0.000 2.940 2.763
## .t1_nf_sh_tt_05 2.626 0.029 91.849 0.000 2.626 2.454
## .t1_nf_sh_tt_06 2.373 0.029 82.165 0.000 2.373 2.196
## .t1_nf_sh_tt_07 3.011 0.029 103.365 0.000 3.011 2.762
## .t1_nf_sh_tt_08 2.293 0.028 81.475 0.000 2.293 2.177
## .t1_nf_sh_tt_10 2.249 0.029 78.845 0.000 2.249 2.108
## .t1_nf_sh_tt_11 2.295 0.028 81.531 0.000 2.295 2.179
## .t2_nf_sh_tt_01 1.764 0.030 58.870 0.000 1.764 1.576
## .t2_nf_sh_tt_02 1.932 0.029 67.096 0.000 1.932 1.797
## .t2_nf_sh_tt_03 2.903 0.029 99.573 0.000 2.903 2.664
## .t2_nf_sh_tt_04 2.998 0.029 104.623 0.000 2.998 2.800
## .t2_nf_sh_tt_05 2.710 0.028 95.895 0.000 2.710 2.566
## .t2_nf_sh_tt_06 2.428 0.029 83.576 0.000 2.428 2.237
## .t2_nf_sh_tt_07 3.119 0.029 107.636 0.000 3.119 2.882
## .t2_nf_sh_tt_08 2.332 0.028 82.737 0.000 2.332 2.215
## .t2_nf_sh_tt_10 2.271 0.028 81.149 0.000 2.271 2.175
## .t2_nf_sh_tt_11 2.363 0.028 83.963 0.000 2.363 2.251
## .t3_nf_sh_tt_01 1.777 0.030 59.910 0.000 1.777 1.600
## .t3_nf_sh_tt_02 1.887 0.028 67.626 0.000 1.887 1.806
## .t3_nf_sh_tt_03 2.951 0.028 103.577 0.000 2.951 2.765
## .t3_nf_sh_tt_04 3.057 0.028 107.956 0.000 3.057 2.882
## .t3_nf_sh_tt_05 2.737 0.028 97.466 0.000 2.737 2.603
## .t3_nf_sh_tt_06 2.473 0.028 87.188 0.000 2.473 2.328
## .t3_nf_sh_tt_07 3.103 0.028 112.660 0.000 3.103 3.010
## .t3_nf_sh_tt_08 2.368 0.027 87.262 0.000 2.368 2.331
## .t3_nf_sh_tt_10 2.297 0.027 83.925 0.000 2.297 2.242
## .t3_nf_sh_tt_11 2.366 0.028 85.992 0.000 2.366 2.296
## .t1_nf_sh_bh_01 1.713 0.029 60.081 0.000 1.713 1.605
## .t1_nf_sh_bh_02 1.244 0.015 80.287 0.000 1.244 2.145
## .t1_nf_sh_bh_03 2.672 0.028 94.720 0.000 2.672 2.529
## .t1_nf_sh_bh_04 2.725 0.028 96.795 0.000 2.725 2.584
## .t1_nf_sh_bh_05 2.545 0.026 96.688 0.000 2.545 2.582
## .t1_nf_sh_bh_06 2.431 0.026 93.869 0.000 2.431 2.507
## .t1_nf_sh_bh_07 2.878 0.028 102.195 0.000 2.878 2.729
## .t1_nf_sh_bh_08 2.194 0.025 86.140 0.000 2.194 2.302
## .t1_nf_sh_bh_10 1.793 0.024 75.653 0.000 1.793 2.022
## .t1_nf_sh_bh_11 1.739 0.022 78.954 0.000 1.739 2.110
## .t2_nf_sh_bh_01 1.713 0.028 61.277 0.000 1.713 1.639
## .t2_nf_sh_bh_02 1.214 0.013 94.409 0.000 1.214 2.522
## .t2_nf_sh_bh_03 2.681 0.027 97.837 0.000 2.681 2.613
## .t2_nf_sh_bh_04 2.764 0.028 99.692 0.000 2.764 2.663
## .t2_nf_sh_bh_05 2.558 0.026 97.672 0.000 2.558 2.609
## .t2_nf_sh_bh_06 2.434 0.026 94.964 0.000 2.434 2.537
## .t2_nf_sh_bh_07 2.923 0.028 105.145 0.000 2.923 2.808
## .t2_nf_sh_bh_08 2.239 0.025 88.523 0.000 2.239 2.365
## .t2_nf_sh_bh_10 1.805 0.023 79.856 0.000 1.805 2.134
## .t2_nf_sh_bh_11 1.734 0.021 80.702 0.000 1.734 2.156
## .t3_nf_sh_bh_01 1.702 0.028 61.391 0.000 1.702 1.639
## .t3_nf_sh_bh_02 1.226 0.013 91.181 0.000 1.226 2.436
## .t3_nf_sh_bh_03 2.627 0.026 99.684 0.000 2.627 2.661
## .t3_nf_sh_bh_04 2.692 0.027 100.443 0.000 2.692 2.682
## .t3_nf_sh_bh_05 2.509 0.025 101.643 0.000 2.509 2.714
## .t3_nf_sh_bh_06 2.395 0.024 98.409 0.000 2.395 2.628
## .t3_nf_sh_bh_07 2.865 0.027 104.202 0.000 2.865 2.783
## .t3_nf_sh_bh_08 2.178 0.024 89.471 0.000 2.178 2.392
## .t3_nf_sh_bh_10 1.776 0.023 78.319 0.000 1.776 2.092
## .t3_nf_sh_bh_11 1.715 0.021 81.704 0.000 1.715 2.183
## t1_pri_con_f 0.000 0.000 0.000
## t2_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
## .t1_pri_con_f1 0.000 0.000 0.000
## .t1_pri_con_f2 0.000 0.000 0.000
## .t2_pri_con_f1 0.000 0.000 0.000
## .t2_pri_con_f2 0.000 0.000 0.000
## .t3_pri_con_f1 0.000 0.000 0.000
## .t3_pri_con_f2 0.000 0.000 0.000
## t1_inf_sh_tt_f 0.000 0.000 0.000
## t2_inf_sh_tt_f 0.000 0.000 0.000
## t3_inf_sh_tt_f 0.000 0.000 0.000
## .t1_nf_sh_tt_f1 0.000 0.000 0.000
## .t1_nf_sh_tt_f2 0.000 0.000 0.000
## .t1_nf_sh_tt_f3 0.000 0.000 0.000
## .t1_nf_sh_tt_f4 0.000 0.000 0.000
## .t1_nf_sh_tt_f5 0.000 0.000 0.000
## .t2_nf_sh_tt_f1 0.000 0.000 0.000
## .t2_nf_sh_tt_f2 0.000 0.000 0.000
## .t2_nf_sh_tt_f3 0.000 0.000 0.000
## .t2_nf_sh_tt_f4 0.000 0.000 0.000
## .t2_nf_sh_tt_f5 0.000 0.000 0.000
## .t3_nf_sh_tt_f1 0.000 0.000 0.000
## .t3_nf_sh_tt_f2 0.000 0.000 0.000
## .t3_nf_sh_tt_f3 0.000 0.000 0.000
## .t3_nf_sh_tt_f4 0.000 0.000 0.000
## .t3_nf_sh_tt_f5 0.000 0.000 0.000
## t1_inf_sh_bh_f 0.000 0.000 0.000
## t2_inf_sh_bh_f 0.000 0.000 0.000
## t3_inf_sh_bh_f 0.000 0.000 0.000
## .t1_nf_sh_bh_f1 0.000 0.000 0.000
## .t1_nf_sh_bh_f2 0.000 0.000 0.000
## .t1_nf_sh_bh_f3 0.000 0.000 0.000
## .t1_nf_sh_bh_f4 0.000 0.000 0.000
## .t1_nf_sh_bh_f5 0.000 0.000 0.000
## .t2_nf_sh_bh_f1 0.000 0.000 0.000
## .t2_nf_sh_bh_f2 0.000 0.000 0.000
## .t2_nf_sh_bh_f3 0.000 0.000 0.000
## .t2_nf_sh_bh_f4 0.000 0.000 0.000
## .t2_nf_sh_bh_f5 0.000 0.000 0.000
## .t3_nf_sh_bh_f1 0.000 0.000 0.000
## .t3_nf_sh_bh_f2 0.000 0.000 0.000
## .t3_nf_sh_bh_f3 0.000 0.000 0.000
## .t3_nf_sh_bh_f4 0.000 0.000 0.000
## .t3_nf_sh_bh_f5 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 0.430 0.022 19.770 0.000 0.430 0.375
## .t1_pri_con_05 0.901 0.040 22.795 0.000 0.901 0.545
## .t1_pri_con_06 0.546 0.027 20.394 0.000 0.546 0.393
## .t1_pri_con_07 0.514 0.025 20.296 0.000 0.514 0.334
## .t1_pri_con_08 0.400 0.021 19.068 0.000 0.400 0.292
## .t1_pri_con_09 0.350 0.018 19.974 0.000 0.350 0.316
## .t2_pri_con_04 0.411 0.020 20.148 0.000 0.411 0.364
## .t2_pri_con_05 0.913 0.039 23.245 0.000 0.913 0.548
## .t2_pri_con_06 0.507 0.025 20.546 0.000 0.507 0.374
## .t2_pri_con_07 0.454 0.023 19.893 0.000 0.454 0.296
## .t2_pri_con_08 0.373 0.020 18.952 0.000 0.373 0.268
## .t2_pri_con_09 0.349 0.017 19.964 0.000 0.349 0.304
## .t3_pri_con_04 0.418 0.020 20.636 0.000 0.418 0.375
## .t3_pri_con_05 0.955 0.040 23.584 0.000 0.955 0.566
## .t3_pri_con_06 0.493 0.024 20.725 0.000 0.493 0.375
## .t3_pri_con_07 0.443 0.022 20.068 0.000 0.443 0.290
## .t3_pri_con_08 0.333 0.018 18.495 0.000 0.333 0.245
## .t3_pri_con_09 0.358 0.017 20.651 0.000 0.358 0.309
## .t1_nf_sh_tt_01 0.624 0.051 12.213 0.000 0.624 0.512
## .t1_nf_sh_tt_02 0.738 0.044 16.630 0.000 0.738 0.621
## .t1_nf_sh_tt_03 0.182 0.012 15.173 0.000 0.182 0.153
## .t1_nf_sh_tt_04 0.213 0.012 17.894 0.000 0.213 0.188
## .t1_nf_sh_tt_05 0.125 0.011 11.317 0.000 0.125 0.109
## .t1_nf_sh_tt_06 0.262 0.013 19.759 0.000 0.262 0.225
## .t1_nf_sh_tt_07 0.517 0.028 18.710 0.000 0.517 0.435
## .t1_nf_sh_tt_08 0.586 0.027 21.919 0.000 0.586 0.528
## .t1_nf_sh_tt_10 0.153 0.021 7.153 0.000 0.153 0.135
## .t1_nf_sh_tt_11 0.170 0.020 8.287 0.000 0.170 0.153
## .t2_nf_sh_tt_01 0.714 0.050 14.152 0.000 0.714 0.570
## .t2_nf_sh_tt_02 0.747 0.043 17.371 0.000 0.747 0.647
## .t2_nf_sh_tt_03 0.182 0.012 15.418 0.000 0.182 0.153
## .t2_nf_sh_tt_04 0.233 0.012 18.968 0.000 0.233 0.203
## .t2_nf_sh_tt_05 0.118 0.011 11.088 0.000 0.118 0.105
## .t2_nf_sh_tt_06 0.293 0.014 21.050 0.000 0.293 0.249
## .t2_nf_sh_tt_07 0.545 0.028 19.475 0.000 0.545 0.465
## .t2_nf_sh_tt_08 0.620 0.027 22.644 0.000 0.620 0.559
## .t2_nf_sh_tt_10 0.110 0.020 5.380 0.000 0.110 0.101
## .t2_nf_sh_tt_11 0.168 0.020 8.371 0.000 0.168 0.152
## .t3_nf_sh_tt_01 0.718 0.050 14.480 0.000 0.718 0.582
## .t3_nf_sh_tt_02 0.701 0.041 16.920 0.000 0.701 0.642
## .t3_nf_sh_tt_03 0.147 0.011 13.033 0.000 0.147 0.129
## .t3_nf_sh_tt_04 0.224 0.012 18.648 0.000 0.224 0.199
## .t3_nf_sh_tt_05 0.138 0.012 11.909 0.000 0.138 0.125
## .t3_nf_sh_tt_06 0.270 0.014 19.992 0.000 0.270 0.239
## .t3_nf_sh_tt_07 0.460 0.025 18.526 0.000 0.460 0.433
## .t3_nf_sh_tt_08 0.561 0.025 22.763 0.000 0.561 0.544
## .t3_nf_sh_tt_10 0.114 0.021 5.561 0.000 0.114 0.109
## .t3_nf_sh_tt_11 0.170 0.020 8.523 0.000 0.170 0.160
## .t1_nf_sh_bh_01 0.624 0.065 9.627 0.000 0.624 0.548
## .t1_nf_sh_bh_02 0.288 0.012 23.729 0.000 0.288 0.857
## .t1_nf_sh_bh_03 0.078 0.005 14.195 0.000 0.078 0.070
## .t1_nf_sh_bh_04 0.077 0.005 14.119 0.000 0.077 0.069
## .t1_nf_sh_bh_05 0.050 0.006 8.109 0.000 0.050 0.051
## .t1_nf_sh_bh_06 0.161 0.008 21.073 0.000 0.161 0.172
## .t1_nf_sh_bh_07 0.301 0.018 16.441 0.000 0.301 0.271
## .t1_nf_sh_bh_08 0.467 0.019 24.317 0.000 0.467 0.514
## .t1_nf_sh_bh_10 0.111 0.019 5.983 0.000 0.111 0.142
## .t1_nf_sh_bh_11 0.217 0.015 14.462 0.000 0.217 0.319
## .t2_nf_sh_bh_01 0.775 0.052 14.926 0.000 0.775 0.709
## .t2_nf_sh_bh_02 0.202 0.008 23.892 0.000 0.202 0.872
## .t2_nf_sh_bh_03 0.081 0.006 13.342 0.000 0.081 0.077
## .t2_nf_sh_bh_04 0.108 0.007 16.252 0.000 0.108 0.100
## .t2_nf_sh_bh_05 0.064 0.007 9.284 0.000 0.064 0.067
## .t2_nf_sh_bh_06 0.162 0.008 19.952 0.000 0.162 0.176
## .t2_nf_sh_bh_07 0.302 0.019 15.925 0.000 0.302 0.279
## .t2_nf_sh_bh_08 0.471 0.019 24.494 0.000 0.471 0.525
## .t2_nf_sh_bh_10 0.085 0.017 4.887 0.000 0.085 0.119
## .t2_nf_sh_bh_11 0.216 0.014 15.481 0.000 0.216 0.333
## .t3_nf_sh_bh_01 0.670 0.056 12.049 0.000 0.670 0.622
## .t3_nf_sh_bh_02 0.215 0.009 23.437 0.000 0.215 0.850
## .t3_nf_sh_bh_03 0.061 0.005 11.810 0.000 0.061 0.062
## .t3_nf_sh_bh_04 0.097 0.006 16.841 0.000 0.097 0.096
## .t3_nf_sh_bh_05 0.053 0.006 8.761 0.000 0.053 0.062
## .t3_nf_sh_bh_06 0.153 0.007 21.252 0.000 0.153 0.185
## .t3_nf_sh_bh_07 0.319 0.019 16.608 0.000 0.319 0.301
## .t3_nf_sh_bh_08 0.425 0.018 23.964 0.000 0.425 0.513
## .t3_nf_sh_bh_10 0.075 0.017 4.351 0.000 0.075 0.105
## .t3_nf_sh_bh_11 0.175 0.013 13.533 0.000 0.175 0.284
## t1_pri_con_f 0.636 0.035 18.264 0.000 1.000 1.000
## t2_pri_con_f 0.671 0.036 18.623 0.000 1.000 1.000
## t3_pri_con_f 0.678 0.036 18.806 0.000 1.000 1.000
## .t1_pri_con_f1 0.079 0.014 5.532 0.000 0.111 0.111
## .t1_pri_con_f2 0.100 0.019 5.355 0.000 0.097 0.097
## .t2_pri_con_f1 0.048 0.013 3.673 0.000 0.066 0.066
## .t2_pri_con_f2 0.102 0.018 5.772 0.000 0.094 0.094
## .t3_pri_con_f1 0.019 0.012 1.535 0.125 0.027 0.027
## .t3_pri_con_f2 0.097 0.017 5.697 0.000 0.090 0.090
## t1_inf_sh_tt_f 0.109 0.013 8.314 0.000 1.000 1.000
## t2_inf_sh_tt_f 0.109 0.013 8.312 0.000 1.000 1.000
## t3_inf_sh_tt_f 0.101 0.012 8.299 0.000 1.000 1.000
## .t1_nf_sh_tt_f1 0.486 0.048 10.048 0.000 0.817 0.817
## .t1_nf_sh_tt_f2 0.085 0.013 6.479 0.000 0.084 0.084
## .t1_nf_sh_tt_f3 0.139 0.014 9.844 0.000 0.136 0.136
## .t1_nf_sh_tt_f4 0.147 0.020 7.480 0.000 0.219 0.219
## .t1_nf_sh_tt_f5 0.749 0.036 20.686 0.000 0.760 0.760
## .t2_nf_sh_tt_f1 0.430 0.045 9.571 0.000 0.797 0.797
## .t2_nf_sh_tt_f2 0.074 0.012 6.068 0.000 0.074 0.074
## .t2_nf_sh_tt_f3 0.112 0.013 8.607 0.000 0.112 0.112
## .t2_nf_sh_tt_f4 0.100 0.018 5.476 0.000 0.160 0.160
## .t2_nf_sh_tt_f5 0.743 0.036 20.918 0.000 0.758 0.758
## .t3_nf_sh_tt_f1 0.415 0.043 9.535 0.000 0.803 0.803
## .t3_nf_sh_tt_f2 0.125 0.014 9.091 0.000 0.126 0.126
## .t3_nf_sh_tt_f3 0.144 0.015 9.899 0.000 0.149 0.149
## .t3_nf_sh_tt_f4 0.114 0.017 6.556 0.000 0.189 0.189
## .t3_nf_sh_tt_f5 0.715 0.034 20.767 0.000 0.764 0.764
## t1_inf_sh_bh_f 0.117 0.013 8.887 0.000 1.000 1.000
## t2_inf_sh_bh_f 0.109 0.012 8.884 0.000 1.000 1.000
## t3_inf_sh_bh_f 0.101 0.011 8.882 0.000 1.000 1.000
## .t1_nf_sh_bh_f1 0.398 0.060 6.594 0.000 0.774 0.774
## .t1_nf_sh_bh_f2 0.080 0.008 9.594 0.000 0.077 0.077
## .t1_nf_sh_bh_f3 0.103 0.009 11.475 0.000 0.111 0.111
## .t1_nf_sh_bh_f4 0.050 0.015 3.403 0.001 0.061 0.061
## .t1_nf_sh_bh_f5 0.484 0.027 18.081 0.000 0.717 0.717
## .t2_nf_sh_bh_f1 0.209 0.042 5.013 0.000 0.656 0.656
## .t2_nf_sh_bh_f2 0.074 0.009 8.583 0.000 0.076 0.076
## .t2_nf_sh_bh_f3 0.129 0.010 12.935 0.000 0.144 0.144
## .t2_nf_sh_bh_f4 0.068 0.015 4.534 0.000 0.087 0.087
## .t2_nf_sh_bh_f5 0.451 0.025 18.029 0.000 0.716 0.716
## .t3_nf_sh_bh_f1 0.306 0.049 6.278 0.000 0.752 0.752
## .t3_nf_sh_bh_f2 0.082 0.008 10.243 0.000 0.090 0.090
## .t3_nf_sh_bh_f3 0.091 0.008 10.813 0.000 0.113 0.113
## .t3_nf_sh_bh_f4 0.080 0.015 5.223 0.000 0.108 0.108
## .t3_nf_sh_bh_f5 0.480 0.026 18.753 0.000 0.743 0.7432 Results
In what follows, we report additional models, which are also related to our research question.
2.1 RI-CLPM
2.1.1 Two Variables
Here, we look at the bivariate relations of privacy concerns and information sharing. This is interesting, because in the paper we also address privacy attitudes, thereby potentially attenuating the effect of privacy concerns. However, when analyzing only these two variables we do not find larger effects sizes.
2.1.1.1 Model 1
Here, we use regular observed means.
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_m + 1*t2_pri_con_m + 1*t3_pri_con_m
inf_sha_beh_b =~ 1*t1_inf_sha_beh_m + 1*t2_inf_sha_beh_m + 1*t3_inf_sha_beh_m
# intercepts
t1_pri_con_m ~ mu1*1
t2_pri_con_m ~ mu2*1
t3_pri_con_m ~ mu3*1
t1_inf_sha_beh_m ~ pi1*1
t2_inf_sha_beh_m ~ pi2*1
t3_inf_sha_beh_m ~ pi3*1
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_m
t2_pri_con_w =~ 1*t2_pri_con_m
t3_pri_con_w =~ 1*t3_pri_con_m
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_m
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_m
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_m
# estimate variances
pri_con_b ~~ pri_con_b
inf_sha_beh_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_pri_con_w
t2_pri_con_w ~~ t2_pri_con_w
t3_pri_con_w ~~ t3_pri_con_w
t1_inf_sha_beh_w ~~ t1_inf_sha_beh_w
t2_inf_sha_beh_w ~~ t2_inf_sha_beh_w
t3_inf_sha_beh_w ~~ t3_inf_sha_beh_w
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_beh_w
'
fit <- lavaan(model, data = d_wide, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 42 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 26
## Number of equality constraints 5
##
## Number of observations 1403
## Number of missing patterns 4
##
## Model Test User Model:
##
## Test statistic 3.780
## Degrees of freedom 6
## P-value (Chi-square) 0.706
##
## Model Test Baseline Model:
##
## Test statistic 4114.935
## Degrees of freedom 15
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.001
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -7478.685
## Loglikelihood unrestricted model (H1) -7476.795
##
## Akaike (AIC) 14999.371
## Bayesian (BIC) 15109.545
## Sample-size adjusted Bayesian (BIC) 15042.835
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.026
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.010
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b =~
## t1_pri_con_m 1.000 0.758 0.856
## t2_pri_con_m 1.000 0.758 0.850
## t3_pri_con_m 1.000 0.758 0.850
## inf_sha_beh_b =~
## t1_inf_sh_bh_m 1.000 0.495 0.757
## t2_inf_sh_bh_m 1.000 0.495 0.771
## t3_inf_sh_bh_m 1.000 0.495 0.803
## t1_pri_con_w =~
## t1_pri_con_m 1.000 0.458 0.517
## t2_pri_con_w =~
## t2_pri_con_m 1.000 0.471 0.527
## t3_pri_con_w =~
## t3_pri_con_m 1.000 0.469 0.526
## t1_inf_sha_beh_w =~
## t1_inf_sh_bh_m 1.000 0.428 0.654
## t2_inf_sha_beh_w =~
## t2_inf_sh_bh_m 1.000 0.408 0.636
## t3_inf_sha_beh_w =~
## t3_inf_sh_bh_m 1.000 0.367 0.596
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.087 0.071 1.225 0.220 0.084 0.084
## t1_nf_s__ (a2) 0.013 0.038 0.333 0.739 0.011 0.011
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (b1) 0.035 0.029 1.196 0.232 0.039 0.039
## t1_nf_s__ (b2) 0.042 0.046 0.903 0.367 0.044 0.044
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.087 0.071 1.225 0.220 0.087 0.087
## t2_nf_s__ (a2) 0.013 0.038 0.333 0.739 0.011 0.011
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (b1) 0.035 0.029 1.196 0.232 0.045 0.045
## t2_nf_s__ (b2) 0.042 0.046 0.903 0.367 0.046 0.046
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b ~~
## inf_sh_bh_ -0.068 0.013 -5.346 0.000 -0.182 -0.182
## t1_pri_con_w ~~
## t1_nf_sh__ -0.011 0.008 -1.457 0.145 -0.058 -0.058
## .t2_pri_con_w ~~
## .t2_nf_sh__ (a) 0.006 0.007 0.963 0.336 0.033 0.033
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) 0.006 0.007 0.963 0.336 0.037 0.037
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pr_c_ (mu1) 3.671 0.024 155.157 0.000 3.671 4.146
## .t2_pr_c_ (mu2) 3.617 0.024 151.750 0.000 3.617 4.053
## .t3_pr_c_ (mu3) 3.589 0.024 150.625 0.000 3.589 4.026
## .t1_nf___ (pi1) 2.122 0.017 121.474 0.000 2.122 3.243
## .t2_nf___ (pi2) 2.135 0.017 124.561 0.000 2.135 3.325
## .t3_nf___ (pi3) 2.101 0.016 127.588 0.000 2.101 3.406
## pri_cn_b 0.000 0.000 0.000
## inf_sh__ 0.000 0.000 0.000
## t1_pr_c_ 0.000 0.000 0.000
## .t2_pr_c_ 0.000 0.000 0.000
## .t3_pr_c_ 0.000 0.000 0.000
## t1_nf___ 0.000 0.000 0.000
## .t2_nf___ 0.000 0.000 0.000
## .t3_nf___ 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b 0.575 0.027 21.060 0.000 1.000 1.000
## inf_sha_beh_b 0.245 0.013 19.278 0.000 1.000 1.000
## t1_pri_con_w 0.209 0.013 16.655 0.000 1.000 1.000
## .t2_pri_con_w 0.220 0.026 8.386 0.000 0.993 0.993
## .t3_pri_con_w 0.218 0.013 17.469 0.000 0.992 0.992
## t1_inf_sh_bh_w 0.183 0.010 18.744 0.000 1.000 1.000
## .t2_inf_sh_bh_w 0.166 0.014 11.927 0.000 0.997 0.997
## .t3_inf_sh_bh_w 0.134 0.008 17.035 0.000 0.996 0.996
## .t1_pri_con_m 0.000 0.000 0.000
## .t2_pri_con_m 0.000 0.000 0.000
## .t3_pri_con_m 0.000 0.000 0.000
## .t1_inf_sh_bh_m 0.000 0.000 0.000
## .t2_inf_sh_bh_m 0.000 0.000 0.000
## .t3_inf_sh_bh_m 0.000 0.000 0.0002.1.1.2 Model 2
Model with a (broad) single item measure of privacy concerns (“In general, how concerned are you about your privacy while using the Internet?”).
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_01 + 1*t2_pri_con_01 + 1*t3_pri_con_01
inf_sha_beh_b =~ 1*t1_inf_sha_beh_m + 1*t2_inf_sha_beh_m + 1*t3_inf_sha_beh_m
# intercepts
t1_pri_con_01 ~ mu1*1
t2_pri_con_01 ~ mu2*1
t3_pri_con_01 ~ mu3*1
t1_inf_sha_beh_m ~ pi1*1
t2_inf_sha_beh_m ~ pi2*1
t3_inf_sha_beh_m ~ pi3*1
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_01
t2_pri_con_w =~ 1*t2_pri_con_01
t3_pri_con_w =~ 1*t3_pri_con_01
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_m
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_m
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_m
# estimate variances
pri_con_b ~~ pri_con_b
inf_sha_beh_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_pri_con_w
t2_pri_con_w ~~ t2_pri_con_w
t3_pri_con_w ~~ t3_pri_con_w
t1_inf_sha_beh_w ~~ t1_inf_sha_beh_w
t2_inf_sha_beh_w ~~ t2_inf_sha_beh_w
t3_inf_sha_beh_w ~~ t3_inf_sha_beh_w
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_beh_w
'
fit <- lavaan(model, data = d_wide, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 42 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 26
## Number of equality constraints 5
##
## Number of observations 1403
## Number of missing patterns 4
##
## Model Test User Model:
##
## Test statistic 1.834
## Degrees of freedom 6
## P-value (Chi-square) 0.934
##
## Model Test Baseline Model:
##
## Test statistic 2962.543
## Degrees of freedom 15
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.004
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -8913.859
## Loglikelihood unrestricted model (H1) -8912.942
##
## Akaike (AIC) 17869.717
## Bayesian (BIC) 17979.891
## Sample-size adjusted Bayesian (BIC) 17913.182
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.009
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.007
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b =~
## t1_pri_con_01 1.000 0.841 0.766
## t2_pri_con_01 1.000 0.841 0.784
## t3_pri_con_01 1.000 0.841 0.759
## inf_sha_beh_b =~
## t1_inf_sh_bh_m 1.000 0.495 0.756
## t2_inf_sh_bh_m 1.000 0.495 0.772
## t3_inf_sh_bh_m 1.000 0.495 0.804
## t1_pri_con_w =~
## t1_pri_con_01 1.000 0.706 0.643
## t2_pri_con_w =~
## t2_pri_con_01 1.000 0.666 0.621
## t3_pri_con_w =~
## t3_pri_con_01 1.000 0.721 0.651
## t1_inf_sha_beh_w =~
## t1_inf_sh_bh_m 1.000 0.429 0.654
## t2_inf_sha_beh_w =~
## t2_inf_sh_bh_m 1.000 0.408 0.636
## t3_inf_sha_beh_w =~
## t3_inf_sh_bh_m 1.000 0.366 0.595
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) -0.027 0.051 -0.530 0.596 -0.029 -0.029
## t1_nf_s__ (a2) -0.048 0.055 -0.881 0.378 -0.031 -0.031
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (b1) 0.010 0.018 0.528 0.598 0.017 0.017
## t1_nf_s__ (b2) 0.041 0.047 0.880 0.379 0.043 0.043
## t3_pri_con_w ~
## t2_pr_cn_ (a1) -0.027 0.051 -0.530 0.596 -0.025 -0.025
## t2_nf_s__ (a2) -0.048 0.055 -0.881 0.378 -0.027 -0.027
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (b1) 0.010 0.018 0.528 0.598 0.017 0.017
## t2_nf_s__ (b2) 0.041 0.047 0.880 0.379 0.046 0.046
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b ~~
## inf_sh_bh_ -0.046 0.015 -3.102 0.002 -0.110 -0.110
## t1_pri_con_w ~~
## t1_nf_sh__ -0.024 0.011 -2.128 0.033 -0.080 -0.080
## .t2_pri_con_w ~~
## .t2_nf_sh__ (a) -0.008 0.009 -0.889 0.374 -0.030 -0.030
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) -0.008 0.009 -0.889 0.374 -0.031 -0.031
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_p__01 (mu1) 3.335 0.029 113.605 0.000 3.335 3.037
## .t2_p__01 (mu2) 3.334 0.029 116.365 0.000 3.334 3.109
## .t3_p__01 (mu3) 3.337 0.030 112.652 0.000 3.337 3.012
## .t1_nf___ (pi1) 2.122 0.017 121.362 0.000 2.122 3.240
## .t2_nf___ (pi2) 2.135 0.017 124.611 0.000 2.135 3.327
## .t3_nf___ (pi3) 2.101 0.016 127.702 0.000 2.101 3.409
## pri_cn_b 0.000 0.000 0.000
## inf_sh__ 0.000 0.000 0.000
## t1_pr_c_ 0.000 0.000 0.000
## .t2_pr_c_ 0.000 0.000 0.000
## .t3_pr_c_ 0.000 0.000 0.000
## t1_nf___ 0.000 0.000 0.000
## .t2_nf___ 0.000 0.000 0.000
## .t3_nf___ 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b 0.707 0.037 19.173 0.000 1.000 1.000
## inf_sha_beh_b 0.245 0.013 19.261 0.000 1.000 1.000
## t1_pri_con_w 0.498 0.027 18.186 0.000 1.000 1.000
## .t2_pri_con_w 0.442 0.043 10.295 0.000 0.998 0.998
## .t3_pri_con_w 0.519 0.027 18.911 0.000 0.999 0.999
## t1_inf_sh_bh_w 0.184 0.010 18.734 0.000 1.000 1.000
## .t2_inf_sh_bh_w 0.166 0.014 11.855 0.000 0.998 0.998
## .t3_inf_sh_bh_w 0.134 0.008 16.993 0.000 0.998 0.998
## .t1_pri_con_01 0.000 0.000 0.000
## .t2_pri_con_01 0.000 0.000 0.000
## .t3_pri_con_01 0.000 0.000 0.000
## .t1_inf_sh_bh_m 0.000 0.000 0.000
## .t2_inf_sh_bh_m 0.000 0.000 0.000
## .t3_inf_sh_bh_m 0.000 0.000 0.0002.1.1.3 Model 3
With Factor Scores.
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_fs + 1*t2_pri_con_fs + 1*t3_pri_con_fs
inf_sha_beh_b =~ 1*t1_inf_sha_beh_fs + 1*t2_inf_sha_beh_fs + 1*t3_inf_sha_beh_fs
# intercepts
t1_pri_con_fs ~ 1
t2_pri_con_fs ~ 1
t3_pri_con_fs ~ 1
t1_inf_sha_beh_fs ~ 1
t2_inf_sha_beh_fs ~ 1
t3_inf_sha_beh_fs ~ 1
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_fs
t2_pri_con_w =~ 1*t2_pri_con_fs
t3_pri_con_w =~ 1*t3_pri_con_fs
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_fs
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_fs
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_fs
# estimate variances
pri_con_b ~~ pri_con_b
inf_sha_beh_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_pri_con_w
t2_pri_con_w ~~ t2_pri_con_w
t3_pri_con_w ~~ t3_pri_con_w
t1_inf_sha_beh_w ~~ t1_inf_sha_beh_w
t2_inf_sha_beh_w ~~ t2_inf_sha_beh_w
t3_inf_sha_beh_w ~~ t3_inf_sha_beh_w
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_beh_w
'
fit <- lavaan(model, data = d_wide)
summary(fit, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 48 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 26
## Number of equality constraints 5
##
## Number of observations 1403
##
## Model Test User Model:
##
## Test statistic 4.872
## Degrees of freedom 6
## P-value (Chi-square) 0.560
##
## Model Test Baseline Model:
##
## Test statistic 4626.337
## Degrees of freedom 15
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.001
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -7132.491
## Loglikelihood unrestricted model (H1) -7130.055
##
## Akaike (AIC) 14306.982
## Bayesian (BIC) 14417.156
## Sample-size adjusted Bayesian (BIC) 14350.446
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.031
## P-value RMSEA <= 0.05 0.999
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.011
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b =~
## t1_pri_con_fs 1.000 0.755 0.882
## t2_pri_con_fs 1.000 0.755 0.861
## t3_pri_con_fs 1.000 0.755 0.872
## inf_sha_beh_b =~
## t1_nf_sh_bh_fs 1.000 0.500 0.766
## t2_nf_sh_bh_fs 1.000 0.500 0.785
## t3_nf_sh_bh_fs 1.000 0.500 0.807
## t1_pri_con_w =~
## t1_pri_con_fs 1.000 0.403 0.471
## t2_pri_con_w =~
## t2_pri_con_fs 1.000 0.446 0.509
## t3_pri_con_w =~
## t3_pri_con_fs 1.000 0.424 0.490
## t1_inf_sha_beh_w =~
## t1_nf_sh_bh_fs 1.000 0.420 0.643
## t2_inf_sha_beh_w =~
## t2_nf_sh_bh_fs 1.000 0.395 0.620
## t3_inf_sha_beh_w =~
## t3_nf_sh_bh_fs 1.000 0.366 0.591
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.136 0.064 2.108 0.035 0.122 0.122
## t1_nf_s__ (a2) -0.022 0.035 -0.615 0.539 -0.020 -0.020
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (b1) 0.013 0.033 0.390 0.696 0.013 0.013
## t1_nf_s__ (b2) 0.028 0.050 0.564 0.573 0.030 0.030
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.136 0.064 2.108 0.035 0.143 0.143
## t2_nf_s__ (a2) -0.022 0.035 -0.615 0.539 -0.020 -0.020
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (b1) 0.013 0.033 0.390 0.696 0.015 0.015
## t2_nf_s__ (b2) 0.028 0.050 0.564 0.573 0.030 0.030
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b ~~
## inf_sh_bh_ -0.054 0.012 -4.330 0.000 -0.143 -0.143
## t1_pri_con_w ~~
## t1_nf_sh__ -0.016 0.007 -2.279 0.023 -0.094 -0.094
## .t2_pri_con_w ~~
## .t2_nf_sh__ (a) 0.007 0.006 1.100 0.271 0.037 0.037
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) 0.007 0.006 1.100 0.271 0.043 0.043
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_fs 3.707 0.023 162.274 0.000 3.707 4.332
## .t2_pri_con_fs 3.636 0.023 155.317 0.000 3.636 4.147
## .t3_pri_con_fs 3.607 0.023 156.023 0.000 3.607 4.165
## .t1_nf_sh_bh_fs 2.193 0.017 125.833 0.000 2.193 3.359
## .t2_nf_sh_bh_fs 2.206 0.017 129.597 0.000 2.206 3.460
## .t3_nf_sh_bh_fs 2.168 0.017 131.009 0.000 2.168 3.498
## pri_con_b 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000
## .t2_pri_con_w 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000
## .t2_inf_sh_bh_w 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b 0.570 0.026 22.266 0.000 1.000 1.000
## inf_sha_beh_b 0.250 0.013 19.509 0.000 1.000 1.000
## t1_pri_con_w 0.162 0.010 15.544 0.000 1.000 1.000
## .t2_pri_con_w 0.196 0.020 10.020 0.000 0.984 0.984
## .t3_pri_con_w 0.176 0.010 16.999 0.000 0.979 0.979
## t1_inf_sh_bh_w 0.176 0.009 18.803 0.000 1.000 1.000
## .t2_inf_sh_bh_w 0.156 0.014 10.841 0.000 0.999 0.999
## .t3_inf_sh_bh_w 0.134 0.008 17.221 0.000 0.999 0.999
## .t1_pri_con_fs 0.000 0.000 0.000
## .t2_pri_con_fs 0.000 0.000 0.000
## .t3_pri_con_fs 0.000 0.000 0.000
## .t1_nf_sh_bh_fs 0.000 0.000 0.000
## .t2_nf_sh_bh_fs 0.000 0.000 0.000
## .t3_nf_sh_bh_fs 0.000 0.000 0.0002.1.1.4 Model 4
With Factor Scores and Control Variables.
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_fs + 1*t2_pri_con_fs + 1*t3_pri_con_fs
inf_sha_beh_b =~ 1*t1_inf_sha_beh_fs + 1*t2_inf_sha_beh_fs + 1*t3_inf_sha_beh_fs
# intercepts
t1_pri_con_fs ~ 1
t2_pri_con_fs ~ 1
t3_pri_con_fs ~ 1
t1_inf_sha_beh_fs ~ 1
t2_inf_sha_beh_fs ~ 1
t3_inf_sha_beh_fs ~ 1
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_fs
t2_pri_con_w =~ 1*t2_pri_con_fs
t3_pri_con_w =~ 1*t3_pri_con_fs
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_fs
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_fs
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_fs
# estimate variances
pri_con_b ~~ pri_con_b
inf_sha_beh_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_pri_con_w
t2_pri_con_w ~~ t2_pri_con_w
t3_pri_con_w ~~ t3_pri_con_w
t1_inf_sha_beh_w ~~ t1_inf_sha_beh_w
t2_inf_sha_beh_w ~~ t2_inf_sha_beh_w
t3_inf_sha_beh_w ~~ t3_inf_sha_beh_w
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_beh_w
# control variables
t1_pri_con_fs ~ age + edu_num + male
t2_pri_con_fs ~ age + edu_num + male
t3_pri_con_fs ~ age + edu_num + male
t1_inf_sha_beh_fs ~ age + edu_num + male
t2_inf_sha_beh_fs ~ age + edu_num + male
t3_inf_sha_beh_fs ~ age + edu_num + male
'
fit <- lavaan(model, data = d_wide, missing = "ml")
summary(fit, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 113 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 44
## Number of equality constraints 5
##
## Number of observations 1403
## Number of missing patterns 1
##
## Model Test User Model:
##
## Test statistic 6.268
## Degrees of freedom 6
## P-value (Chi-square) 0.394
##
## Model Test Baseline Model:
##
## Test statistic 4835.945
## Degrees of freedom 33
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -7028.385
## Loglikelihood unrestricted model (H1) -7025.251
##
## Akaike (AIC) 14134.770
## Bayesian (BIC) 14339.379
## Sample-size adjusted Bayesian (BIC) 14215.490
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.006
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.036
## P-value RMSEA <= 0.05 0.998
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.008
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b =~
## t1_pri_con_fs 1.000 0.737 0.862
## t2_pri_con_fs 1.000 0.737 0.840
## t3_pri_con_fs 1.000 0.737 0.849
## inf_sha_beh_b =~
## t1_nf_sh_bh_fs 1.000 0.468 0.718
## t2_nf_sh_bh_fs 1.000 0.468 0.734
## t3_nf_sh_bh_fs 1.000 0.468 0.754
## t1_pri_con_w =~
## t1_pri_con_fs 1.000 0.403 0.472
## t2_pri_con_w =~
## t2_pri_con_fs 1.000 0.450 0.513
## t3_pri_con_w =~
## t3_pri_con_fs 1.000 0.425 0.489
## t1_inf_sha_beh_w =~
## t1_nf_sh_bh_fs 1.000 0.421 0.646
## t2_inf_sha_beh_w =~
## t2_nf_sh_bh_fs 1.000 0.394 0.618
## t3_inf_sha_beh_w =~
## t3_nf_sh_bh_fs 1.000 0.364 0.586
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.145 0.067 2.163 0.031 0.130 0.130
## t1_nf_s__ (a2) -0.021 0.035 -0.609 0.542 -0.020 -0.020
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (b1) 0.013 0.031 0.412 0.680 0.013 0.013
## t1_nf_s__ (b2) 0.027 0.044 0.621 0.534 0.029 0.029
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.145 0.067 2.163 0.031 0.154 0.154
## t2_nf_s__ (a2) -0.021 0.035 -0.609 0.542 -0.020 -0.020
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (b1) 0.013 0.031 0.412 0.680 0.016 0.016
## t2_nf_s__ (b2) 0.027 0.044 0.621 0.534 0.030 0.030
## t1_pri_con_fs ~
## age 0.010 0.001 6.844 0.000 0.010 0.184
## edu_num -0.023 0.013 -1.759 0.079 -0.023 -0.047
## male -0.002 0.046 -0.043 0.966 -0.002 -0.001
## t2_pri_con_fs ~
## age 0.010 0.002 6.509 0.000 0.010 0.175
## edu_num -0.023 0.013 -1.676 0.094 -0.023 -0.045
## male 0.012 0.047 0.251 0.802 0.012 0.007
## t3_pri_con_fs ~
## age 0.011 0.002 7.473 0.000 0.011 0.200
## edu_num -0.017 0.013 -1.310 0.190 -0.017 -0.035
## male 0.010 0.047 0.220 0.825 0.010 0.006
## t1_inf_sha_beh_fs ~
## age -0.009 0.001 -7.936 0.000 -0.009 -0.210
## edu_num 0.057 0.010 5.848 0.000 0.057 0.153
## male -0.132 0.035 -3.830 0.000 -0.132 -0.102
## t2_inf_sha_beh_fs ~
## age -0.010 0.001 -9.072 0.000 -0.010 -0.238
## edu_num 0.065 0.010 6.769 0.000 0.065 0.176
## male -0.083 0.034 -2.467 0.014 -0.083 -0.065
## t3_inf_sha_beh_fs ~
## age -0.009 0.001 -8.798 0.000 -0.009 -0.230
## edu_num 0.070 0.009 7.607 0.000 0.070 0.196
## male -0.121 0.033 -3.734 0.000 -0.121 -0.098
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b ~~
## inf_sh_bh_ -0.030 0.012 -2.614 0.009 -0.088 -0.088
## t1_pri_con_w ~~
## t1_nf_sh__ -0.017 0.007 -2.348 0.019 -0.098 -0.098
## .t2_pri_con_w ~~
## .t2_nf_sh__ (a) 0.007 0.006 1.138 0.255 0.037 0.037
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) 0.007 0.006 1.138 0.255 0.043 0.043
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_fs 3.270 0.136 24.029 0.000 3.270 3.827
## .t2_pri_con_fs 3.189 0.140 22.794 0.000 3.189 3.637
## .t3_pri_con_fs 3.064 0.138 22.237 0.000 3.064 3.532
## .t1_nf_sh_bh_fs 2.583 0.102 25.304 0.000 2.583 3.963
## .t2_nf_sh_bh_fs 2.539 0.099 25.598 0.000 2.539 3.980
## .t3_nf_sh_bh_fs 2.497 0.096 25.988 0.000 2.497 4.024
## pri_con_b 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000
## .t2_pri_con_w 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000
## .t2_inf_sh_bh_w 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b 0.542 0.025 21.867 0.000 1.000 1.000
## inf_sha_beh_b 0.219 0.011 19.078 0.000 1.000 1.000
## t1_pri_con_w 0.163 0.010 15.492 0.000 1.000 1.000
## .t2_pri_con_w 0.199 0.021 9.694 0.000 0.982 0.982
## .t3_pri_con_w 0.176 0.011 16.699 0.000 0.976 0.976
## t1_inf_sh_bh_w 0.177 0.010 18.671 0.000 1.000 1.000
## .t2_inf_sh_bh_w 0.155 0.013 12.395 0.000 0.999 0.999
## .t3_inf_sh_bh_w 0.132 0.008 17.350 0.000 0.999 0.999
## .t1_pri_con_fs 0.000 0.000 0.000
## .t2_pri_con_fs 0.000 0.000 0.000
## .t3_pri_con_fs 0.000 0.000 0.000
## .t1_nf_sh_bh_fs 0.000 0.000 0.000
## .t2_nf_sh_bh_fs 0.000 0.000 0.000
## .t3_nf_sh_bh_fs 0.000 0.000 0.0002.1.1.5 Model 5
In this model, we omit all longitudinal paths in order to better estimate the concurrent relations of the variables for all waves (in the regular RI-CLPM, only the relations at wave 1 can be interpreted meaningfully).
model <- "
# between relations
pri_con_b =~ 1*t1_pri_con_m + 1*t2_pri_con_m + 1*t3_pri_con_m
inf_sha_beh_b =~ 1*t1_inf_sha_beh_m + 1*t2_inf_sha_beh_m + 1*t3_inf_sha_beh_m
# intercepts
t1_pri_con_m ~ mu1*1
t2_pri_con_m ~ mu2*1
t3_pri_con_m ~ mu3*1
t1_inf_sha_beh_m ~ pi1*1
t2_inf_sha_beh_m ~ pi2*1
t3_inf_sha_beh_m ~ pi3*1
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_m
t2_pri_con_w =~ 1*t2_pri_con_m
t3_pri_con_w =~ 1*t3_pri_con_m
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_m
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_m
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_m
# estimate variances
pri_con_b ~~ pri_con_b
inf_sha_beh_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_pri_con_w
t2_pri_con_w ~~ t2_pri_con_w
t3_pri_con_w ~~ t3_pri_con_w
t1_inf_sha_beh_w ~~ t1_inf_sha_beh_w
t2_inf_sha_beh_w ~~ t2_inf_sha_beh_w
t3_inf_sha_beh_w ~~ t3_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ a*t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_beh_w
"
fit <- lavaan(model, data = d_wide, missing = "ml")
summary(fit, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 43 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 18
## Number of equality constraints 2
##
## Number of observations 1403
## Number of missing patterns 4
##
## Model Test User Model:
##
## Test statistic 9.758
## Degrees of freedom 11
## P-value (Chi-square) 0.552
##
## Model Test Baseline Model:
##
## Test statistic 4114.935
## Degrees of freedom 15
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -7481.675
## Loglikelihood unrestricted model (H1) -7476.795
##
## Akaike (AIC) 14995.349
## Bayesian (BIC) 15079.291
## Sample-size adjusted Bayesian (BIC) 15028.465
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.026
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.014
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b =~
## t1_pri_con_m 1.000 0.768 0.861
## t2_pri_con_m 1.000 0.768 0.869
## t3_pri_con_m 1.000 0.768 0.856
## inf_sha_beh_b =~
## t1_inf_sh_bh_m 1.000 0.500 0.762
## t2_inf_sh_bh_m 1.000 0.500 0.784
## t3_inf_sh_bh_m 1.000 0.500 0.808
## t1_pri_con_w =~
## t1_pri_con_m 1.000 0.454 0.509
## t2_pri_con_w =~
## t2_pri_con_m 1.000 0.437 0.495
## t3_pri_con_w =~
## t3_pri_con_m 1.000 0.463 0.517
## t1_inf_sha_beh_w =~
## t1_inf_sh_bh_m 1.000 0.425 0.647
## t2_inf_sha_beh_w =~
## t2_inf_sh_bh_m 1.000 0.396 0.621
## t3_inf_sha_beh_w =~
## t3_inf_sh_bh_m 1.000 0.365 0.589
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b ~~
## inf_sh_bh_ -0.065 0.012 -5.365 0.000 -0.169 -0.169
## t1_pri_con_w ~~
## t1_nf_sh__ (a) -0.002 0.003 -0.596 0.551 -0.010 -0.010
## t2_pri_con_w ~~
## t2_nf_sh__ (a) -0.002 0.003 -0.596 0.551 -0.012 -0.012
## t3_pri_con_w ~~
## t3_nf_sh__ (a) -0.002 0.003 -0.596 0.551 -0.012 -0.012
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pr_c_ (mu1) 3.671 0.024 154.082 0.000 3.671 4.117
## .t2_pr_c_ (mu2) 3.617 0.024 153.306 0.000 3.617 4.095
## .t3_pr_c_ (mu3) 3.589 0.024 149.810 0.000 3.589 4.004
## .t1_nf___ (pi1) 2.122 0.018 121.158 0.000 2.122 3.235
## .t2_nf___ (pi2) 2.135 0.017 125.399 0.000 2.135 3.348
## .t3_nf___ (pi3) 2.101 0.017 127.142 0.000 2.101 3.394
## pri_cn_b 0.000 0.000 0.000
## inf_sh__ 0.000 0.000 0.000
## t1_pr_c_ 0.000 0.000 0.000
## t2_pr_c_ 0.000 0.000 0.000
## t3_pr_c_ 0.000 0.000 0.000
## t1_nf___ 0.000 0.000 0.000
## t2_nf___ 0.000 0.000 0.000
## t3_nf___ 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b 0.589 0.025 23.655 0.000 1.000 1.000
## inf_sha_beh_b 0.250 0.011 21.807 0.000 1.000 1.000
## t1_pri_con_w 0.206 0.011 18.002 0.000 1.000 1.000
## t2_pri_con_w 0.191 0.011 17.470 0.000 1.000 1.000
## t3_pri_con_w 0.214 0.012 18.435 0.000 1.000 1.000
## t1_inf_sh_bh_w 0.180 0.009 19.921 0.000 1.000 1.000
## t2_inf_sh_bh_w 0.157 0.008 18.899 0.000 1.000 1.000
## t3_inf_sh_bh_w 0.133 0.008 17.519 0.000 1.000 1.000
## .t1_pri_con_m 0.000 0.000 0.000
## .t2_pri_con_m 0.000 0.000 0.000
## .t3_pri_con_m 0.000 0.000 0.000
## .t1_inf_sh_bh_m 0.000 0.000 0.000
## .t2_inf_sh_bh_m 0.000 0.000 0.000
## .t3_inf_sh_bh_m 0.000 0.000 0.0002.1.1.6 Model 6
The same like above, using Factor Scores and control variables.
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_fs + 1*t2_pri_con_fs + 1*t3_pri_con_fs
inf_sha_beh_b =~ 1*t1_inf_sha_beh_fs + 1*t2_inf_sha_beh_fs + 1*t3_inf_sha_beh_fs
# intercepts
t1_pri_con_fs ~ 1
t2_pri_con_fs ~ 1
t3_pri_con_fs ~ 1
t1_inf_sha_beh_fs ~ 1
t2_inf_sha_beh_fs ~ 1
t3_inf_sha_beh_fs ~ 1
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_fs
t2_pri_con_w =~ 1*t2_pri_con_fs
t3_pri_con_w =~ 1*t3_pri_con_fs
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_fs
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_fs
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_fs
# estimate variances
pri_con_b ~~ pri_con_b
inf_sha_beh_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_pri_con_w
t2_pri_con_w ~~ t2_pri_con_w
t3_pri_con_w ~~ t3_pri_con_w
t1_inf_sha_beh_w ~~ t1_inf_sha_beh_w
t2_inf_sha_beh_w ~~ t2_inf_sha_beh_w
t3_inf_sha_beh_w ~~ t3_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ a*t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_beh_w
# control variables
t1_pri_con_fs ~ age + edu_num + male
t2_pri_con_fs ~ age + edu_num + male
t3_pri_con_fs ~ age + edu_num + male
t1_inf_sha_beh_fs ~ age + edu_num + male
t2_inf_sha_beh_fs ~ age + edu_num + male
t3_inf_sha_beh_fs ~ age + edu_num + male
'
fit <- lavaan(model, data = d_wide, missing = "ml")
summary(fit, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 112 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 36
## Number of equality constraints 2
##
## Number of observations 1403
## Number of missing patterns 1
##
## Model Test User Model:
##
## Test statistic 18.421
## Degrees of freedom 11
## P-value (Chi-square) 0.072
##
## Model Test Baseline Model:
##
## Test statistic 4835.945
## Degrees of freedom 33
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.998
## Tucker-Lewis Index (TLI) 0.995
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -7034.461
## Loglikelihood unrestricted model (H1) -7025.251
##
## Akaike (AIC) 14136.923
## Bayesian (BIC) 14315.299
## Sample-size adjusted Bayesian (BIC) 14207.294
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.022
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.039
## P-value RMSEA <= 0.05 0.998
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.013
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b =~
## t1_pri_con_fs 1.000 0.750 0.867
## t2_pri_con_fs 1.000 0.750 0.869
## t3_pri_con_fs 1.000 0.750 0.860
## inf_sha_beh_b =~
## t1_nf_sh_bh_fs 1.000 0.471 0.722
## t2_nf_sh_bh_fs 1.000 0.471 0.741
## t3_nf_sh_bh_fs 1.000 0.471 0.757
## t1_pri_con_w =~
## t1_pri_con_fs 1.000 0.400 0.463
## t2_pri_con_w =~
## t2_pri_con_fs 1.000 0.399 0.462
## t3_pri_con_w =~
## t3_pri_con_fs 1.000 0.411 0.471
## t1_inf_sha_beh_w =~
## t1_nf_sh_bh_fs 1.000 0.419 0.642
## t2_inf_sha_beh_w =~
## t2_nf_sh_bh_fs 1.000 0.387 0.608
## t3_inf_sha_beh_w =~
## t3_nf_sh_bh_fs 1.000 0.363 0.583
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_fs ~
## age 0.010 0.002 6.759 0.000 0.010 0.182
## edu_num -0.023 0.013 -1.737 0.082 -0.023 -0.046
## male -0.002 0.047 -0.042 0.966 -0.002 -0.001
## t2_pri_con_fs ~
## age 0.010 0.002 6.614 0.000 0.010 0.178
## edu_num -0.023 0.013 -1.703 0.089 -0.023 -0.045
## male 0.012 0.047 0.255 0.799 0.012 0.007
## t3_pri_con_fs ~
## age 0.011 0.002 7.429 0.000 0.011 0.199
## edu_num -0.017 0.013 -1.303 0.193 -0.017 -0.035
## male 0.010 0.047 0.219 0.826 0.010 0.006
## t1_inf_sha_beh_fs ~
## age -0.009 0.001 -7.927 0.000 -0.009 -0.209
## edu_num 0.057 0.010 5.841 0.000 0.057 0.153
## male -0.132 0.035 -3.825 0.000 -0.132 -0.101
## t2_inf_sha_beh_fs ~
## age -0.010 0.001 -9.112 0.000 -0.010 -0.239
## edu_num 0.065 0.009 6.799 0.000 0.065 0.176
## male -0.083 0.033 -2.478 0.013 -0.083 -0.065
## t3_inf_sha_beh_fs ~
## age -0.009 0.001 -8.776 0.000 -0.009 -0.229
## edu_num 0.070 0.009 7.588 0.000 0.070 0.196
## male -0.121 0.033 -3.724 0.000 -0.121 -0.098
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b ~~
## inf_sh_bh_ -0.031 0.011 -2.851 0.004 -0.089 -0.089
## t1_pri_con_w ~~
## t1_nf_sh__ (a) 0.000 0.003 0.142 0.887 0.003 0.003
## t2_pri_con_w ~~
## t2_nf_sh__ (a) 0.000 0.003 0.142 0.887 0.003 0.003
## t3_pri_con_w ~~
## t3_nf_sh__ (a) 0.000 0.003 0.142 0.887 0.003 0.003
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_fs 3.270 0.138 23.732 0.000 3.270 3.781
## .t2_pri_con_fs 3.189 0.138 23.164 0.000 3.189 3.694
## .t3_pri_con_fs 3.064 0.139 22.107 0.000 3.064 3.512
## .t1_nf_sh_bh_fs 2.583 0.102 25.274 0.000 2.583 3.959
## .t2_nf_sh_bh_fs 2.539 0.099 25.712 0.000 2.539 3.997
## .t3_nf_sh_bh_fs 2.497 0.096 25.922 0.000 2.497 4.014
## pri_con_b 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000
## t2_pri_con_w 0.000 0.000 0.000
## t3_pri_con_w 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000
## t2_inf_sh_bh_w 0.000 0.000 0.000
## t3_inf_sh_bh_w 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## pri_con_b 0.562 0.023 24.101 0.000 1.000 1.000
## inf_sha_beh_b 0.222 0.010 21.431 0.000 1.000 1.000
## t1_pri_con_w 0.160 0.009 17.623 0.000 1.000 1.000
## t2_pri_con_w 0.159 0.009 17.698 0.000 1.000 1.000
## t3_pri_con_w 0.169 0.009 18.168 0.000 1.000 1.000
## t1_inf_sh_bh_w 0.176 0.009 20.015 0.000 1.000 1.000
## t2_inf_sh_bh_w 0.149 0.008 18.825 0.000 1.000 1.000
## t3_inf_sh_bh_w 0.131 0.007 17.765 0.000 1.000 1.000
## .t1_pri_con_fs 0.000 0.000 0.000
## .t2_pri_con_fs 0.000 0.000 0.000
## .t3_pri_con_fs 0.000 0.000 0.000
## .t1_nf_sh_bh_fs 0.000 0.000 0.000
## .t2_nf_sh_bh_fs 0.000 0.000 0.000
## .t3_nf_sh_bh_fs 0.000 0.000 0.0002.1.2 Three Variables
2.1.2.1 Model 1
With observed means.
model <- '
# random intercepts (between person)
pri_con_b =~ 1*t1_pri_con_m + 1*t2_pri_con_m + 1*t3_pri_con_m
inf_sha_att_b =~ 1*t1_inf_sha_att_m + 1*t2_inf_sha_att_m + 1*t3_inf_sha_att_m
inf_sha_beh_b =~ 1*t1_inf_sha_beh_m + 1*t2_inf_sha_beh_m + 1*t3_inf_sha_beh_m
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_m
t2_pri_con_w =~ 1*t2_pri_con_m
t3_pri_con_w =~ 1*t3_pri_con_m
t1_inf_sha_att_w =~ 1*t1_inf_sha_att_m
t2_inf_sha_att_w =~ 1*t2_inf_sha_att_m
t3_inf_sha_att_w =~ 1*t3_inf_sha_att_m
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_m
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_m
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_m
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_att_w + a3*t1_inf_sha_beh_w
t2_inf_sha_att_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_att_w + b3*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ c1*t1_pri_con_w + c2*t1_inf_sha_att_w + c3*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_att_w + a3*t2_inf_sha_beh_w
t3_inf_sha_att_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_att_w + b3*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ c1*t2_pri_con_w + c2*t2_inf_sha_att_w + c3*t2_inf_sha_beh_w
# setting variances of observed variables to zero
t1_pri_con_m ~~ 0*t1_pri_con_m
t2_pri_con_m ~~ 0*t2_pri_con_m
t3_pri_con_m ~~ 0*t3_pri_con_m
t1_inf_sha_att_m ~~ 0*t1_inf_sha_att_m
t2_inf_sha_att_m ~~ 0*t2_inf_sha_att_m
t3_inf_sha_att_m ~~ 0*t3_inf_sha_att_m
t1_inf_sha_beh_m ~~ 0*t1_inf_sha_beh_m
t2_inf_sha_beh_m ~~ 0*t2_inf_sha_beh_m
t3_inf_sha_beh_m ~~ 0*t3_inf_sha_beh_m
# allow covariances RIs & variables measured at the same time
pri_con_b ~~ inf_sha_att_b + inf_sha_beh_b
inf_sha_att_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_att_w + t1_inf_sha_beh_w
t1_inf_sha_att_w ~~ t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_att_w + b*t2_inf_sha_beh_w
t2_inf_sha_att_w ~~ c*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_att_w + b*t3_inf_sha_beh_w
t3_inf_sha_att_w ~~ c*t3_inf_sha_beh_w
'
fit <- sem(model, estimator = "ML", data = d_wide, orthogonal = TRUE, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE, ci = TRUE)## lavaan 0.6-7 ended normally after 76 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 51
## Number of equality constraints 12
##
## Number of observations 1403
## Number of missing patterns 7
##
## Model Test User Model:
##
## Test statistic 16.409
## Degrees of freedom 15
## P-value (Chi-square) 0.355
##
## Model Test Baseline Model:
##
## Test statistic 6284.683
## Degrees of freedom 36
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 0.999
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -10864.395
## Loglikelihood unrestricted model (H1) -10856.190
##
## Akaike (AIC) 21806.789
## Bayesian (BIC) 22011.398
## Sample-size adjusted Bayesian (BIC) 21887.509
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.008
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.027
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.013
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b =~
## t1_pri_con_m 1.000 1.000 1.000 0.758 0.856
## t2_pri_con_m 1.000 1.000 1.000 0.758 0.851
## t3_pri_con_m 1.000 1.000 1.000 0.758 0.850
## inf_sha_att_b =~
## t1_inf_sh_tt_m 1.000 1.000 1.000 0.525 0.741
## t2_inf_sh_tt_m 1.000 1.000 1.000 0.525 0.744
## t3_inf_sh_tt_m 1.000 1.000 1.000 0.525 0.761
## inf_sha_beh_b =~
## t1_inf_sh_bh_m 1.000 1.000 1.000 0.492 0.752
## t2_inf_sh_bh_m 1.000 1.000 1.000 0.492 0.761
## t3_inf_sh_bh_m 1.000 1.000 1.000 0.492 0.804
## t1_pri_con_w =~
## t1_pri_con_m 1.000 1.000 1.000 0.457 0.516
## t2_pri_con_w =~
## t2_pri_con_m 1.000 1.000 1.000 0.468 0.525
## t3_pri_con_w =~
## t3_pri_con_m 1.000 1.000 1.000 0.470 0.527
## t1_inf_sha_att_w =~
## t1_inf_sh_tt_m 1.000 1.000 1.000 0.475 0.671
## t2_inf_sha_att_w =~
## t2_inf_sh_tt_m 1.000 1.000 1.000 0.471 0.668
## t3_inf_sha_att_w =~
## t3_inf_sh_tt_m 1.000 1.000 1.000 0.447 0.649
## t1_inf_sha_beh_w =~
## t1_inf_sh_bh_m 1.000 1.000 1.000 0.432 0.660
## t2_inf_sha_beh_w =~
## t2_inf_sh_bh_m 1.000 1.000 1.000 0.420 0.649
## t3_inf_sha_beh_w =~
## t3_inf_sh_bh_m 1.000 1.000 1.000 0.364 0.595
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.082 0.072 1.139 0.255 -0.059 0.222 0.080 0.080
## t1_nf_s__ (a2) -0.032 0.035 -0.932 0.351 -0.101 0.036 -0.033 -0.033
## t1_nf_s__ (a3) 0.008 0.037 0.223 0.824 -0.065 0.081 0.008 0.008
## t2_inf_sha_att_w ~
## t1_pr_cn_ (b1) -0.018 0.035 -0.507 0.612 -0.087 0.051 -0.017 -0.017
## t1_nf_s__ (b2) 0.111 0.046 2.415 0.016 0.021 0.202 0.112 0.112
## t1_nf_s__ (b3) 0.038 0.036 1.038 0.299 -0.033 0.109 0.035 0.035
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (c1) 0.032 0.029 1.107 0.268 -0.025 0.090 0.035 0.035
## t1_nf_s__ (c2) -0.006 0.029 -0.195 0.846 -0.062 0.051 -0.006 -0.006
## t1_nf_s__ (c3) 0.066 0.041 1.605 0.108 -0.015 0.147 0.068 0.068
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.082 0.072 1.139 0.255 -0.059 0.222 0.081 0.081
## t2_nf_s__ (a2) -0.032 0.035 -0.932 0.351 -0.101 0.036 -0.032 -0.032
## t2_nf_s__ (a3) 0.008 0.037 0.223 0.824 -0.065 0.081 0.007 0.007
## t3_inf_sha_att_w ~
## t2_pr_cn_ (b1) -0.018 0.035 -0.507 0.612 -0.087 0.051 -0.019 -0.019
## t2_nf_s__ (b2) 0.111 0.046 2.415 0.016 0.021 0.202 0.117 0.117
## t2_nf_s__ (b3) 0.038 0.036 1.038 0.299 -0.033 0.109 0.035 0.035
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (c1) 0.032 0.029 1.107 0.268 -0.025 0.090 0.042 0.042
## t2_nf_s__ (c2) -0.006 0.029 -0.195 0.846 -0.062 0.051 -0.007 -0.007
## t2_nf_s__ (c3) 0.066 0.041 1.605 0.108 -0.015 0.147 0.077 0.077
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b ~~
## inf_sh_tt_ -0.128 0.015 -8.769 0.000 -0.156 -0.099 -0.321 -0.321
## inf_sh_bh_ -0.067 0.013 -5.248 0.000 -0.092 -0.042 -0.180 -0.180
## inf_sha_att_b ~~
## inf_sh_bh_ 0.174 0.011 15.664 0.000 0.152 0.196 0.675 0.675
## t1_pri_con_w ~~
## t1_nf_sh__ -0.002 0.009 -0.209 0.834 -0.019 0.016 -0.009 -0.009
## t1_nf_sh__ -0.011 0.008 -1.416 0.157 -0.027 0.004 -0.057 -0.057
## t1_inf_sha_att_w ~~
## t1_nf_sh__ 0.028 0.008 3.510 0.000 0.012 0.043 0.136 0.136
## .t2_pri_con_w ~~
## .t2_nf_sh__ (a) -0.007 0.008 -0.896 0.370 -0.023 0.008 -0.032 -0.032
## .t2_nf_sh__ (b) 0.005 0.007 0.736 0.462 -0.008 0.018 0.025 0.025
## .t2_inf_sha_att_w ~~
## .t2_nf_sh__ (c) 0.032 0.006 4.947 0.000 0.019 0.045 0.164 0.164
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) -0.007 0.008 -0.896 0.370 -0.023 0.008 -0.034 -0.034
## .t3_nf_sh__ (b) 0.005 0.007 0.736 0.462 -0.008 0.018 0.028 0.028
## .t3_inf_sha_att_w ~~
## .t3_nf_sh__ (c) 0.032 0.006 4.947 0.000 0.019 0.045 0.200 0.200
## pri_con_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_m 3.671 0.024 155.214 0.000 3.625 3.717 3.671 4.147
## .t2_pri_con_m 3.617 0.024 151.977 0.000 3.570 3.664 3.617 4.059
## .t3_pri_con_m 3.589 0.024 150.526 0.000 3.543 3.636 3.589 4.023
## .t1_inf_sh_tt_m 2.342 0.019 123.900 0.000 2.305 2.379 2.342 3.308
## .t2_inf_sh_tt_m 2.402 0.019 127.433 0.000 2.365 2.438 2.402 3.407
## .t3_inf_sh_tt_m 2.421 0.018 131.570 0.000 2.385 2.457 2.421 3.513
## .t1_inf_sh_bh_m 2.122 0.017 121.415 0.000 2.088 2.157 2.122 3.241
## .t2_inf_sh_bh_m 2.135 0.017 123.635 0.000 2.101 2.169 2.135 3.301
## .t3_inf_sh_bh_m 2.101 0.016 128.586 0.000 2.069 2.133 2.101 3.433
## pri_con_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t1_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t1_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## pri_con_b 0.575 0.027 20.987 0.000 0.521 0.629 1.000 1.000
## inf_sha_att_b 0.275 0.016 17.149 0.000 0.244 0.307 1.000 1.000
## inf_sha_beh_b 0.242 0.013 19.290 0.000 0.217 0.267 1.000 1.000
## t1_pri_con_w 0.209 0.013 16.673 0.000 0.184 0.233 1.000 1.000
## .t2_pri_con_w 0.217 0.026 8.271 0.000 0.166 0.269 0.993 0.993
## .t3_pri_con_w 0.219 0.013 17.466 0.000 0.195 0.244 0.992 0.992
## t1_inf_sh_tt_w 0.226 0.013 17.958 0.000 0.201 0.250 1.000 1.000
## .t2_inf_sh_tt_w 0.218 0.016 13.910 0.000 0.187 0.249 0.985 0.985
## .t3_inf_sh_tt_w 0.196 0.011 18.271 0.000 0.175 0.218 0.983 0.983
## t1_inf_sh_bh_w 0.187 0.010 18.785 0.000 0.167 0.206 1.000 1.000
## .t2_inf_sh_bh_w 0.175 0.012 14.279 0.000 0.151 0.199 0.994 0.994
## .t3_inf_sh_bh_w 0.131 0.008 16.945 0.000 0.116 0.147 0.992 0.9922.1.2.2 Model 2
With observed means and control variables.
model <- '
# random intercepts (between person)
pri_con_b =~ 1*t1_pri_con_m + 1*t2_pri_con_m + 1*t3_pri_con_m
inf_sha_att_b =~ 1*t1_inf_sha_att_m + 1*t2_inf_sha_att_m + 1*t3_inf_sha_att_m
inf_sha_beh_b =~ 1*t1_inf_sha_beh_m + 1*t2_inf_sha_beh_m + 1*t3_inf_sha_beh_m
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_m
t2_pri_con_w =~ 1*t2_pri_con_m
t3_pri_con_w =~ 1*t3_pri_con_m
t1_inf_sha_att_w =~ 1*t1_inf_sha_att_m
t2_inf_sha_att_w =~ 1*t2_inf_sha_att_m
t3_inf_sha_att_w =~ 1*t3_inf_sha_att_m
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_m
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_m
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_m
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_att_w + a3*t1_inf_sha_beh_w
t2_inf_sha_att_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_att_w + b3*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ c1*t1_pri_con_w + c2*t1_inf_sha_att_w + c3*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_att_w + a3*t2_inf_sha_beh_w
t3_inf_sha_att_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_att_w + b3*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ c1*t2_pri_con_w + c2*t2_inf_sha_att_w + c3*t2_inf_sha_beh_w
# setting variances of observed variables to zero
t1_pri_con_m ~~ 0*t1_pri_con_m
t2_pri_con_m ~~ 0*t2_pri_con_m
t3_pri_con_m ~~ 0*t3_pri_con_m
t1_inf_sha_att_m ~~ 0*t1_inf_sha_att_m
t2_inf_sha_att_m ~~ 0*t2_inf_sha_att_m
t3_inf_sha_att_m ~~ 0*t3_inf_sha_att_m
t1_inf_sha_beh_m ~~ 0*t1_inf_sha_beh_m
t2_inf_sha_beh_m ~~ 0*t2_inf_sha_beh_m
t3_inf_sha_beh_m ~~ 0*t3_inf_sha_beh_m
# allow covariances RIs & variables measured at the same time
pri_con_b ~~ inf_sha_att_b + inf_sha_beh_b
inf_sha_att_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_att_w + t1_inf_sha_beh_w
t1_inf_sha_att_w ~~ t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_att_w + b*t2_inf_sha_beh_w
t2_inf_sha_att_w ~~ c*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_att_w + b*t3_inf_sha_beh_w
t3_inf_sha_att_w ~~ c*t3_inf_sha_beh_w
# control variables
t1_pri_con_m ~ age + edu_num + male
t2_pri_con_m ~ age + edu_num + male
t3_pri_con_m ~ age + edu_num + male
t1_inf_sha_beh_m ~ age + edu_num + male
t2_inf_sha_beh_m ~ age + edu_num + male
t3_inf_sha_beh_m ~ age + edu_num + male
t1_inf_sha_att_m ~ age + edu_num + male
t2_inf_sha_att_m ~ age + edu_num + male
t3_inf_sha_att_m ~ age + edu_num + male
'
fit <- sem(model, estimator = "ML", data = d_wide, orthogonal = TRUE, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE, ci = TRUE)## lavaan 0.6-7 ended normally after 172 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 78
## Number of equality constraints 12
##
## Number of observations 1403
## Number of missing patterns 7
##
## Model Test User Model:
##
## Test statistic 16.098
## Degrees of freedom 15
## P-value (Chi-square) 0.376
##
## Model Test Baseline Model:
##
## Test statistic 6592.769
## Degrees of freedom 63
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 0.999
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -10710.196
## Loglikelihood unrestricted model (H1) -10702.147
##
## Akaike (AIC) 21552.392
## Bayesian (BIC) 21898.652
## Sample-size adjusted Bayesian (BIC) 21688.995
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.007
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.027
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.008
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b =~
## t1_pri_con_m 1.000 1.000 1.000 0.734 0.831
## t2_pri_con_m 1.000 1.000 1.000 0.734 0.824
## t3_pri_con_m 1.000 1.000 1.000 0.734 0.822
## inf_sha_att_b =~
## t1_inf_sh_tt_m 1.000 1.000 1.000 0.499 0.709
## t2_inf_sh_tt_m 1.000 1.000 1.000 0.499 0.707
## t3_inf_sh_tt_m 1.000 1.000 1.000 0.499 0.720
## inf_sha_beh_b =~
## t1_inf_sh_bh_m 1.000 1.000 1.000 0.461 0.705
## t2_inf_sh_bh_m 1.000 1.000 1.000 0.461 0.715
## t3_inf_sh_bh_m 1.000 1.000 1.000 0.461 0.751
## t1_pri_con_w =~
## t1_pri_con_m 1.000 1.000 1.000 0.457 0.518
## t2_pri_con_w =~
## t2_pri_con_m 1.000 1.000 1.000 0.471 0.528
## t3_pri_con_w =~
## t3_pri_con_m 1.000 1.000 1.000 0.470 0.526
## t1_inf_sha_att_w =~
## t1_inf_sh_tt_m 1.000 1.000 1.000 0.472 0.671
## t2_inf_sha_att_w =~
## t2_inf_sh_tt_m 1.000 1.000 1.000 0.465 0.660
## t3_inf_sha_att_w =~
## t3_inf_sh_tt_m 1.000 1.000 1.000 0.445 0.643
## t1_inf_sha_beh_w =~
## t1_inf_sh_bh_m 1.000 1.000 1.000 0.433 0.662
## t2_inf_sha_beh_w =~
## t2_inf_sh_bh_m 1.000 1.000 1.000 0.414 0.642
## t3_inf_sha_beh_w =~
## t3_inf_sh_bh_m 1.000 1.000 1.000 0.361 0.588
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.088 0.069 1.283 0.200 -0.046 0.223 0.086 0.086
## t1_nf_s__ (a2) -0.028 0.035 -0.802 0.422 -0.096 0.040 -0.028 -0.028
## t1_nf_s__ (a3) 0.012 0.037 0.337 0.736 -0.060 0.085 0.011 0.011
## t2_inf_sha_att_w ~
## t1_pr_cn_ (b1) -0.010 0.035 -0.296 0.767 -0.079 0.058 -0.010 -0.010
## t1_nf_s__ (b2) 0.101 0.046 2.210 0.027 0.011 0.191 0.103 0.103
## t1_nf_s__ (b3) 0.029 0.036 0.814 0.416 -0.041 0.098 0.027 0.027
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (c1) 0.038 0.028 1.329 0.184 -0.018 0.094 0.042 0.042
## t1_nf_s__ (c2) -0.007 0.028 -0.239 0.811 -0.062 0.048 -0.008 -0.008
## t1_nf_s__ (c3) 0.055 0.039 1.398 0.162 -0.022 0.132 0.058 0.058
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.088 0.069 1.283 0.200 -0.046 0.223 0.088 0.088
## t2_nf_s__ (a2) -0.028 0.035 -0.802 0.422 -0.096 0.040 -0.028 -0.028
## t2_nf_s__ (a3) 0.012 0.037 0.337 0.736 -0.060 0.085 0.011 0.011
## t3_inf_sha_att_w ~
## t2_pr_cn_ (b1) -0.010 0.035 -0.296 0.767 -0.079 0.058 -0.011 -0.011
## t2_nf_s__ (b2) 0.101 0.046 2.210 0.027 0.011 0.191 0.106 0.106
## t2_nf_s__ (b3) 0.029 0.036 0.814 0.416 -0.041 0.098 0.027 0.027
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (c1) 0.038 0.028 1.329 0.184 -0.018 0.094 0.049 0.049
## t2_nf_s__ (c2) -0.007 0.028 -0.239 0.811 -0.062 0.048 -0.009 -0.009
## t2_nf_s__ (c3) 0.055 0.039 1.398 0.162 -0.022 0.132 0.063 0.063
## t1_pri_con_m ~
## age 0.011 0.002 7.417 0.000 0.008 0.014 0.011 0.199
## edu_num -0.032 0.013 -2.356 0.018 -0.058 -0.005 -0.032 -0.062
## male -0.007 0.048 -0.149 0.881 -0.100 0.086 -0.007 -0.004
## t2_pri_con_m ~
## age 0.012 0.002 7.623 0.000 0.009 0.015 0.012 0.204
## edu_num -0.034 0.014 -2.474 0.013 -0.060 -0.007 -0.034 -0.065
## male 0.021 0.048 0.449 0.654 -0.072 0.115 0.021 0.012
## t3_pri_con_m ~
## age 0.013 0.002 8.215 0.000 0.010 0.016 0.013 0.220
## edu_num -0.025 0.014 -1.871 0.061 -0.052 0.001 -0.025 -0.049
## male 0.032 0.048 0.672 0.501 -0.062 0.126 0.032 0.018
## t1_inf_sha_beh_m ~
## age -0.009 0.001 -7.725 0.000 -0.011 -0.006 -0.009 -0.204
## edu_num 0.056 0.010 5.650 0.000 0.036 0.075 0.056 0.148
## male -0.145 0.035 -4.176 0.000 -0.213 -0.077 -0.145 -0.111
## t2_inf_sha_beh_m ~
## age -0.010 0.001 -8.911 0.000 -0.012 -0.008 -0.010 -0.234
## edu_num 0.064 0.010 6.661 0.000 0.045 0.083 0.064 0.173
## male -0.084 0.034 -2.464 0.014 -0.150 -0.017 -0.084 -0.065
## t3_inf_sha_beh_m ~
## age -0.010 0.001 -9.234 0.000 -0.012 -0.008 -0.010 -0.241
## edu_num 0.068 0.009 7.450 0.000 0.050 0.086 0.068 0.192
## male -0.129 0.032 -4.021 0.000 -0.192 -0.066 -0.129 -0.105
## t1_inf_sha_att_m ~
## age -0.004 0.001 -3.327 0.001 -0.006 -0.002 -0.004 -0.089
## edu_num 0.027 0.011 2.529 0.011 0.006 0.048 0.027 0.067
## male -0.284 0.038 -7.519 0.000 -0.357 -0.210 -0.284 -0.201
## t2_inf_sha_att_m ~
## age -0.006 0.001 -5.182 0.000 -0.009 -0.004 -0.006 -0.137
## edu_num 0.045 0.011 4.240 0.000 0.024 0.066 0.045 0.111
## male -0.291 0.037 -7.763 0.000 -0.365 -0.218 -0.291 -0.206
## t3_inf_sha_att_m ~
## age -0.007 0.001 -6.146 0.000 -0.010 -0.005 -0.007 -0.162
## edu_num 0.047 0.010 4.524 0.000 0.027 0.068 0.047 0.118
## male -0.268 0.037 -7.309 0.000 -0.340 -0.196 -0.268 -0.194
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b ~~
## inf_sh_tt_ -0.114 0.014 -8.348 0.000 -0.141 -0.087 -0.311 -0.311
## inf_sh_bh_ -0.040 0.012 -3.393 0.001 -0.063 -0.017 -0.118 -0.118
## inf_sha_att_b ~~
## inf_sh_bh_ 0.151 0.010 14.987 0.000 0.131 0.171 0.656 0.656
## t1_pri_con_w ~~
## t1_nf_sh__ -0.004 0.009 -0.405 0.685 -0.021 0.014 -0.016 -0.016
## t1_nf_sh__ -0.013 0.008 -1.583 0.113 -0.028 0.003 -0.063 -0.063
## t1_inf_sha_att_w ~~
## t1_nf_sh__ 0.028 0.008 3.575 0.000 0.013 0.043 0.136 0.136
## .t2_pri_con_w ~~
## .t2_nf_sh__ (a) -0.005 0.008 -0.590 0.555 -0.020 0.011 -0.021 -0.021
## .t2_nf_sh__ (b) 0.006 0.006 0.986 0.324 -0.006 0.019 0.032 0.032
## .t2_inf_sha_att_w ~~
## .t2_nf_sh__ (c) 0.030 0.006 4.887 0.000 0.018 0.042 0.158 0.158
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) -0.005 0.008 -0.590 0.555 -0.020 0.011 -0.022 -0.022
## .t3_nf_sh__ (b) 0.006 0.006 0.986 0.324 -0.006 0.019 0.037 0.037
## .t3_inf_sha_att_w ~~
## .t3_nf_sh__ (c) 0.030 0.006 4.887 0.000 0.018 0.042 0.190 0.190
## pri_con_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_m 3.221 0.140 22.959 0.000 2.946 3.496 3.221 3.646
## .t2_pri_con_m 3.111 0.141 22.000 0.000 2.834 3.389 3.111 3.490
## .t3_pri_con_m 2.975 0.142 20.974 0.000 2.697 3.253 2.975 3.330
## .t1_inf_sh_tt_m 2.847 0.111 25.548 0.000 2.629 3.066 2.847 4.045
## .t2_inf_sh_tt_m 2.947 0.111 26.617 0.000 2.730 3.165 2.947 4.178
## .t3_inf_sh_tt_m 2.978 0.108 27.480 0.000 2.766 3.191 2.978 4.302
## .t1_inf_sh_bh_m 2.528 0.103 24.659 0.000 2.327 2.729 2.528 3.865
## .t2_inf_sh_bh_m 2.468 0.100 24.566 0.000 2.271 2.664 2.468 3.825
## .t3_inf_sh_bh_m 2.471 0.095 26.045 0.000 2.285 2.657 2.471 4.024
## pri_con_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t1_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t1_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## pri_con_b 0.539 0.026 20.731 0.000 0.488 0.590 1.000 1.000
## inf_sha_att_b 0.249 0.015 16.676 0.000 0.220 0.278 1.000 1.000
## inf_sha_beh_b 0.212 0.011 18.742 0.000 0.190 0.235 1.000 1.000
## t1_pri_con_w 0.209 0.013 16.657 0.000 0.185 0.234 1.000 1.000
## .t2_pri_con_w 0.220 0.025 8.744 0.000 0.171 0.269 0.992 0.992
## .t3_pri_con_w 0.219 0.013 17.514 0.000 0.194 0.243 0.991 0.991
## t1_inf_sh_tt_w 0.223 0.012 18.207 0.000 0.199 0.247 1.000 1.000
## .t2_inf_sh_tt_w 0.214 0.015 13.962 0.000 0.184 0.244 0.988 0.988
## .t3_inf_sh_tt_w 0.196 0.011 18.462 0.000 0.175 0.217 0.987 0.987
## t1_inf_sh_bh_w 0.188 0.010 18.988 0.000 0.168 0.207 1.000 1.000
## .t2_inf_sh_bh_w 0.171 0.012 14.847 0.000 0.148 0.193 0.995 0.995
## .t3_inf_sh_bh_w 0.129 0.008 17.175 0.000 0.115 0.144 0.993 0.9932.1.2.3 Model 3
With Factor Scores.
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_fs + 1*t2_pri_con_fs + 1*t3_pri_con_fs
inf_sha_beh_b =~ 1*t1_inf_sha_beh_fs + 1*t2_inf_sha_beh_fs + 1*t3_inf_sha_beh_fs
inf_sha_att_b =~ 1*t1_inf_sha_att_fs + 1*t2_inf_sha_att_fs + 1*t3_inf_sha_att_fs
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_fs
t2_pri_con_w =~ 1*t2_pri_con_fs
t3_pri_con_w =~ 1*t3_pri_con_fs
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_fs
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_fs
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_fs
t1_inf_sha_att_w =~ 1*t1_inf_sha_att_fs
t2_inf_sha_att_w =~ 1*t2_inf_sha_att_fs
t3_inf_sha_att_w =~ 1*t3_inf_sha_att_fs
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_att_w + a3*t1_inf_sha_beh_w
t2_inf_sha_att_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_att_w + b3*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ c1*t1_pri_con_w + c2*t1_inf_sha_att_w + c3*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_att_w + a3*t2_inf_sha_beh_w
t3_inf_sha_att_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_att_w + b3*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ c1*t2_pri_con_w + c2*t2_inf_sha_att_w + c3*t2_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_att_b + inf_sha_beh_b
inf_sha_att_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_att_w + t1_inf_sha_beh_w
t1_inf_sha_att_w ~~ t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_att_w + b*t2_inf_sha_beh_w
t2_inf_sha_att_w ~~ c*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_att_w + b*t3_inf_sha_beh_w
t3_inf_sha_att_w ~~ c*t3_inf_sha_beh_w
# setting variances of observed variables to zero
t1_pri_con_fs ~~ 0*t1_pri_con_fs
t2_pri_con_fs ~~ 0*t2_pri_con_fs
t3_pri_con_fs ~~ 0*t3_pri_con_fs
t1_inf_sha_att_fs ~~ 0*t1_inf_sha_att_fs
t2_inf_sha_att_fs ~~ 0*t2_inf_sha_att_fs
t3_inf_sha_att_fs ~~ 0*t3_inf_sha_att_fs
t1_inf_sha_beh_fs ~~ 0*t1_inf_sha_beh_fs
t2_inf_sha_beh_fs ~~ 0*t2_inf_sha_beh_fs
t3_inf_sha_beh_fs ~~ 0*t3_inf_sha_beh_fs
'
fit <- sem(model, data = d_wide, orthogonal = TRUE, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE, ci = TRUE)## lavaan 0.6-7 ended normally after 81 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 51
## Number of equality constraints 12
##
## Number of observations 1403
## Number of missing patterns 1
##
## Model Test User Model:
##
## Test statistic 26.276
## Degrees of freedom 15
## P-value (Chi-square) 0.035
##
## Model Test Baseline Model:
##
## Test statistic 6848.636
## Degrees of freedom 36
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.998
## Tucker-Lewis Index (TLI) 0.996
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -10390.169
## Loglikelihood unrestricted model (H1) -10377.031
##
## Akaike (AIC) 20858.337
## Bayesian (BIC) 21062.945
## Sample-size adjusted Bayesian (BIC) 20939.057
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.023
## 90 Percent confidence interval - lower 0.006
## 90 Percent confidence interval - upper 0.038
## P-value RMSEA <= 0.05 0.999
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.015
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b =~
## t1_pri_con_fs 1.000 1.000 1.000 0.755 0.883
## t2_pri_con_fs 1.000 1.000 1.000 0.755 0.861
## t3_pri_con_fs 1.000 1.000 1.000 0.755 0.871
## inf_sha_beh_b =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.497 0.760
## t2_nf_sh_bh_fs 1.000 1.000 1.000 0.497 0.772
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.497 0.809
## inf_sha_att_b =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.511 0.737
## t2_nf_sh_tt_fs 1.000 1.000 1.000 0.511 0.746
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.511 0.767
## t1_pri_con_w =~
## t1_pri_con_fs 1.000 1.000 1.000 0.402 0.470
## t2_pri_con_w =~
## t2_pri_con_fs 1.000 1.000 1.000 0.445 0.508
## t3_pri_con_w =~
## t3_pri_con_fs 1.000 1.000 1.000 0.425 0.491
## t1_inf_sha_beh_w =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.425 0.650
## t2_inf_sha_beh_w =~
## t2_nf_sh_bh_fs 1.000 1.000 1.000 0.409 0.635
## t3_inf_sha_beh_w =~
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.361 0.588
## t1_inf_sha_att_w =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.469 0.676
## t2_inf_sha_att_w =~
## t2_nf_sh_tt_fs 1.000 1.000 1.000 0.456 0.666
## t3_inf_sha_att_w =~
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.428 0.642
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.134 0.072 1.872 0.061 -0.006 0.275 0.121 0.121
## t1_nf_s__ (a2) -0.002 0.032 -0.058 0.954 -0.065 0.061 -0.002 -0.002
## t1_nf_s__ (a3) -0.029 0.035 -0.834 0.404 -0.097 0.039 -0.028 -0.028
## t2_inf_sha_att_w ~
## t1_pr_cn_ (b1) -0.024 0.038 -0.625 0.532 -0.098 0.050 -0.021 -0.021
## t1_nf_s__ (b2) 0.112 0.047 2.408 0.016 0.021 0.203 0.115 0.115
## t1_nf_s__ (b3) 0.049 0.036 1.354 0.176 -0.022 0.119 0.045 0.045
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (c1) 0.011 0.032 0.333 0.739 -0.052 0.073 0.011 0.011
## t1_nf_s__ (c2) -0.001 0.029 -0.021 0.983 -0.057 0.056 -0.001 -0.001
## t1_nf_s__ (c3) 0.056 0.041 1.353 0.176 -0.025 0.136 0.058 0.058
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.134 0.072 1.872 0.061 -0.006 0.275 0.141 0.141
## t2_nf_s__ (a2) -0.002 0.032 -0.058 0.954 -0.065 0.061 -0.002 -0.002
## t2_nf_s__ (a3) -0.029 0.035 -0.834 0.404 -0.097 0.039 -0.028 -0.028
## t3_inf_sha_att_w ~
## t2_pr_cn_ (b1) -0.024 0.038 -0.625 0.532 -0.098 0.050 -0.025 -0.025
## t2_nf_s__ (b2) 0.112 0.047 2.408 0.016 0.021 0.203 0.119 0.119
## t2_nf_s__ (b3) 0.049 0.036 1.354 0.176 -0.022 0.119 0.046 0.046
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (c1) 0.011 0.032 0.333 0.739 -0.052 0.073 0.013 0.013
## t2_nf_s__ (c2) -0.001 0.029 -0.021 0.983 -0.057 0.056 -0.001 -0.001
## t2_nf_s__ (c3) 0.056 0.041 1.353 0.176 -0.025 0.136 0.063 0.063
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b ~~
## inf_sh_tt_ -0.123 0.014 -8.823 0.000 -0.150 -0.095 -0.317 -0.317
## inf_sh_bh_ -0.053 0.013 -4.243 0.000 -0.078 -0.029 -0.142 -0.142
## inf_sha_beh_b ~~
## inf_sh_tt_ 0.172 0.011 15.824 0.000 0.151 0.194 0.679 0.679
## t1_pri_con_w ~~
## t1_nf_sh__ -0.010 0.008 -1.240 0.215 -0.025 0.006 -0.052 -0.052
## t1_nf_sh__ -0.016 0.007 -2.253 0.024 -0.030 -0.002 -0.094 -0.094
## t1_inf_sha_beh_w ~~
## t1_nf_sh__ 0.030 0.008 3.902 0.000 0.015 0.045 0.151 0.151
## .t2_pri_con_w ~~
## .t2_nf_sh__ (a) -0.005 0.007 -0.703 0.482 -0.018 0.009 -0.024 -0.024
## .t2_nf_sh__ (b) 0.006 0.006 0.943 0.346 -0.006 0.017 0.031 0.031
## .t2_inf_sha_beh_w ~~
## .t2_nf_sh__ (c) 0.029 0.006 4.609 0.000 0.016 0.041 0.155 0.155
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) -0.005 0.007 -0.703 0.482 -0.018 0.009 -0.027 -0.027
## .t3_nf_sh__ (b) 0.006 0.006 0.943 0.346 -0.006 0.017 0.037 0.037
## .t3_inf_sha_beh_w ~~
## .t3_nf_sh__ (c) 0.029 0.006 4.609 0.000 0.016 0.041 0.187 0.187
## pri_con_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 3.707 0.023 162.325 0.000 3.663 3.752 3.707 4.334
## .t2_pri_con_fs 3.636 0.023 155.386 0.000 3.590 3.682 3.636 4.148
## .t3_pri_con_fs 3.607 0.023 155.930 0.000 3.561 3.652 3.607 4.163
## .t1_nf_sh_bh_fs 2.193 0.017 125.641 0.000 2.159 2.228 2.193 3.354
## .t2_nf_sh_bh_fs 2.206 0.017 128.511 0.000 2.173 2.240 2.206 3.431
## .t3_nf_sh_bh_fs 2.168 0.016 132.315 0.000 2.136 2.201 2.168 3.532
## .t1_nf_sh_tt_fs 2.418 0.019 130.551 0.000 2.382 2.454 2.418 3.485
## .t2_nf_sh_tt_fs 2.482 0.018 135.718 0.000 2.446 2.518 2.482 3.623
## .t3_nf_sh_tt_fs 2.502 0.018 140.473 0.000 2.467 2.537 2.502 3.750
## pri_con_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b 0.000 0.000 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t2_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t2_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## pri_con_b 0.570 0.026 22.006 0.000 0.519 0.621 1.000 1.000
## inf_sha_beh_b 0.247 0.013 19.718 0.000 0.222 0.271 1.000 1.000
## inf_sha_att_b 0.261 0.015 16.978 0.000 0.231 0.292 1.000 1.000
## t1_pri_con_w 0.162 0.010 15.582 0.000 0.141 0.182 1.000 1.000
## .t2_pri_con_w 0.195 0.022 8.984 0.000 0.153 0.238 0.984 0.984
## .t3_pri_con_w 0.177 0.011 16.554 0.000 0.156 0.198 0.980 0.980
## t1_inf_sh_bh_w 0.181 0.010 18.562 0.000 0.162 0.200 1.000 1.000
## .t2_inf_sh_bh_w 0.166 0.012 14.182 0.000 0.143 0.189 0.997 0.997
## .t3_inf_sh_bh_w 0.130 0.008 17.086 0.000 0.115 0.144 0.996 0.996
## t1_inf_sh_tt_w 0.220 0.012 18.228 0.000 0.196 0.244 1.000 1.000
## .t2_inf_sh_tt_w 0.204 0.015 13.557 0.000 0.175 0.234 0.982 0.982
## .t3_inf_sh_tt_w 0.180 0.010 17.990 0.000 0.160 0.200 0.981 0.9812.1.2.4 Model 4 (final)
With Factor Scores and control variables. This is the final model we report in the paper.
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_fs + 1*t2_pri_con_fs + 1*t3_pri_con_fs
inf_sha_beh_b =~ 1*t1_inf_sha_beh_fs + 1*t2_inf_sha_beh_fs + 1*t3_inf_sha_beh_fs
inf_sha_att_b =~ 1*t1_inf_sha_att_fs + 1*t2_inf_sha_att_fs + 1*t3_inf_sha_att_fs
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_fs
t2_pri_con_w =~ 1*t2_pri_con_fs
t3_pri_con_w =~ 1*t3_pri_con_fs
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_fs
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_fs
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_fs
t1_inf_sha_att_w =~ 1*t1_inf_sha_att_fs
t2_inf_sha_att_w =~ 1*t2_inf_sha_att_fs
t3_inf_sha_att_w =~ 1*t3_inf_sha_att_fs
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_att_w + a3*t1_inf_sha_beh_w
t2_inf_sha_att_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_att_w + b3*t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ c1*t1_pri_con_w + c2*t1_inf_sha_att_w + c3*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + a2*t2_inf_sha_att_w + a3*t2_inf_sha_beh_w
t3_inf_sha_att_w ~ b1*t2_pri_con_w + b2*t2_inf_sha_att_w + b3*t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ c1*t2_pri_con_w + c2*t2_inf_sha_att_w + c3*t2_inf_sha_beh_w
# covariances
pri_con_b ~~ cor_b_1*inf_sha_att_b + cor_b_2*inf_sha_beh_b
inf_sha_att_b ~~ cor_b_3*inf_sha_beh_b
t1_pri_con_w ~~ cor_w_1*t1_inf_sha_att_w + cor_w_2*t1_inf_sha_beh_w
t1_inf_sha_att_w ~~ cor_w_3*t1_inf_sha_beh_w
t2_pri_con_w ~~ a*t2_inf_sha_att_w + b*t2_inf_sha_beh_w
t2_inf_sha_att_w ~~ c*t2_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_att_w + b*t3_inf_sha_beh_w
t3_inf_sha_att_w ~~ c*t3_inf_sha_beh_w
# setting variances of observed variables to zero
t1_pri_con_fs ~~ 0*t1_pri_con_fs
t2_pri_con_fs ~~ 0*t2_pri_con_fs
t3_pri_con_fs ~~ 0*t3_pri_con_fs
t1_inf_sha_att_fs ~~ 0*t1_inf_sha_att_fs
t2_inf_sha_att_fs ~~ 0*t2_inf_sha_att_fs
t3_inf_sha_att_fs ~~ 0*t3_inf_sha_att_fs
t1_inf_sha_beh_fs ~~ 0*t1_inf_sha_beh_fs
t2_inf_sha_beh_fs ~~ 0*t2_inf_sha_beh_fs
t3_inf_sha_beh_fs ~~ 0*t3_inf_sha_beh_fs
# control variables
t1_pri_con_fs ~ age + edu_num + male
t2_pri_con_fs ~ age + edu_num + male
t3_pri_con_fs ~ age + edu_num + male
t1_inf_sha_beh_fs ~ age + edu_num + male
t2_inf_sha_beh_fs ~ age + edu_num + male
t3_inf_sha_beh_fs ~ age + edu_num + male
t1_inf_sha_att_fs ~ age + edu_num + male
t2_inf_sha_att_fs ~ age + edu_num + male
t3_inf_sha_att_fs ~ age + edu_num + male
'
fit <- sem(model, data = d_wide, orthogonal = TRUE, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE, ci = TRUE)## lavaan 0.6-7 ended normally after 162 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 78
## Number of equality constraints 12
##
## Number of observations 1403
## Number of missing patterns 1
##
## Model Test User Model:
##
## Test statistic 25.184
## Degrees of freedom 15
## P-value (Chi-square) 0.048
##
## Model Test Baseline Model:
##
## Test statistic 7133.872
## Degrees of freedom 63
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.999
## Tucker-Lewis Index (TLI) 0.994
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -10247.004
## Loglikelihood unrestricted model (H1) -10234.413
##
## Akaike (AIC) 20626.009
## Bayesian (BIC) 20972.269
## Sample-size adjusted Bayesian (BIC) 20762.612
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.022
## 90 Percent confidence interval - lower 0.002
## 90 Percent confidence interval - upper 0.037
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.010
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b =~
## t1_pri_con_fs 1.000 1.000 1.000 0.737 0.862
## t2_pri_con_fs 1.000 1.000 1.000 0.737 0.840
## t3_pri_con_fs 1.000 1.000 1.000 0.737 0.849
## inf_sha_beh_b =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.466 0.713
## t2_nf_sh_bh_fs 1.000 1.000 1.000 0.466 0.726
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.466 0.757
## inf_sha_att_b =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.486 0.705
## t2_nf_sh_tt_fs 1.000 1.000 1.000 0.486 0.709
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.486 0.725
## t1_pri_con_w =~
## t1_pri_con_fs 1.000 1.000 1.000 0.402 0.471
## t2_pri_con_w =~
## t2_pri_con_fs 1.000 1.000 1.000 0.450 0.513
## t3_pri_con_w =~
## t3_pri_con_fs 1.000 1.000 1.000 0.426 0.490
## t1_inf_sha_beh_w =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.427 0.653
## t2_inf_sha_beh_w =~
## t2_nf_sh_bh_fs 1.000 1.000 1.000 0.403 0.628
## t3_inf_sha_beh_w =~
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.358 0.582
## t1_inf_sha_att_w =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.466 0.676
## t2_inf_sha_att_w =~
## t2_nf_sh_tt_fs 1.000 1.000 1.000 0.451 0.658
## t3_inf_sha_att_w =~
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.427 0.637
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.145 0.068 2.151 0.031 0.013 0.278 0.130 0.130
## t1_nf_s__ (a2) 0.002 0.032 0.062 0.951 -0.060 0.064 0.002 0.002
## t1_nf_s__ (a3) -0.028 0.034 -0.802 0.422 -0.095 0.040 -0.026 -0.026
## t2_inf_sha_att_w ~
## t1_pr_cn_ (b1) -0.017 0.037 -0.466 0.641 -0.090 0.055 -0.015 -0.015
## t1_nf_s__ (b2) 0.103 0.046 2.243 0.025 0.013 0.193 0.106 0.106
## t1_nf_s__ (b3) 0.040 0.035 1.152 0.249 -0.028 0.109 0.038 0.038
## t2_inf_sha_beh_w ~
## t1_pr_cn_ (c1) 0.013 0.031 0.409 0.683 -0.048 0.074 0.013 0.013
## t1_nf_s__ (c2) -0.002 0.028 -0.067 0.947 -0.057 0.053 -0.002 -0.002
## t1_nf_s__ (c3) 0.045 0.039 1.144 0.253 -0.032 0.122 0.048 0.048
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.145 0.068 2.151 0.031 0.013 0.278 0.154 0.154
## t2_nf_s__ (a2) 0.002 0.032 0.062 0.951 -0.060 0.064 0.002 0.002
## t2_nf_s__ (a3) -0.028 0.034 -0.802 0.422 -0.095 0.040 -0.026 -0.026
## t3_inf_sha_att_w ~
## t2_pr_cn_ (b1) -0.017 0.037 -0.466 0.641 -0.090 0.055 -0.018 -0.018
## t2_nf_s__ (b2) 0.103 0.046 2.243 0.025 0.013 0.193 0.109 0.109
## t2_nf_s__ (b3) 0.040 0.035 1.152 0.249 -0.028 0.109 0.038 0.038
## t3_inf_sha_beh_w ~
## t2_pr_cn_ (c1) 0.013 0.031 0.409 0.683 -0.048 0.074 0.016 0.016
## t2_nf_s__ (c2) -0.002 0.028 -0.067 0.947 -0.057 0.053 -0.002 -0.002
## t2_nf_s__ (c3) 0.045 0.039 1.144 0.253 -0.032 0.122 0.051 0.051
## t1_pri_con_fs ~
## age 0.010 0.001 6.847 0.000 0.007 0.013 0.010 0.184
## edu_num -0.023 0.013 -1.759 0.079 -0.049 0.003 -0.023 -0.047
## male -0.002 0.046 -0.043 0.966 -0.092 0.088 -0.002 -0.001
## t2_pri_con_fs ~
## age 0.010 0.002 6.510 0.000 0.007 0.013 0.010 0.175
## edu_num -0.023 0.013 -1.676 0.094 -0.049 0.004 -0.023 -0.045
## male 0.012 0.047 0.251 0.802 -0.081 0.105 0.012 0.007
## t3_pri_con_fs ~
## age 0.011 0.002 7.468 0.000 0.008 0.014 0.011 0.200
## edu_num -0.017 0.013 -1.310 0.190 -0.043 0.009 -0.017 -0.035
## male 0.010 0.047 0.220 0.826 -0.081 0.102 0.010 0.006
## t1_inf_sha_beh_fs ~
## age -0.009 0.001 -7.913 0.000 -0.011 -0.007 -0.009 -0.209
## edu_num 0.057 0.010 5.831 0.000 0.038 0.077 0.057 0.152
## male -0.132 0.035 -3.819 0.000 -0.200 -0.064 -0.132 -0.101
## t2_inf_sha_beh_fs ~
## age -0.010 0.001 -9.013 0.000 -0.012 -0.008 -0.010 -0.237
## edu_num 0.065 0.010 6.725 0.000 0.046 0.083 0.065 0.174
## male -0.083 0.034 -2.451 0.014 -0.149 -0.017 -0.083 -0.065
## t3_inf_sha_beh_fs ~
## age -0.009 0.001 -8.878 0.000 -0.011 -0.007 -0.009 -0.232
## edu_num 0.070 0.009 7.677 0.000 0.052 0.088 0.070 0.198
## male -0.121 0.032 -3.768 0.000 -0.185 -0.058 -0.121 -0.099
## t1_inf_sha_att_fs ~
## age -0.004 0.001 -3.599 0.000 -0.007 -0.002 -0.004 -0.096
## edu_num 0.031 0.011 2.989 0.003 0.011 0.052 0.031 0.079
## male -0.262 0.037 -7.083 0.000 -0.334 -0.189 -0.262 -0.190
## t2_inf_sha_att_fs ~
## age -0.006 0.001 -5.372 0.000 -0.009 -0.004 -0.006 -0.142
## edu_num 0.050 0.010 4.834 0.000 0.030 0.070 0.050 0.126
## male -0.263 0.036 -7.231 0.000 -0.334 -0.192 -0.263 -0.192
## t3_inf_sha_att_fs ~
## age -0.007 0.001 -6.188 0.000 -0.009 -0.005 -0.007 -0.163
## edu_num 0.051 0.010 5.100 0.000 0.032 0.071 0.051 0.133
## male -0.248 0.035 -6.984 0.000 -0.317 -0.178 -0.248 -0.185
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b ~~
## in___ (cr_b_1) -0.111 0.013 -8.462 0.000 -0.136 -0.085 -0.309 -0.309
## in___ (cr_b_2) -0.030 0.012 -2.573 0.010 -0.053 -0.007 -0.087 -0.087
## inf_sha_beh_b ~~
## in___ (cr_b_3) 0.149 0.010 15.116 0.000 0.130 0.168 0.657 0.657
## t1_pri_con_w ~~
## t1___ (cr_w_1) -0.011 0.008 -1.376 0.169 -0.026 0.005 -0.057 -0.057
## t1___ (cr_w_2) -0.017 0.007 -2.375 0.018 -0.031 -0.003 -0.100 -0.100
## t1_inf_sha_beh_w ~~
## t1___ (cr_w_3) 0.031 0.008 4.013 0.000 0.016 0.045 0.153 0.153
## .t2_pri_con_w ~~
## .t2___ (a) -0.003 0.007 -0.498 0.619 -0.017 0.010 -0.017 -0.017
## .t2___ (b) 0.006 0.006 1.049 0.294 -0.005 0.017 0.033 0.033
## .t2_inf_sha_beh_w ~~
## .t2___ (c) 0.027 0.006 4.542 0.000 0.015 0.039 0.149 0.149
## .t3_pri_con_w ~~
## .t3___ (a) -0.003 0.007 -0.498 0.619 -0.017 0.010 -0.019 -0.019
## .t3___ (b) 0.006 0.006 1.049 0.294 -0.005 0.017 0.040 0.040
## .t3_inf_sha_beh_w ~~
## .t3___ (c) 0.027 0.006 4.542 0.000 0.015 0.039 0.178 0.178
## pri_con_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 3.270 0.136 24.039 0.000 3.003 3.537 3.270 3.829
## .t2_pri_con_fs 3.189 0.140 22.798 0.000 2.914 3.463 3.189 3.638
## .t3_pri_con_fs 3.064 0.138 22.220 0.000 2.793 3.334 3.064 3.530
## .t1_nf_sh_bh_fs 2.583 0.102 25.230 0.000 2.382 2.783 2.583 3.952
## .t2_nf_sh_bh_fs 2.539 0.100 25.431 0.000 2.344 2.735 2.539 3.957
## .t3_nf_sh_bh_fs 2.497 0.095 26.225 0.000 2.310 2.684 2.497 4.057
## .t1_nf_sh_tt_fs 2.883 0.109 26.403 0.000 2.669 3.097 2.883 4.179
## .t2_nf_sh_tt_fs 2.964 0.107 27.586 0.000 2.754 3.175 2.964 4.324
## .t3_nf_sh_tt_fs 2.996 0.105 28.588 0.000 2.791 3.202 2.996 4.472
## pri_con_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b 0.000 0.000 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t2_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t2_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## pri_con_b 0.542 0.025 21.853 0.000 0.494 0.591 1.000 1.000
## inf_sha_beh_b 0.217 0.011 19.186 0.000 0.195 0.239 1.000 1.000
## inf_sha_att_b 0.236 0.014 16.522 0.000 0.208 0.264 1.000 1.000
## t1_pri_con_w 0.162 0.010 15.492 0.000 0.141 0.182 1.000 1.000
## .t2_pri_con_w 0.199 0.021 9.670 0.000 0.158 0.239 0.982 0.982
## .t3_pri_con_w 0.177 0.011 16.686 0.000 0.156 0.198 0.976 0.976
## t1_inf_sh_bh_w 0.182 0.010 18.768 0.000 0.163 0.201 1.000 1.000
## .t2_inf_sh_bh_w 0.162 0.011 14.695 0.000 0.141 0.184 0.998 0.998
## .t3_inf_sh_bh_w 0.128 0.007 17.307 0.000 0.113 0.142 0.997 0.997
## t1_inf_sh_tt_w 0.218 0.012 18.456 0.000 0.194 0.241 1.000 1.000
## .t2_inf_sh_tt_w 0.200 0.015 13.697 0.000 0.172 0.229 0.985 0.985
## .t3_inf_sh_tt_w 0.179 0.010 18.200 0.000 0.160 0.199 0.985 0.985fit_riclpm <- fit
effect_std_ci <- standardizedsolution(fit) %>%
filter(lhs == "pri_con_b", rhs == "inf_sha_beh_b")2.1.2.5 Model 5
Same model, but with unconstrained effects. That way, we can empirically test the assumption whether effects have changed over time. With Factor Scores, control variables, and 4 waves / 1 year intervals
model_free <- '
# between relations
pri_con_b =~ 1*t1_pri_con_fs + 1*t2_pri_con_fs + 1*t3_pri_con_fs
inf_sha_beh_b =~ 1*t1_inf_sha_beh_fs + 1*t2_inf_sha_beh_fs + 1*t3_inf_sha_beh_fs
inf_sha_att_b =~ 1*t1_inf_sha_att_fs + 1*t2_inf_sha_att_fs + 1*t3_inf_sha_att_fs
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_fs
t2_pri_con_w =~ 1*t2_pri_con_fs
t3_pri_con_w =~ 1*t3_pri_con_fs
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_fs
t2_inf_sha_beh_w =~ 1*t2_inf_sha_beh_fs
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_fs
t1_inf_sha_att_w =~ 1*t1_inf_sha_att_fs
t2_inf_sha_att_w =~ 1*t2_inf_sha_att_fs
t3_inf_sha_att_w =~ 1*t3_inf_sha_att_fs
# within person effects
t2_pri_con_w ~ a1*t1_pri_con_w + t1_inf_sha_att_w + t1_inf_sha_beh_w
t2_inf_sha_att_w ~ t1_pri_con_w + b2*t1_inf_sha_att_w + t1_inf_sha_beh_w
t2_inf_sha_beh_w ~ t1_pri_con_w + t1_inf_sha_att_w + c3*t1_inf_sha_beh_w
t3_pri_con_w ~ a1*t2_pri_con_w + t2_inf_sha_att_w + t2_inf_sha_beh_w
t3_inf_sha_att_w ~ t2_pri_con_w + b2*t2_inf_sha_att_w + t2_inf_sha_beh_w
t3_inf_sha_beh_w ~ t2_pri_con_w + t2_inf_sha_att_w + c3*t2_inf_sha_beh_w
# covariances
pri_con_b ~~ cor_b_1*inf_sha_att_b + cor_b_2*inf_sha_beh_b
inf_sha_att_b ~~ cor_b_3*inf_sha_beh_b
t1_pri_con_w ~~ cor_w_1*t1_inf_sha_att_w + cor_w_2*t1_inf_sha_beh_w
t1_inf_sha_att_w ~~ cor_w_3*t1_inf_sha_beh_w
t2_pri_con_w ~~ t2_inf_sha_att_w + t2_inf_sha_beh_w
t2_inf_sha_att_w ~~ t2_inf_sha_beh_w
t3_pri_con_w ~~ t3_inf_sha_att_w + t3_inf_sha_beh_w
t3_inf_sha_att_w ~~ t3_inf_sha_beh_w
# setting variances of observed variables to zero
t1_pri_con_fs ~~ 0*t1_pri_con_fs
t2_pri_con_fs ~~ 0*t2_pri_con_fs
t3_pri_con_fs ~~ 0*t3_pri_con_fs
t1_inf_sha_att_fs ~~ 0*t1_inf_sha_att_fs
t2_inf_sha_att_fs ~~ 0*t2_inf_sha_att_fs
t3_inf_sha_att_fs ~~ 0*t3_inf_sha_att_fs
t1_inf_sha_beh_fs ~~ 0*t1_inf_sha_beh_fs
t2_inf_sha_beh_fs ~~ 0*t2_inf_sha_beh_fs
t3_inf_sha_beh_fs ~~ 0*t3_inf_sha_beh_fs
# control variables
t1_pri_con_fs ~ age + edu_num + male
t2_pri_con_fs ~ age + edu_num + male
t3_pri_con_fs ~ age + edu_num + male
t1_inf_sha_beh_fs ~ age + edu_num + male
t2_inf_sha_beh_fs ~ age + edu_num + male
t3_inf_sha_beh_fs ~ age + edu_num + male
t1_inf_sha_att_fs ~ age + edu_num + male
t2_inf_sha_att_fs ~ age + edu_num + male
t3_inf_sha_att_fs ~ age + edu_num + male
'
fit_free <- sem(model_free, data = d_wide, orthogonal = TRUE, missing = "ML")
summary(fit_free, standardized = TRUE, fit.measures = TRUE, ci = TRUE)## lavaan 0.6-7 ended normally after 185 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 78
## Number of equality constraints 3
##
## Number of observations 1403
## Number of missing patterns 1
##
## Model Test User Model:
##
## Test statistic 10.935
## Degrees of freedom 6
## P-value (Chi-square) 0.090
##
## Model Test Baseline Model:
##
## Test statistic 7133.872
## Degrees of freedom 63
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.999
## Tucker-Lewis Index (TLI) 0.993
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -10239.880
## Loglikelihood unrestricted model (H1) -10234.413
##
## Akaike (AIC) 20629.760
## Bayesian (BIC) 21023.238
## Sample-size adjusted Bayesian (BIC) 20784.990
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.024
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.047
## P-value RMSEA <= 0.05 0.973
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.007
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b =~
## t1_pri_con_fs 1.000 1.000 1.000 0.734 0.860
## t2_pri_con_fs 1.000 1.000 1.000 0.734 0.838
## t3_pri_con_fs 1.000 1.000 1.000 0.734 0.846
## inf_sha_beh_b =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.469 0.719
## t2_nf_sh_bh_fs 1.000 1.000 1.000 0.469 0.734
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.469 0.756
## inf_sha_att_b =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.485 0.706
## t2_nf_sh_tt_fs 1.000 1.000 1.000 0.485 0.706
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.485 0.722
## t1_pri_con_w =~
## t1_pri_con_fs 1.000 1.000 1.000 0.406 0.475
## t2_pri_con_w =~
## t2_pri_con_fs 1.000 1.000 1.000 0.453 0.517
## t3_pri_con_w =~
## t3_pri_con_fs 1.000 1.000 1.000 0.429 0.495
## t1_inf_sha_beh_w =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.422 0.646
## t2_inf_sha_beh_w =~
## t2_nf_sh_bh_fs 1.000 1.000 1.000 0.394 0.617
## t3_inf_sha_beh_w =~
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.362 0.583
## t1_inf_sha_att_w =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.464 0.675
## t2_inf_sha_att_w =~
## t2_nf_sh_tt_fs 1.000 1.000 1.000 0.454 0.661
## t3_inf_sha_att_w =~
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.431 0.641
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## t2_pri_con_w ~
## t1_pr_cn_ (a1) 0.148 0.066 2.253 0.024 0.019 0.277 0.133 0.133
## t1_nf_s__ -0.050 0.048 -1.032 0.302 -0.144 0.045 -0.051 -0.051
## t1_nf_s__ -0.043 0.051 -0.845 0.398 -0.144 0.057 -0.040 -0.040
## t2_inf_sha_att_w ~
## t1_pr_cn_ -0.191 0.080 -2.403 0.016 -0.347 -0.035 -0.171 -0.171
## t1_nf_s__ (b2) 0.105 0.050 2.084 0.037 0.006 0.203 0.107 0.107
## t1_nf_s__ -0.035 0.050 -0.702 0.483 -0.133 0.063 -0.033 -0.033
## t2_inf_sha_beh_w ~
## t1_pr_cn_ -0.016 0.074 -0.211 0.833 -0.160 0.129 -0.016 -0.016
## t1_nf_s__ -0.055 0.041 -1.337 0.181 -0.135 0.026 -0.065 -0.065
## t1_nf_s__ (c3) 0.026 0.043 0.596 0.551 -0.059 0.110 0.028 0.028
## t3_pri_con_w ~
## t2_pr_cn_ (a1) 0.148 0.066 2.253 0.024 0.019 0.277 0.156 0.156
## t2_nf_s__ -0.073 0.060 -1.219 0.223 -0.189 0.044 -0.077 -0.077
## t2_nf_s__ -0.014 0.067 -0.216 0.829 -0.146 0.117 -0.013 -0.013
## t3_inf_sha_att_w ~
## t2_pr_cn_ -0.014 0.049 -0.296 0.767 -0.110 0.081 -0.015 -0.015
## t2_nf_s__ (b2) 0.105 0.050 2.084 0.037 0.006 0.203 0.111 0.111
## t2_nf_s__ 0.077 0.053 1.432 0.152 -0.028 0.181 0.070 0.070
## t3_inf_sha_beh_w ~
## t2_pr_cn_ 0.005 0.044 0.110 0.913 -0.082 0.092 0.006 0.006
## t2_nf_s__ 0.021 0.045 0.463 0.643 -0.067 0.109 0.026 0.026
## t2_nf_s__ (c3) 0.026 0.043 0.596 0.551 -0.059 0.110 0.028 0.028
## t1_pri_con_fs ~
## age 0.010 0.001 6.850 0.000 0.007 0.013 0.010 0.184
## edu_num -0.023 0.013 -1.760 0.078 -0.049 0.003 -0.023 -0.047
## male -0.002 0.046 -0.043 0.966 -0.092 0.088 -0.002 -0.001
## t2_pri_con_fs ~
## age 0.010 0.002 6.509 0.000 0.007 0.013 0.010 0.175
## edu_num -0.023 0.013 -1.676 0.094 -0.049 0.004 -0.023 -0.045
## male 0.012 0.047 0.251 0.802 -0.081 0.105 0.012 0.007
## t3_pri_con_fs ~
## age 0.011 0.002 7.468 0.000 0.008 0.014 0.011 0.200
## edu_num -0.017 0.013 -1.310 0.190 -0.043 0.009 -0.017 -0.035
## male 0.010 0.047 0.220 0.826 -0.081 0.102 0.010 0.006
## t1_inf_sha_beh_fs ~
## age -0.009 0.001 -7.926 0.000 -0.011 -0.007 -0.009 -0.209
## edu_num 0.057 0.010 5.840 0.000 0.038 0.077 0.057 0.153
## male -0.132 0.035 -3.825 0.000 -0.200 -0.065 -0.132 -0.101
## t2_inf_sha_beh_fs ~
## age -0.010 0.001 -9.064 0.000 -0.012 -0.008 -0.010 -0.238
## edu_num 0.065 0.010 6.763 0.000 0.046 0.083 0.065 0.175
## male -0.083 0.034 -2.465 0.014 -0.149 -0.017 -0.083 -0.065
## t3_inf_sha_beh_fs ~
## age -0.009 0.001 -8.808 0.000 -0.011 -0.007 -0.009 -0.230
## edu_num 0.070 0.009 7.617 0.000 0.052 0.088 0.070 0.197
## male -0.121 0.032 -3.738 0.000 -0.185 -0.058 -0.121 -0.098
## t1_inf_sha_att_fs ~
## age -0.004 0.001 -3.612 0.000 -0.007 -0.002 -0.004 -0.096
## edu_num 0.031 0.010 2.999 0.003 0.011 0.052 0.031 0.079
## male -0.262 0.037 -7.107 0.000 -0.334 -0.190 -0.262 -0.190
## t2_inf_sha_att_fs ~
## age -0.006 0.001 -5.361 0.000 -0.009 -0.004 -0.006 -0.142
## edu_num 0.050 0.010 4.824 0.000 0.030 0.070 0.050 0.126
## male -0.263 0.036 -7.217 0.000 -0.335 -0.192 -0.263 -0.191
## t3_inf_sha_att_fs ~
## age -0.007 0.001 -6.171 0.000 -0.009 -0.005 -0.007 -0.163
## edu_num 0.051 0.010 5.085 0.000 0.032 0.071 0.051 0.133
## male -0.248 0.036 -6.963 0.000 -0.318 -0.178 -0.248 -0.184
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b ~~
## in___ (cr_b_1) -0.100 0.014 -7.257 0.000 -0.128 -0.073 -0.282 -0.282
## in___ (cr_b_2) -0.028 0.012 -2.322 0.020 -0.052 -0.004 -0.081 -0.081
## inf_sha_beh_b ~~
## in___ (cr_b_3) 0.150 0.010 14.757 0.000 0.130 0.170 0.661 0.661
## t1_pri_con_w ~~
## t1___ (cr_w_1) -0.020 0.009 -2.106 0.035 -0.038 -0.001 -0.106 -0.106
## t1___ (cr_w_2) -0.020 0.009 -2.205 0.027 -0.038 -0.002 -0.117 -0.117
## t1_inf_sha_beh_w ~~
## t1___ (cr_w_3) 0.023 0.008 2.769 0.006 0.007 0.038 0.115 0.115
## .t2_pri_con_w ~~
## .t2___ -0.028 0.014 -2.073 0.038 -0.055 -0.002 -0.142 -0.142
## .t2___ 0.001 0.012 0.085 0.932 -0.022 0.024 0.006 0.006
## .t2_inf_sha_beh_w ~~
## .t2___ 0.019 0.011 1.797 0.072 -0.002 0.041 0.111 0.111
## .t3_pri_con_w ~~
## .t3___ 0.003 0.008 0.378 0.706 -0.013 0.018 0.017 0.017
## .t3___ 0.009 0.007 1.169 0.242 -0.006 0.023 0.057 0.057
## .t3_inf_sha_beh_w ~~
## .t3___ 0.036 0.007 5.168 0.000 0.022 0.050 0.235 0.235
## pri_con_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 3.270 0.136 24.049 0.000 3.004 3.537 3.270 3.830
## .t2_pri_con_fs 3.189 0.140 22.796 0.000 2.914 3.463 3.189 3.638
## .t3_pri_con_fs 3.064 0.138 22.221 0.000 2.793 3.334 3.064 3.530
## .t1_nf_sh_bh_fs 2.583 0.102 25.272 0.000 2.382 2.783 2.583 3.958
## .t2_nf_sh_bh_fs 2.539 0.099 25.575 0.000 2.345 2.734 2.539 3.977
## .t3_nf_sh_bh_fs 2.497 0.096 26.019 0.000 2.309 2.685 2.497 4.028
## .t1_nf_sh_tt_fs 2.883 0.109 26.494 0.000 2.669 3.096 2.883 4.192
## .t2_nf_sh_tt_fs 2.964 0.108 27.531 0.000 2.753 3.175 2.964 4.316
## .t3_nf_sh_tt_fs 2.996 0.105 28.506 0.000 2.790 3.202 2.996 4.460
## pri_con_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b 0.000 0.000 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t2_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t2_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t2_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t2_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## pri_con_b 0.539 0.025 21.832 0.000 0.491 0.588 1.000 1.000
## inf_sha_beh_b 0.220 0.011 19.154 0.000 0.197 0.242 1.000 1.000
## inf_sha_att_b 0.235 0.015 15.941 0.000 0.206 0.264 1.000 1.000
## t1_pri_con_w 0.164 0.011 15.252 0.000 0.143 0.186 1.000 1.000
## .t2_pri_con_w 0.200 0.020 9.980 0.000 0.161 0.240 0.975 0.975
## .t3_pri_con_w 0.178 0.011 16.735 0.000 0.157 0.199 0.965 0.965
## t1_inf_sh_bh_w 0.178 0.010 18.456 0.000 0.159 0.197 1.000 1.000
## .t2_inf_sh_bh_w 0.155 0.013 12.059 0.000 0.130 0.180 0.995 0.995
## .t3_inf_sh_bh_w 0.131 0.008 17.383 0.000 0.116 0.145 0.998 0.998
## t1_inf_sh_tt_w 0.215 0.012 17.811 0.000 0.192 0.239 1.000 1.000
## .t2_inf_sh_tt_w 0.197 0.017 11.660 0.000 0.164 0.230 0.957 0.957
## .t3_inf_sh_tt_w 0.182 0.010 18.035 0.000 0.162 0.201 0.980 0.980effect_std_ci_free <- standardizedsolution(fit) %>%
filter(lhs == "pri_con_b", rhs == "inf_sha_beh_b")
# model comparison
(model_comp <- anova(fit_riclpm, fit_free))Shows that model with freely estimated parameters does not show significantly improved fit.
2.1.2.6 Model 6
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_m + 1*t3_pri_con_m + 1*t4_pri_con_m + 1*t5_pri_con_m
inf_sha_beh_b =~ 1*t1_inf_sha_beh_m + 1*t3_inf_sha_beh_m + 1*t4_inf_sha_beh_m + 1*t5_inf_sha_beh_m
inf_sha_att_b =~ 1*t1_inf_sha_att_m + 1*t3_inf_sha_att_m + 1*t4_inf_sha_att_m + 1*t5_inf_sha_att_m
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_m
t3_pri_con_w =~ 1*t3_pri_con_m
t4_pri_con_w =~ 1*t4_pri_con_m
t5_pri_con_w =~ 1*t5_pri_con_m
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_m
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_m
t4_inf_sha_beh_w =~ 1*t4_inf_sha_beh_m
t5_inf_sha_beh_w =~ 1*t5_inf_sha_beh_m
t1_inf_sha_att_w =~ 1*t1_inf_sha_att_m
t3_inf_sha_att_w =~ 1*t3_inf_sha_att_m
t4_inf_sha_att_w =~ 1*t4_inf_sha_att_m
t5_inf_sha_att_w =~ 1*t5_inf_sha_att_m
# within person effects
t3_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_att_w + a3*t1_inf_sha_beh_w
t3_inf_sha_att_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_att_w + b3*t1_inf_sha_beh_w
t3_inf_sha_beh_w ~ c1*t1_pri_con_w + c2*t1_inf_sha_att_w + c3*t1_inf_sha_beh_w
t4_pri_con_w ~ a1*t3_pri_con_w + a2*t3_inf_sha_att_w + a3*t3_inf_sha_beh_w
t4_inf_sha_att_w ~ b1*t3_pri_con_w + b2*t3_inf_sha_att_w + b3*t3_inf_sha_beh_w
t4_inf_sha_beh_w ~ c1*t3_pri_con_w + c2*t3_inf_sha_att_w + c3*t3_inf_sha_beh_w
t5_pri_con_w ~ a1*t4_pri_con_w + a2*t4_inf_sha_att_w + a3*t4_inf_sha_beh_w
t5_inf_sha_att_w ~ b1*t4_pri_con_w + b2*t4_inf_sha_att_w + b3*t4_inf_sha_beh_w
t5_inf_sha_beh_w ~ c1*t4_pri_con_w + c2*t4_inf_sha_att_w + c3*t4_inf_sha_beh_w
# covariances
pri_con_b ~~ inf_sha_att_b + inf_sha_beh_b
inf_sha_att_b ~~ inf_sha_beh_b
t1_pri_con_w ~~ t1_inf_sha_att_w + t1_inf_sha_beh_w
t1_inf_sha_att_w ~~ t1_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_att_w + b*t3_inf_sha_beh_w
t3_inf_sha_att_w ~~ c*t3_inf_sha_beh_w
t4_pri_con_w ~~ a*t4_inf_sha_att_w + b*t4_inf_sha_beh_w
t4_inf_sha_att_w ~~ c*t4_inf_sha_beh_w
t5_pri_con_w ~~ a*t5_inf_sha_att_w + b*t5_inf_sha_beh_w
t5_inf_sha_att_w ~~ c*t5_inf_sha_beh_w
# setting variances of observed variables to zero
t1_pri_con_m ~~ 0*t1_pri_con_m
t3_pri_con_m ~~ 0*t3_pri_con_m
t4_pri_con_m ~~ 0*t4_pri_con_m
t5_pri_con_m ~~ 0*t5_pri_con_m
t1_inf_sha_att_m ~~ 0*t1_inf_sha_att_m
t3_inf_sha_att_m ~~ 0*t3_inf_sha_att_m
t4_inf_sha_att_m ~~ 0*t4_inf_sha_att_m
t5_inf_sha_att_m ~~ 0*t5_inf_sha_att_m
t1_inf_sha_beh_m ~~ 0*t1_inf_sha_beh_m
t3_inf_sha_beh_m ~~ 0*t3_inf_sha_beh_m
t4_inf_sha_beh_m ~~ 0*t4_inf_sha_beh_m
t5_inf_sha_beh_m ~~ 0*t5_inf_sha_beh_m
# control variables
t1_pri_con_m ~ age + edu_num + male
t3_pri_con_m ~ age + edu_num + male
t4_pri_con_m ~ age + edu_num + male
t5_pri_con_m ~ age + edu_num + male
t1_inf_sha_beh_m ~ age + edu_num + male
t3_inf_sha_beh_m ~ age + edu_num + male
t4_inf_sha_beh_m ~ age + edu_num + male
t5_inf_sha_beh_m ~ age + edu_num + male
t1_inf_sha_att_m ~ age + edu_num + male
t3_inf_sha_att_m ~ age + edu_num + male
t4_inf_sha_att_m ~ age + edu_num + male
t5_inf_sha_att_m ~ age + edu_num + male
'
fit <- sem(model, data = d_wide_all, orthogonal = TRUE, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE, ci = TRUE)## lavaan 0.6-7 ended normally after 194 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 105
## Number of equality constraints 24
##
## Used Total
## Number of observations 803 893
## Number of missing patterns 4
##
## Model Test User Model:
##
## Test statistic 245.361
## Degrees of freedom 45
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 4878.239
## Degrees of freedom 102
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.958
## Tucker-Lewis Index (TLI) 0.905
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -8739.515
## Loglikelihood unrestricted model (H1) -8616.835
##
## Akaike (AIC) 17641.030
## Bayesian (BIC) 18020.786
## Sample-size adjusted Bayesian (BIC) 17763.566
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.074
## 90 Percent confidence interval - lower 0.065
## 90 Percent confidence interval - upper 0.084
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.079
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b =~
## t1_pri_con_m 1.000 1.000 1.000 0.715 0.813
## t3_pri_con_m 1.000 1.000 1.000 0.715 0.822
## t4_pri_con_m 1.000 1.000 1.000 0.715 0.799
## t5_pri_con_m 1.000 1.000 1.000 0.715 0.801
## inf_sha_beh_b =~
## t1_inf_sh_bh_m 1.000 1.000 1.000 0.413 0.654
## t3_inf_sh_bh_m 1.000 1.000 1.000 0.413 0.718
## t4_inf_sh_bh_m 1.000 1.000 1.000 0.413 0.694
## t5_inf_sh_bh_m 1.000 1.000 1.000 0.413 0.278
## inf_sha_att_b =~
## t1_inf_sh_tt_m 1.000 1.000 1.000 0.479 0.681
## t3_inf_sh_tt_m 1.000 1.000 1.000 0.479 0.701
## t4_inf_sh_tt_m 1.000 1.000 1.000 0.479 0.730
## t5_inf_sh_tt_m 1.000 1.000 1.000 0.479 0.702
## t1_pri_con_w =~
## t1_pri_con_m 1.000 1.000 1.000 0.481 0.547
## t3_pri_con_w =~
## t3_pri_con_m 1.000 1.000 1.000 0.465 0.535
## t4_pri_con_w =~
## t4_pri_con_m 1.000 1.000 1.000 0.506 0.565
## t5_pri_con_w =~
## t5_pri_con_m 1.000 1.000 1.000 0.492 0.551
## t1_inf_sha_beh_w =~
## t1_inf_sh_bh_m 1.000 1.000 1.000 0.459 0.727
## t3_inf_sha_beh_w =~
## t3_inf_sh_bh_m 1.000 1.000 1.000 0.370 0.643
## t4_inf_sha_beh_w =~
## t4_inf_sh_bh_m 1.000 1.000 1.000 0.407 0.683
## t5_inf_sha_beh_w =~
## t5_inf_sh_bh_m 1.000 1.000 1.000 1.426 0.958
## t1_inf_sha_att_w =~
## t1_inf_sh_tt_m 1.000 1.000 1.000 0.496 0.705
## t3_inf_sha_att_w =~
## t3_inf_sh_tt_m 1.000 1.000 1.000 0.467 0.683
## t4_inf_sha_att_w =~
## t4_inf_sh_tt_m 1.000 1.000 1.000 0.425 0.648
## t5_inf_sha_att_w =~
## t5_inf_sh_tt_m 1.000 1.000 1.000 0.461 0.676
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## t3_pri_con_w ~
## t1_pr_cn_ (a1) 0.166 0.037 4.437 0.000 0.092 0.239 0.171 0.171
## t1_nf_s__ (a2) 0.016 0.030 0.541 0.588 -0.043 0.076 0.017 0.017
## t1_nf_s__ (a3) -0.025 0.036 -0.691 0.490 -0.096 0.046 -0.025 -0.025
## t3_inf_sha_att_w ~
## t1_pr_cn_ (b1) 0.037 0.028 1.304 0.192 -0.018 0.092 0.038 0.038
## t1_nf_s__ (b2) 0.071 0.035 2.055 0.040 0.003 0.139 0.076 0.076
## t1_nf_s__ (b3) 0.055 0.034 1.617 0.106 -0.012 0.122 0.054 0.054
## t3_inf_sha_beh_w ~
## t1_pr_cn_ (c1) -0.002 0.032 -0.056 0.956 -0.065 0.062 -0.002 -0.002
## t1_nf_s__ (c2) 0.003 0.031 0.113 0.910 -0.057 0.063 0.005 0.005
## t1_nf_s__ (c3) 0.069 0.053 1.302 0.193 -0.035 0.172 0.085 0.085
## t4_pri_con_w ~
## t3_pr_cn_ (a1) 0.166 0.037 4.437 0.000 0.092 0.239 0.152 0.152
## t3_nf_s__ (a2) 0.016 0.030 0.541 0.588 -0.043 0.076 0.015 0.015
## t3_nf_s__ (a3) -0.025 0.036 -0.691 0.490 -0.096 0.046 -0.018 -0.018
## t4_inf_sha_att_w ~
## t3_pr_cn_ (b1) 0.037 0.028 1.304 0.192 -0.018 0.092 0.040 0.040
## t3_nf_s__ (b2) 0.071 0.035 2.055 0.040 0.003 0.139 0.078 0.078
## t3_nf_s__ (b3) 0.055 0.034 1.617 0.106 -0.012 0.122 0.048 0.048
## t4_inf_sha_beh_w ~
## t3_pr_cn_ (c1) -0.002 0.032 -0.056 0.956 -0.065 0.062 -0.002 -0.002
## t3_nf_s__ (c2) 0.003 0.031 0.113 0.910 -0.057 0.063 0.004 0.004
## t3_nf_s__ (c3) 0.069 0.053 1.302 0.193 -0.035 0.172 0.062 0.062
## t5_pri_con_w ~
## t4_pr_cn_ (a1) 0.166 0.037 4.437 0.000 0.092 0.239 0.170 0.170
## t4_nf_s__ (a2) 0.016 0.030 0.541 0.588 -0.043 0.076 0.014 0.014
## t4_nf_s__ (a3) -0.025 0.036 -0.691 0.490 -0.096 0.046 -0.021 -0.021
## t5_inf_sha_att_w ~
## t4_pr_cn_ (b1) 0.037 0.028 1.304 0.192 -0.018 0.092 0.040 0.040
## t4_nf_s__ (b2) 0.071 0.035 2.055 0.040 0.003 0.139 0.066 0.066
## t4_nf_s__ (b3) 0.055 0.034 1.617 0.106 -0.012 0.122 0.049 0.049
## t5_inf_sha_beh_w ~
## t4_pr_cn_ (c1) -0.002 0.032 -0.056 0.956 -0.065 0.062 -0.001 -0.001
## t4_nf_s__ (c2) 0.003 0.031 0.113 0.910 -0.057 0.063 0.001 0.001
## t4_nf_s__ (c3) 0.069 0.053 1.302 0.193 -0.035 0.172 0.020 0.020
## t1_pri_con_m ~
## age 0.012 0.002 5.396 0.000 0.007 0.016 0.012 0.193
## edu_num -0.030 0.018 -1.726 0.084 -0.065 0.004 -0.030 -0.060
## male -0.028 0.063 -0.444 0.657 -0.152 0.096 -0.028 -0.016
## t3_pri_con_m ~
## age 0.011 0.002 5.280 0.000 0.007 0.016 0.011 0.189
## edu_num -0.040 0.017 -2.285 0.022 -0.074 -0.006 -0.040 -0.080
## male 0.002 0.063 0.026 0.979 -0.122 0.125 0.002 0.001
## t4_pri_con_m ~
## age 0.012 0.002 5.318 0.000 0.007 0.016 0.012 0.190
## edu_num -0.046 0.018 -2.561 0.010 -0.081 -0.011 -0.046 -0.090
## male -0.027 0.065 -0.414 0.679 -0.153 0.100 -0.027 -0.015
## t5_pri_con_m ~
## age 0.014 0.002 6.353 0.000 0.010 0.018 0.014 0.225
## edu_num -0.043 0.018 -2.431 0.015 -0.078 -0.008 -0.043 -0.084
## male -0.015 0.064 -0.232 0.816 -0.140 0.110 -0.015 -0.008
## t1_inf_sha_beh_m ~
## age -0.006 0.002 -4.021 0.000 -0.009 -0.003 -0.006 -0.143
## edu_num 0.050 0.013 3.921 0.000 0.025 0.074 0.050 0.137
## male -0.130 0.045 -2.859 0.004 -0.219 -0.041 -0.130 -0.102
## t3_inf_sha_beh_m ~
## age -0.007 0.001 -4.814 0.000 -0.009 -0.004 -0.007 -0.169
## edu_num 0.066 0.011 5.801 0.000 0.044 0.088 0.066 0.200
## male -0.121 0.041 -2.963 0.003 -0.201 -0.041 -0.121 -0.105
## t4_inf_sha_beh_m ~
## age -0.008 0.001 -5.165 0.000 -0.010 -0.005 -0.008 -0.183
## edu_num 0.055 0.012 4.595 0.000 0.031 0.078 0.055 0.160
## male -0.046 0.043 -1.087 0.277 -0.130 0.037 -0.046 -0.039
## t5_inf_sha_beh_m ~
## age 0.004 0.004 0.968 0.333 -0.004 0.011 0.004 0.035
## edu_num -0.050 0.030 -1.659 0.097 -0.110 0.009 -0.050 -0.059
## male 0.069 0.109 0.628 0.530 -0.145 0.283 0.069 0.023
## t1_inf_sha_att_m ~
## age -0.003 0.002 -1.787 0.074 -0.007 0.000 -0.003 -0.064
## edu_num 0.026 0.014 1.818 0.069 -0.002 0.053 0.026 0.064
## male -0.261 0.051 -5.147 0.000 -0.360 -0.162 -0.261 -0.185
## t3_inf_sha_att_m ~
## age -0.005 0.002 -2.934 0.003 -0.008 -0.002 -0.005 -0.105
## edu_num 0.045 0.014 3.288 0.001 0.018 0.072 0.045 0.115
## male -0.208 0.049 -4.239 0.000 -0.305 -0.112 -0.208 -0.152
## t4_inf_sha_att_m ~
## age -0.006 0.002 -3.454 0.001 -0.009 -0.002 -0.006 -0.123
## edu_num 0.044 0.013 3.364 0.001 0.018 0.070 0.044 0.117
## male -0.209 0.047 -4.435 0.000 -0.301 -0.117 -0.209 -0.158
## t5_inf_sha_att_m ~
## age -0.006 0.002 -3.860 0.000 -0.010 -0.003 -0.006 -0.137
## edu_num 0.051 0.014 3.769 0.000 0.025 0.078 0.051 0.131
## male -0.200 0.049 -4.088 0.000 -0.296 -0.104 -0.200 -0.146
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b ~~
## inf_sh_tt_ -0.110 0.016 -7.108 0.000 -0.141 -0.080 -0.323 -0.323
## inf_sh_bh_ -0.042 0.014 -3.038 0.002 -0.069 -0.015 -0.142 -0.142
## inf_sha_beh_b ~~
## inf_sh_tt_ 0.124 0.011 11.197 0.000 0.103 0.146 0.629 0.629
## t1_pri_con_w ~~
## t1_nf_sh__ -0.014 0.011 -1.217 0.224 -0.036 0.008 -0.057 -0.057
## t1_nf_sh__ -0.020 0.011 -1.859 0.063 -0.042 0.001 -0.092 -0.092
## t1_inf_sha_beh_w ~~
## t1_nf_sh__ 0.046 0.011 4.227 0.000 0.025 0.067 0.201 0.201
## .t3_pri_con_w ~~
## .t3_nf_sh__ (a) -0.010 0.006 -1.620 0.105 -0.023 0.002 -0.048 -0.048
## .t3_nf_sh__ (b) 0.001 0.007 0.164 0.870 -0.012 0.015 0.007 0.007
## .t3_inf_sha_beh_w ~~
## .t3_nf_sh__ (c) 0.039 0.006 6.001 0.000 0.026 0.051 0.226 0.226
## .t4_pri_con_w ~~
## .t4_nf_sh__ (a) -0.010 0.006 -1.620 0.105 -0.023 0.002 -0.048 -0.048
## .t4_nf_sh__ (b) 0.001 0.007 0.164 0.870 -0.012 0.015 0.006 0.006
## .t4_inf_sha_beh_w ~~
## .t4_nf_sh__ (c) 0.039 0.006 6.001 0.000 0.026 0.051 0.225 0.225
## .t5_pri_con_w ~~
## .t5_nf_sh__ (a) -0.010 0.006 -1.620 0.105 -0.023 0.002 -0.046 -0.046
## .t5_nf_sh__ (b) 0.001 0.007 0.164 0.870 -0.012 0.015 0.002 0.002
## .t5_inf_sha_beh_w ~~
## .t5_nf_sh__ (c) 0.039 0.006 6.001 0.000 0.026 0.051 0.059 0.059
## pri_con_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b ~~
## t1_pr_cn_w 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
## t1_nf_sh__ 0.000 0.000 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_m 3.192 0.196 16.312 0.000 2.808 3.575 3.192 3.629
## .t3_pri_con_m 3.140 0.194 16.163 0.000 2.759 3.520 3.140 3.607
## .t4_pri_con_m 3.131 0.199 15.723 0.000 2.741 3.521 3.131 3.500
## .t5_pri_con_m 2.935 0.197 14.896 0.000 2.549 3.321 2.935 3.288
## .t1_inf_sh_bh_m 2.426 0.140 17.296 0.000 2.151 2.701 2.426 3.841
## .t3_inf_sh_bh_m 2.341 0.126 18.590 0.000 2.095 2.588 2.341 4.069
## .t4_inf_sh_bh_m 2.382 0.132 18.095 0.000 2.124 2.640 2.382 3.997
## .t5_inf_sh_bh_m 2.708 0.337 8.030 0.000 2.047 3.368 2.708 1.819
## .t1_inf_sh_tt_m 2.809 0.156 17.956 0.000 2.503 3.116 2.809 3.996
## .t3_inf_sh_tt_m 2.823 0.152 18.598 0.000 2.525 3.120 2.823 4.132
## .t4_inf_sh_tt_m 2.769 0.145 19.044 0.000 2.484 3.054 2.769 4.220
## .t5_inf_sh_tt_m 2.814 0.151 18.647 0.000 2.518 3.109 2.814 4.127
## pri_con_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b 0.000 0.000 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t4_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t5_pri_con_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t4_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t5_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t4_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t5_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t4_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t5_pri_con_m 0.000 0.000 0.000 0.000 0.000
## .t1_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t4_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t5_inf_sh_tt_m 0.000 0.000 0.000 0.000 0.000
## .t1_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## .t4_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## .t5_inf_sh_bh_m 0.000 0.000 0.000 0.000 0.000
## pri_con_b 0.511 0.030 17.062 0.000 0.453 0.570 1.000 1.000
## inf_sha_beh_b 0.171 0.014 11.782 0.000 0.142 0.199 1.000 1.000
## inf_sha_att_b 0.229 0.015 15.046 0.000 0.199 0.259 1.000 1.000
## t1_pri_con_w 0.231 0.016 14.085 0.000 0.199 0.263 1.000 1.000
## .t3_pri_con_w 0.210 0.015 13.819 0.000 0.180 0.240 0.970 0.970
## .t4_pri_con_w 0.250 0.017 14.513 0.000 0.216 0.283 0.977 0.977
## .t5_pri_con_w 0.235 0.015 15.944 0.000 0.206 0.264 0.971 0.971
## t1_inf_sh_bh_w 0.211 0.015 13.672 0.000 0.181 0.241 1.000 1.000
## .t3_inf_sh_bh_w 0.136 0.013 10.650 0.000 0.111 0.161 0.993 0.993
## .t4_inf_sh_bh_w 0.165 0.011 14.906 0.000 0.143 0.186 0.996 0.996
## .t5_inf_sh_bh_w 2.034 0.103 19.672 0.000 1.831 2.237 1.000 1.000
## t1_inf_sh_tt_w 0.246 0.015 15.973 0.000 0.216 0.276 1.000 1.000
## .t3_inf_sh_tt_w 0.215 0.014 15.837 0.000 0.189 0.242 0.989 0.989
## .t4_inf_sh_tt_w 0.179 0.013 14.099 0.000 0.154 0.204 0.989 0.989
## .t5_inf_sh_tt_w 0.210 0.013 16.322 0.000 0.185 0.236 0.990 0.9902.1.2.7 Model 7 (longer intervals)
This is like the final model reported in the paper, but with other, that is longer, intervals. Now, waves are separated by 1 year and span until 2018.
We first need to redo the factor scores, because we now have a different sample.
Specifically, we first estimate a model containing all measures, which is then used to extract factor scores.
name <- "all_vars"
model <- '
# Privacy Concerns
# create factors
t1_pri_con_f =~ 1*t1_pri_con_f1 + a2*t1_pri_con_f2
t3_pri_con_f =~ 1*t3_pri_con_f1 + a2*t3_pri_con_f2
t4_pri_con_f =~ 1*t4_pri_con_f1 + a2*t4_pri_con_f2
t5_pri_con_f =~ 1*t5_pri_con_f1 + a2*t5_pri_con_f2
t1_pri_con_f1 =~ 1*t1_pri_con_04 + b2*t1_pri_con_05 + b3*t1_pri_con_06
t1_pri_con_f2 =~ 1*t1_pri_con_07 + c2*t1_pri_con_08 + c3*t1_pri_con_09
t3_pri_con_f1 =~ 1*t3_pri_con_04 + b2*t3_pri_con_05 + b3*t3_pri_con_06
t3_pri_con_f2 =~ 1*t3_pri_con_07 + c2*t3_pri_con_08 + c3*t3_pri_con_09
t4_pri_con_f1 =~ 1*t4_pri_con_04 + b2*t4_pri_con_05 + b3*t4_pri_con_06
t4_pri_con_f2 =~ 1*t4_pri_con_07 + c2*t4_pri_con_08 + c3*t4_pri_con_09
t5_pri_con_f1 =~ 1*t5_pri_con_04 + b2*t5_pri_con_05 + b3*t5_pri_con_06
t5_pri_con_f2 =~ 1*t5_pri_con_07 + c2*t5_pri_con_08 + c3*t5_pri_con_09
# error covariances
t5_pri_con_04 ~~ t4_pri_con_04 + t3_pri_con_04 + t1_pri_con_04
t5_pri_con_05 ~~ t4_pri_con_05 + t3_pri_con_05 + t1_pri_con_05
t5_pri_con_06 ~~ t4_pri_con_06 + t3_pri_con_06 + t1_pri_con_06
t5_pri_con_07 ~~ t4_pri_con_07 + t3_pri_con_07 + t1_pri_con_07
t5_pri_con_08 ~~ t4_pri_con_08 + t3_pri_con_08 + t1_pri_con_08
t5_pri_con_09 ~~ t4_pri_con_09 + t3_pri_con_09 + t1_pri_con_09
t4_pri_con_04 ~~ t3_pri_con_04 + t1_pri_con_04
t4_pri_con_05 ~~ t3_pri_con_05 + t1_pri_con_05
t4_pri_con_06 ~~ t3_pri_con_06 + t1_pri_con_06
t4_pri_con_07 ~~ t3_pri_con_07 + t1_pri_con_07
t4_pri_con_08 ~~ t3_pri_con_08 + t1_pri_con_08
t4_pri_con_09 ~~ t3_pri_con_09 + t1_pri_con_09
t3_pri_con_04 ~~ t1_pri_con_04
t3_pri_con_05 ~~ t1_pri_con_05
t3_pri_con_06 ~~ t1_pri_con_06
t3_pri_con_07 ~~ t1_pri_con_07
t3_pri_con_08 ~~ t1_pri_con_08
t3_pri_con_09 ~~ t1_pri_con_09
# factor covariances
t5_pri_con_f ~~ t1_pri_con_f + t3_pri_con_f + t4_pri_con_f
t1_pri_con_f ~~ t3_pri_con_f + t4_pri_con_f
t3_pri_con_f ~~ t4_pri_con_f
# Information Sharing Attitude
# create factors
t1_inf_sha_att_f =~ 1*t1_inf_sha_att_f1 + d2*t1_inf_sha_att_f2 + d3*t1_inf_sha_att_f3 + d4*t1_inf_sha_att_f4 + d5*t1_inf_sha_att_f5
t3_inf_sha_att_f =~ 1*t3_inf_sha_att_f1 + d2*t3_inf_sha_att_f2 + d3*t3_inf_sha_att_f3 + d4*t3_inf_sha_att_f4 + d5*t3_inf_sha_att_f5
t4_inf_sha_att_f =~ 1*t4_inf_sha_att_f1 + d2*t4_inf_sha_att_f2 + d3*t4_inf_sha_att_f3 + d4*t4_inf_sha_att_f4 + d5*t4_inf_sha_att_f5
t5_inf_sha_att_f =~ 1*t5_inf_sha_att_f1 + d2*t5_inf_sha_att_f2 + d3*t5_inf_sha_att_f3 + d4*t5_inf_sha_att_f4 + d5*t5_inf_sha_att_f5
t1_inf_sha_att_f1 =~ 1*t1_inf_sha_att_01 + e*t1_inf_sha_att_02
t1_inf_sha_att_f2 =~ 1*t1_inf_sha_att_03 + f*t1_inf_sha_att_04
t1_inf_sha_att_f3 =~ 1*t1_inf_sha_att_05 + g*t1_inf_sha_att_06
t1_inf_sha_att_f4 =~ 1*t1_inf_sha_att_07 + h*t1_inf_sha_att_08
t1_inf_sha_att_f5 =~ 1*t1_inf_sha_att_10 + i*t1_inf_sha_att_11
t3_inf_sha_att_f1 =~ 1*t3_inf_sha_att_01 + e*t3_inf_sha_att_02
t3_inf_sha_att_f2 =~ 1*t3_inf_sha_att_03 + f*t3_inf_sha_att_04
t3_inf_sha_att_f3 =~ 1*t3_inf_sha_att_05 + g*t3_inf_sha_att_06
t3_inf_sha_att_f4 =~ 1*t3_inf_sha_att_07 + h*t3_inf_sha_att_08
t3_inf_sha_att_f5 =~ 1*t3_inf_sha_att_10 + i*t3_inf_sha_att_11
t4_inf_sha_att_f1 =~ 1*t4_inf_sha_att_01 + e*t4_inf_sha_att_02
t4_inf_sha_att_f2 =~ 1*t4_inf_sha_att_03 + f*t4_inf_sha_att_04
t4_inf_sha_att_f3 =~ 1*t4_inf_sha_att_05 + g*t4_inf_sha_att_06
t4_inf_sha_att_f4 =~ 1*t4_inf_sha_att_07 + h*t4_inf_sha_att_08
t4_inf_sha_att_f5 =~ 1*t4_inf_sha_att_10 + i*t4_inf_sha_att_11
t5_inf_sha_att_f1 =~ 1*t5_inf_sha_att_01 + e*t5_inf_sha_att_02
t5_inf_sha_att_f2 =~ 1*t5_inf_sha_att_03 + f*t5_inf_sha_att_04
t5_inf_sha_att_f3 =~ 1*t5_inf_sha_att_05 + g*t5_inf_sha_att_06
t5_inf_sha_att_f4 =~ 1*t5_inf_sha_att_07 + h*t5_inf_sha_att_08
t5_inf_sha_att_f5 =~ 1*t5_inf_sha_att_10 + i*t5_inf_sha_att_11
# factor covariance
t5_inf_sha_att_f ~~ t1_inf_sha_att_f + t3_inf_sha_att_f + t4_inf_sha_att_f
t1_inf_sha_att_f ~~ t3_inf_sha_att_f + t4_inf_sha_att_f
t3_inf_sha_att_f ~~ t4_inf_sha_att_f
# item error covariance
t5_inf_sha_att_01 ~~ t1_inf_sha_att_01 + t3_inf_sha_att_01 + t4_inf_sha_att_01
t1_inf_sha_att_01 ~~ t3_inf_sha_att_01 + t4_inf_sha_att_01
t3_inf_sha_att_01 ~~ t4_inf_sha_att_01
t5_inf_sha_att_02 ~~ t1_inf_sha_att_02 + t3_inf_sha_att_02 + t4_inf_sha_att_02
t1_inf_sha_att_02 ~~ t3_inf_sha_att_02 + t4_inf_sha_att_02
t3_inf_sha_att_02 ~~ t4_inf_sha_att_02
t5_inf_sha_att_03 ~~ t1_inf_sha_att_03 + t3_inf_sha_att_03 + t4_inf_sha_att_03
t1_inf_sha_att_03 ~~ t3_inf_sha_att_03 + t4_inf_sha_att_03
t3_inf_sha_att_03 ~~ t4_inf_sha_att_03
t5_inf_sha_att_04 ~~ t1_inf_sha_att_04 + t3_inf_sha_att_04 + t4_inf_sha_att_04
t1_inf_sha_att_04 ~~ t3_inf_sha_att_04 + t4_inf_sha_att_04
t3_inf_sha_att_04 ~~ t4_inf_sha_att_04
t5_inf_sha_att_05 ~~ t1_inf_sha_att_05 + t3_inf_sha_att_05 + t4_inf_sha_att_05
t1_inf_sha_att_05 ~~ t3_inf_sha_att_05 + t4_inf_sha_att_05
t3_inf_sha_att_05 ~~ t4_inf_sha_att_05
t5_inf_sha_att_06 ~~ t1_inf_sha_att_06 + t3_inf_sha_att_06 + t4_inf_sha_att_06
t1_inf_sha_att_06 ~~ t3_inf_sha_att_06 + t4_inf_sha_att_06
t3_inf_sha_att_06 ~~ t4_inf_sha_att_06
t5_inf_sha_att_07 ~~ t1_inf_sha_att_07 + t3_inf_sha_att_07 + t4_inf_sha_att_07
t1_inf_sha_att_07 ~~ t3_inf_sha_att_07 + t4_inf_sha_att_07
t3_inf_sha_att_07 ~~ t4_inf_sha_att_07
t5_inf_sha_att_08 ~~ t1_inf_sha_att_08 + t3_inf_sha_att_08 + t4_inf_sha_att_08
t1_inf_sha_att_08 ~~ t3_inf_sha_att_08 + t4_inf_sha_att_08
t3_inf_sha_att_08 ~~ t4_inf_sha_att_08
t5_inf_sha_att_10 ~~ t1_inf_sha_att_10 + t3_inf_sha_att_10 + t4_inf_sha_att_10
t1_inf_sha_att_10 ~~ t3_inf_sha_att_10 + t4_inf_sha_att_10
t3_inf_sha_att_10 ~~ t4_inf_sha_att_10
t5_inf_sha_att_11 ~~ t1_inf_sha_att_11 + t3_inf_sha_att_11 + t4_inf_sha_att_11
t1_inf_sha_att_11 ~~ t3_inf_sha_att_11 + t4_inf_sha_att_11
t3_inf_sha_att_11 ~~ t4_inf_sha_att_11
# information sharing behavior
# create factors
t1_inf_sha_beh_f =~ 1*t1_inf_sha_beh_f1 + o2*t1_inf_sha_beh_f2 + o3*t1_inf_sha_beh_f3 + o4*t1_inf_sha_beh_f4 + o5*t1_inf_sha_beh_f5
t3_inf_sha_beh_f =~ 1*t3_inf_sha_beh_f1 + o2*t3_inf_sha_beh_f2 + o3*t3_inf_sha_beh_f3 + o4*t3_inf_sha_beh_f4 + o5*t3_inf_sha_beh_f5
t4_inf_sha_beh_f =~ 1*t4_inf_sha_beh_f1 + o2*t4_inf_sha_beh_f2 + o3*t4_inf_sha_beh_f3 + o4*t4_inf_sha_beh_f4 + o5*t4_inf_sha_beh_f5
t5_inf_sha_beh_f =~ 1*t5_inf_sha_beh_f1 + o2*t5_inf_sha_beh_f2 + o3*t5_inf_sha_beh_f3 + o4*t5_inf_sha_beh_f4 + o5*t5_inf_sha_beh_f5
t1_inf_sha_beh_f1 =~ 1*t1_inf_sha_beh_01 + j2*t1_inf_sha_beh_02
t1_inf_sha_beh_f2 =~ 1*t1_inf_sha_beh_03 + k2*t1_inf_sha_beh_04
t1_inf_sha_beh_f3 =~ 1*t1_inf_sha_beh_05 + l2*t1_inf_sha_beh_06
t1_inf_sha_beh_f4 =~ 1*t1_inf_sha_beh_07 + m2*t1_inf_sha_beh_08
t1_inf_sha_beh_f5 =~ 1*t1_inf_sha_beh_10 + n2*t1_inf_sha_beh_11
t3_inf_sha_beh_f1 =~ 1*t3_inf_sha_beh_01 + j2*t3_inf_sha_beh_02
t3_inf_sha_beh_f2 =~ 1*t3_inf_sha_beh_03 + k2*t3_inf_sha_beh_04
t3_inf_sha_beh_f3 =~ 1*t3_inf_sha_beh_05 + l2*t3_inf_sha_beh_06
t3_inf_sha_beh_f4 =~ 1*t3_inf_sha_beh_07 + m2*t3_inf_sha_beh_08
t3_inf_sha_beh_f5 =~ 1*t3_inf_sha_beh_10 + n2*t3_inf_sha_beh_11
t4_inf_sha_beh_f1 =~ 1*t4_inf_sha_beh_01 + j2*t4_inf_sha_beh_02
t4_inf_sha_beh_f2 =~ 1*t4_inf_sha_beh_03 + k2*t4_inf_sha_beh_04
t4_inf_sha_beh_f3 =~ 1*t4_inf_sha_beh_05 + l2*t4_inf_sha_beh_06
t4_inf_sha_beh_f4 =~ 1*t4_inf_sha_beh_07 + m2*t4_inf_sha_beh_08
t4_inf_sha_beh_f5 =~ 1*t4_inf_sha_beh_10 + n2*t4_inf_sha_beh_11
t5_inf_sha_beh_f1 =~ 1*t5_inf_sha_beh_01 + j2*t5_inf_sha_beh_02
t5_inf_sha_beh_f2 =~ 1*t5_inf_sha_beh_03 + k2*t5_inf_sha_beh_04
t5_inf_sha_beh_f3 =~ 1*t5_inf_sha_beh_05 + l2*t5_inf_sha_beh_06
t5_inf_sha_beh_f4 =~ 1*t5_inf_sha_beh_07 + m2*t5_inf_sha_beh_08
t5_inf_sha_beh_f5 =~ 1*t5_inf_sha_beh_10 + n2*t5_inf_sha_beh_11
# factor covariance
t5_inf_sha_beh_f ~~ t1_inf_sha_beh_f + t3_inf_sha_beh_f + t4_inf_sha_beh_f
t1_inf_sha_beh_f ~~ t3_inf_sha_beh_f + t4_inf_sha_beh_f
t3_inf_sha_beh_f ~~ t4_inf_sha_beh_f
# item error covariance
t5_inf_sha_beh_01 ~~ t1_inf_sha_beh_01 + t3_inf_sha_beh_01 + t4_inf_sha_beh_01
t1_inf_sha_beh_01 ~~ t3_inf_sha_beh_01 + t4_inf_sha_beh_01
t3_inf_sha_beh_01 ~~ t4_inf_sha_beh_01
t5_inf_sha_beh_02 ~~ t1_inf_sha_beh_02 + t3_inf_sha_beh_02 + t4_inf_sha_beh_02
t1_inf_sha_beh_02 ~~ t3_inf_sha_beh_02 + t4_inf_sha_beh_02
t3_inf_sha_beh_02 ~~ t4_inf_sha_beh_02
t5_inf_sha_beh_03 ~~ t1_inf_sha_beh_03 + t3_inf_sha_beh_03 + t4_inf_sha_beh_03
t1_inf_sha_beh_03 ~~ t3_inf_sha_beh_03 + t4_inf_sha_beh_03
t3_inf_sha_beh_03 ~~ t4_inf_sha_beh_03
t5_inf_sha_beh_04 ~~ t1_inf_sha_beh_04 + t3_inf_sha_beh_04 + t4_inf_sha_beh_04
t1_inf_sha_beh_04 ~~ t3_inf_sha_beh_04 + t4_inf_sha_beh_04
t3_inf_sha_beh_04 ~~ t4_inf_sha_beh_04
t5_inf_sha_beh_05 ~~ t1_inf_sha_beh_05 + t3_inf_sha_beh_05 + t4_inf_sha_beh_05
t1_inf_sha_beh_05 ~~ t3_inf_sha_beh_05 + t4_inf_sha_beh_05
t3_inf_sha_beh_05 ~~ t4_inf_sha_beh_05
t5_inf_sha_beh_06 ~~ t1_inf_sha_beh_06 + t3_inf_sha_beh_06 + t4_inf_sha_beh_06
t1_inf_sha_beh_06 ~~ t3_inf_sha_beh_06 + t4_inf_sha_beh_06
t3_inf_sha_beh_06 ~~ t4_inf_sha_beh_06
t5_inf_sha_beh_07 ~~ t1_inf_sha_beh_07 + t3_inf_sha_beh_07 + t4_inf_sha_beh_07
t1_inf_sha_beh_07 ~~ t3_inf_sha_beh_07 + t4_inf_sha_beh_07
t3_inf_sha_beh_07 ~~ t4_inf_sha_beh_07
t5_inf_sha_beh_08 ~~ t1_inf_sha_beh_08 + t3_inf_sha_beh_08 + t4_inf_sha_beh_08
t1_inf_sha_beh_08 ~~ t3_inf_sha_beh_08 + t4_inf_sha_beh_08
t3_inf_sha_beh_08 ~~ t4_inf_sha_beh_08
t5_inf_sha_beh_10 ~~ t1_inf_sha_beh_10 + t3_inf_sha_beh_10 + t4_inf_sha_beh_10
t1_inf_sha_beh_10 ~~ t3_inf_sha_beh_10 + t4_inf_sha_beh_10
t3_inf_sha_beh_10 ~~ t4_inf_sha_beh_10
t5_inf_sha_beh_11 ~~ t1_inf_sha_beh_11 + t3_inf_sha_beh_11 + t4_inf_sha_beh_11
t1_inf_sha_beh_11 ~~ t3_inf_sha_beh_11 + t4_inf_sha_beh_11
t3_inf_sha_beh_11 ~~ t4_inf_sha_beh_11
## Correlations Attitude and Behavior-Items
t1_inf_sha_beh_01 ~~ t1_inf_sha_att_01
t1_inf_sha_beh_02 ~~ t1_inf_sha_att_02
t1_inf_sha_beh_03 ~~ t1_inf_sha_att_03
t1_inf_sha_beh_04 ~~ t1_inf_sha_att_04
t1_inf_sha_beh_05 ~~ t1_inf_sha_att_05
t1_inf_sha_beh_06 ~~ t1_inf_sha_att_06
t1_inf_sha_beh_07 ~~ t1_inf_sha_att_07
t1_inf_sha_beh_08 ~~ t1_inf_sha_att_08
t1_inf_sha_beh_10 ~~ t1_inf_sha_att_10
t1_inf_sha_beh_11 ~~ t1_inf_sha_att_11
t3_inf_sha_beh_01 ~~ t3_inf_sha_att_01
t3_inf_sha_beh_02 ~~ t3_inf_sha_att_02
t3_inf_sha_beh_03 ~~ t3_inf_sha_att_03
t3_inf_sha_beh_04 ~~ t3_inf_sha_att_04
t3_inf_sha_beh_05 ~~ t3_inf_sha_att_05
t3_inf_sha_beh_06 ~~ t3_inf_sha_att_06
t3_inf_sha_beh_07 ~~ t3_inf_sha_att_07
t3_inf_sha_beh_08 ~~ t3_inf_sha_att_08
t3_inf_sha_beh_10 ~~ t3_inf_sha_att_10
t3_inf_sha_beh_11 ~~ t3_inf_sha_att_11
t4_inf_sha_beh_01 ~~ t4_inf_sha_att_01
t4_inf_sha_beh_02 ~~ t4_inf_sha_att_02
t4_inf_sha_beh_03 ~~ t4_inf_sha_att_03
t4_inf_sha_beh_04 ~~ t4_inf_sha_att_04
t4_inf_sha_beh_05 ~~ t4_inf_sha_att_05
t4_inf_sha_beh_06 ~~ t4_inf_sha_att_06
t4_inf_sha_beh_07 ~~ t4_inf_sha_att_07
t4_inf_sha_beh_08 ~~ t4_inf_sha_att_08
t4_inf_sha_beh_10 ~~ t4_inf_sha_att_10
t4_inf_sha_beh_11 ~~ t4_inf_sha_att_11
t5_inf_sha_beh_01 ~~ t5_inf_sha_att_01
t5_inf_sha_beh_02 ~~ t5_inf_sha_att_02
t5_inf_sha_beh_03 ~~ t5_inf_sha_att_03
t5_inf_sha_beh_04 ~~ t5_inf_sha_att_04
t5_inf_sha_beh_05 ~~ t5_inf_sha_att_05
t5_inf_sha_beh_06 ~~ t5_inf_sha_att_06
t5_inf_sha_beh_07 ~~ t5_inf_sha_att_07
t5_inf_sha_beh_08 ~~ t5_inf_sha_att_08
t5_inf_sha_beh_10 ~~ t5_inf_sha_att_10
t5_inf_sha_beh_11 ~~ t5_inf_sha_att_11
'
assign(paste("fit", name, sep = "_"), cfa(model, d_wide_all, missing = "ML"))
summary(get(paste("fit", name, sep = "_")), standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 439 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 622
## Number of equality constraints 69
##
## Number of observations 893
## Number of missing patterns 110
##
## Model Test User Model:
##
## Test statistic 13924.019
## Degrees of freedom 5011
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 90895.859
## Degrees of freedom 5356
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.896
## Tucker-Lewis Index (TLI) 0.889
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -98960.788
## Loglikelihood unrestricted model (H1) -91998.778
##
## Akaike (AIC) 199027.576
## Bayesian (BIC) 201678.982
## Sample-size adjusted Bayesian (BIC) 199922.755
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.045
## 90 Percent confidence interval - lower 0.044
## 90 Percent confidence interval - upper 0.046
## P-value RMSEA <= 0.05 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.071
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## t1_pri_con_f =~
## t1_pr_c_1 1.000 0.932 0.932
## t1_pr_c_2 (a2) 1.158 0.032 36.640 0.000 0.945 0.945
## t3_pri_con_f =~
## t3_pr_c_1 1.000 0.988 0.988
## t3_pr_c_2 (a2) 1.158 0.032 36.640 0.000 0.944 0.944
## t4_pri_con_f =~
## t4_pr_c_1 1.000 0.963 0.963
## t4_pr_c_2 (a2) 1.158 0.032 36.640 0.000 0.968 0.968
## t5_pri_con_f =~
## t5_pr_c_1 1.000 0.949 0.949
## t5_pr_c_2 (a2) 1.158 0.032 36.640 0.000 0.971 0.971
## t1_pri_con_f1 =~
## t1_pr__04 1.000 0.878 0.830
## t1_pr__05 (b2) 0.974 0.030 32.777 0.000 0.855 0.654
## t1_pr__06 (b3) 1.009 0.025 40.371 0.000 0.886 0.755
## t1_pri_con_f2 =~
## t1_pr__07 1.000 1.002 0.798
## t1_pr__08 (c2) 0.970 0.021 46.262 0.000 0.973 0.833
## t1_pr__09 (c3) 0.878 0.019 45.198 0.000 0.880 0.841
## t3_pri_con_f1 =~
## t3_pr__04 1.000 0.846 0.801
## t3_pr__05 (b2) 0.974 0.030 32.777 0.000 0.825 0.631
## t3_pr__06 (b3) 1.009 0.025 40.371 0.000 0.854 0.756
## t3_pri_con_f2 =~
## t3_pr__07 1.000 1.026 0.828
## t3_pr__08 (c2) 0.970 0.021 46.262 0.000 0.995 0.857
## t3_pr__09 (c3) 0.878 0.019 45.198 0.000 0.901 0.840
## t4_pri_con_f1 =~
## t4_pr__04 1.000 0.870 0.818
## t4_pr__05 (b2) 0.974 0.030 32.777 0.000 0.847 0.657
## t4_pr__06 (b3) 1.009 0.025 40.371 0.000 0.878 0.776
## t4_pri_con_f2 =~
## t4_pr__07 1.000 1.002 0.813
## t4_pr__08 (c2) 0.970 0.021 46.262 0.000 0.972 0.850
## t4_pr__09 (c3) 0.878 0.019 45.198 0.000 0.879 0.826
## t5_pri_con_f1 =~
## t5_pr__04 1.000 0.905 0.849
## t5_pr__05 (b2) 0.974 0.030 32.777 0.000 0.881 0.667
## t5_pr__06 (b3) 1.009 0.025 40.371 0.000 0.913 0.794
## t5_pri_con_f2 =~
## t5_pr__07 1.000 1.024 0.816
## t5_pr__08 (c2) 0.970 0.021 46.262 0.000 0.994 0.856
## t5_pr__09 (c3) 0.878 0.019 45.198 0.000 0.899 0.842
## t1_inf_sha_att_f =~
## t1_nf___1 1.000 0.468 0.468
## t1_nf___2 (d2) 2.544 0.165 15.405 0.000 0.960 0.960
## t1_nf___3 (d3) 2.610 0.169 15.421 0.000 0.931 0.931
## t1_nf___4 (d4) 2.116 0.141 14.977 0.000 0.893 0.893
## t1_nf___5 (d5) 1.426 0.104 13.771 0.000 0.517 0.517
## t3_inf_sha_att_f =~
## t3_nf___1 1.000 0.480 0.480
## t3_nf___2 (d2) 2.544 0.165 15.405 0.000 0.919 0.919
## t3_nf___3 (d3) 2.610 0.169 15.421 0.000 0.939 0.939
## t3_nf___4 (d4) 2.116 0.141 14.977 0.000 0.924 0.924
## t3_nf___5 (d5) 1.426 0.104 13.771 0.000 0.502 0.502
## t4_inf_sha_att_f =~
## t4_nf___1 1.000 0.422 0.422
## t4_nf___2 (d2) 2.544 0.165 15.405 0.000 0.976 0.976
## t4_nf___3 (d3) 2.610 0.169 15.421 0.000 0.917 0.917
## t4_nf___4 (d4) 2.116 0.141 14.977 0.000 0.912 0.912
## t4_nf___5 (d5) 1.426 0.104 13.771 0.000 0.488 0.488
## t5_inf_sha_att_f =~
## t5_nf___1 1.000 0.417 0.417
## t5_nf___2 (d2) 2.544 0.165 15.405 0.000 1.022 1.022
## t5_nf___3 (d3) 2.610 0.169 15.421 0.000 0.901 0.901
## t5_nf___4 (d4) 2.116 0.141 14.977 0.000 0.945 0.945
## t5_nf___5 (d5) 1.426 0.104 13.771 0.000 0.493 0.493
## t1_inf_sha_att_f1 =~
## t1_n___01 1.000 0.761 0.677
## t1_n___02 (e) 0.906 0.064 14.093 0.000 0.689 0.625
## t1_inf_sha_att_f2 =~
## t1_n___03 1.000 0.944 0.912
## t1_n___04 (f) 0.980 0.016 61.381 0.000 0.926 0.902
## t1_inf_sha_att_f3 =~
## t1_n___05 1.000 0.999 0.949
## t1_n___06 (g) 0.959 0.015 65.861 0.000 0.958 0.883
## t1_inf_sha_att_f4 =~
## t1_n___07 1.000 0.844 0.778
## t1_n___08 (h) 0.881 0.027 32.760 0.000 0.744 0.700
## t1_inf_sha_att_f5 =~
## t1_n___10 1.000 0.982 0.912
## t1_n___11 (i) 0.977 0.023 43.310 0.000 0.960 0.912
## t3_inf_sha_att_f1 =~
## t3_n___01 1.000 0.712 0.636
## t3_n___02 (e) 0.906 0.064 14.093 0.000 0.645 0.610
## t3_inf_sha_att_f2 =~
## t3_n___03 1.000 0.946 0.927
## t3_n___04 (f) 0.980 0.016 61.381 0.000 0.927 0.902
## t3_inf_sha_att_f3 =~
## t3_n___05 1.000 0.950 0.921
## t3_n___06 (g) 0.959 0.015 65.861 0.000 0.911 0.859
## t3_inf_sha_att_f4 =~
## t3_n___07 1.000 0.783 0.743
## t3_n___08 (h) 0.881 0.027 32.760 0.000 0.690 0.667
## t3_inf_sha_att_f5 =~
## t3_n___10 1.000 0.972 0.937
## t3_n___11 (i) 0.977 0.023 43.310 0.000 0.950 0.914
## t4_inf_sha_att_f1 =~
## t4_n___01 1.000 0.756 0.625
## t4_n___02 (e) 0.906 0.064 14.093 0.000 0.685 0.634
## t4_inf_sha_att_f2 =~
## t4_n___03 1.000 0.831 0.761
## t4_n___04 (f) 0.980 0.016 61.381 0.000 0.815 0.800
## t4_inf_sha_att_f3 =~
## t4_n___05 1.000 0.908 0.923
## t4_n___06 (g) 0.959 0.015 65.861 0.000 0.870 0.848
## t4_inf_sha_att_f4 =~
## t4_n___07 1.000 0.740 0.721
## t4_n___08 (h) 0.881 0.027 32.760 0.000 0.652 0.640
## t4_inf_sha_att_f5 =~
## t4_n___10 1.000 0.932 0.928
## t4_n___11 (i) 0.977 0.023 43.310 0.000 0.911 0.915
## t5_inf_sha_att_f1 =~
## t5_n___01 1.000 0.784 0.647
## t5_n___02 (e) 0.906 0.064 14.093 0.000 0.710 0.648
## t5_inf_sha_att_f2 =~
## t5_n___03 1.000 0.814 0.749
## t5_n___04 (f) 0.980 0.016 61.381 0.000 0.798 0.786
## t5_inf_sha_att_f3 =~
## t5_n___05 1.000 0.947 0.949
## t5_n___06 (g) 0.959 0.015 65.861 0.000 0.908 0.850
## t5_inf_sha_att_f4 =~
## t5_n___07 1.000 0.733 0.712
## t5_n___08 (h) 0.881 0.027 32.760 0.000 0.646 0.635
## t5_inf_sha_att_f5 =~
## t5_n___10 1.000 0.947 0.947
## t5_n___11 (i) 0.977 0.023 43.310 0.000 0.926 0.916
## t1_inf_sha_beh_f =~
## t1_nf___1 1.000 0.616 0.616
## t1_nf___2 (o2) 2.365 0.109 21.642 0.000 0.931 0.931
## t1_nf___3 (o3) 2.328 0.107 21.777 0.000 0.948 0.948
## t1_nf___4 (o4) 2.149 0.101 21.195 0.000 0.991 0.991
## t1_nf___5 (o5) 1.236 0.067 18.328 0.000 0.567 0.567
## t3_inf_sha_beh_f =~
## t3_nf___1 1.000 0.666 0.666
## t3_nf___2 (o2) 2.365 0.109 21.642 0.000 0.931 0.931
## t3_nf___3 (o3) 2.328 0.107 21.777 0.000 0.938 0.938
## t3_nf___4 (o4) 2.149 0.101 21.195 0.000 0.948 0.948
## t3_nf___5 (o5) 1.236 0.067 18.328 0.000 0.545 0.545
## t4_inf_sha_beh_f =~
## t4_nf___1 1.000 0.522 0.522
## t4_nf___2 (o2) 2.365 0.109 21.642 0.000 0.924 0.924
## t4_nf___3 (o3) 2.328 0.107 21.777 0.000 0.922 0.922
## t4_nf___4 (o4) 2.149 0.101 21.195 0.000 0.993 0.993
## t4_nf___5 (o5) 1.236 0.067 18.328 0.000 0.544 0.544
## t5_inf_sha_beh_f =~
## t5_nf___1 1.000 0.254 0.254
## t5_nf___2 (o2) 2.365 0.109 21.642 0.000 0.993 0.993
## t5_nf___3 (o3) 2.328 0.107 21.777 0.000 0.965 0.965
## t5_nf___4 (o4) 2.149 0.101 21.195 0.000 0.991 0.991
## t5_nf___5 (o5) 1.236 0.067 18.328 0.000 0.472 0.472
## t1_inf_sha_beh_f1 =~
## t1_n___01 1.000 0.625 0.575
## t1_n___02 (j2) 0.426 0.031 13.889 0.000 0.266 0.436
## t1_inf_sha_beh_f2 =~
## t1_n___03 1.000 0.978 0.964
## t1_n___04 (k2) 0.996 0.008 129.672 0.000 0.974 0.967
## t1_inf_sha_beh_f3 =~
## t1_n___05 1.000 0.945 0.973
## t1_n___06 (l2) 0.958 0.009 112.672 0.000 0.905 0.918
## t1_inf_sha_beh_f4 =~
## t1_n___07 1.000 0.835 0.812
## t1_n___08 (m2) 0.865 0.019 44.433 0.000 0.722 0.709
## t1_inf_sha_beh_f5 =~
## t1_n___10 1.000 0.839 0.927
## t1_n___11 (n2) 0.884 0.018 50.156 0.000 0.742 0.860
## t3_inf_sha_beh_f1 =~
## t3_n___01 1.000 0.535 0.485
## t3_n___02 (j2) 0.426 0.031 13.889 0.000 0.228 0.423
## t3_inf_sha_beh_f2 =~
## t3_n___03 1.000 0.905 0.960
## t3_n___04 (k2) 0.996 0.008 129.672 0.000 0.902 0.959
## t3_inf_sha_beh_f3 =~
## t3_n___05 1.000 0.885 0.966
## t3_n___06 (l2) 0.958 0.009 112.672 0.000 0.847 0.912
## t3_inf_sha_beh_f4 =~
## t3_n___07 1.000 0.808 0.807
## t3_n___08 (m2) 0.865 0.019 44.433 0.000 0.699 0.727
## t3_inf_sha_beh_f5 =~
## t3_n___10 1.000 0.808 0.928
## t3_n___11 (n2) 0.884 0.018 50.156 0.000 0.715 0.881
## t4_inf_sha_beh_f1 =~
## t4_n___01 1.000 0.683 0.556
## t4_n___02 (j2) 0.426 0.031 13.889 0.000 0.291 0.503
## t4_inf_sha_beh_f2 =~
## t4_n___03 1.000 0.913 0.930
## t4_n___04 (k2) 0.996 0.008 129.672 0.000 0.910 0.926
## t4_inf_sha_beh_f3 =~
## t4_n___05 1.000 0.900 0.947
## t4_n___06 (l2) 0.958 0.009 112.672 0.000 0.862 0.889
## t4_inf_sha_beh_f4 =~
## t4_n___07 1.000 0.771 0.766
## t4_n___08 (m2) 0.865 0.019 44.433 0.000 0.667 0.679
## t4_inf_sha_beh_f5 =~
## t4_n___10 1.000 0.810 0.917
## t4_n___11 (n2) 0.884 0.018 50.156 0.000 0.717 0.876
## t5_inf_sha_beh_f1 =~
## t5_n___01 1.000 2.142 1.465
## t5_n___02 (j2) 0.426 0.031 13.889 0.000 0.912 0.561
## t5_inf_sha_beh_f2 =~
## t5_n___03 1.000 1.297 0.977
## t5_n___04 (k2) 0.996 0.008 129.672 0.000 1.293 0.971
## t5_inf_sha_beh_f3 =~
## t5_n___05 1.000 1.314 0.998
## t5_n___06 (l2) 0.958 0.009 112.672 0.000 1.258 0.950
## t5_inf_sha_beh_f4 =~
## t5_n___07 1.000 1.180 0.898
## t5_n___08 (m2) 0.865 0.019 44.433 0.000 1.021 0.760
## t5_inf_sha_beh_f5 =~
## t5_n___10 1.000 1.425 1.034
## t5_n___11 (n2) 0.884 0.018 50.156 0.000 1.261 0.910
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t4_pri_con_04 ~~
## .t5_pri_con_04 0.073 0.016 4.520 0.000 0.073 0.213
## .t3_pri_con_04 ~~
## .t5_pri_con_04 0.056 0.016 3.460 0.001 0.056 0.158
## .t1_pri_con_04 ~~
## .t5_pri_con_04 0.049 0.016 3.067 0.002 0.049 0.148
## .t4_pri_con_05 ~~
## .t5_pri_con_05 0.414 0.039 10.685 0.000 0.414 0.432
## .t3_pri_con_05 ~~
## .t5_pri_con_05 0.401 0.040 10.116 0.000 0.401 0.402
## .t1_pri_con_05 ~~
## .t5_pri_con_05 0.407 0.039 10.302 0.000 0.407 0.418
## .t4_pri_con_06 ~~
## .t5_pri_con_06 0.127 0.021 5.920 0.000 0.127 0.255
## .t3_pri_con_06 ~~
## .t5_pri_con_06 0.140 0.022 6.392 0.000 0.140 0.271
## .t1_pri_con_06 ~~
## .t5_pri_con_06 0.156 0.023 6.781 0.000 0.156 0.290
## .t4_pri_con_07 ~~
## .t5_pri_con_07 0.172 0.023 7.525 0.000 0.172 0.331
## .t3_pri_con_07 ~~
## .t5_pri_con_07 0.141 0.022 6.387 0.000 0.141 0.279
## .t1_pri_con_07 ~~
## .t5_pri_con_07 0.124 0.023 5.312 0.000 0.124 0.227
## .t4_pri_con_08 ~~
## .t5_pri_con_08 0.136 0.017 7.787 0.000 0.136 0.375
## .t3_pri_con_08 ~~
## .t5_pri_con_08 0.121 0.017 7.075 0.000 0.121 0.336
## .t1_pri_con_08 ~~
## .t5_pri_con_08 0.125 0.018 6.901 0.000 0.125 0.321
## .t4_pri_con_09 ~~
## .t5_pri_con_09 0.101 0.016 6.452 0.000 0.101 0.293
## .t3_pri_con_09 ~~
## .t5_pri_con_09 0.088 0.015 5.756 0.000 0.088 0.261
## .t1_pri_con_09 ~~
## .t5_pri_con_09 0.075 0.015 5.001 0.000 0.075 0.230
## .t3_pri_con_04 ~~
## .t4_pri_con_04 0.094 0.017 5.399 0.000 0.094 0.242
## .t1_pri_con_04 ~~
## .t4_pri_con_04 0.043 0.017 2.534 0.011 0.043 0.118
## .t3_pri_con_05 ~~
## .t4_pri_con_05 0.428 0.040 10.751 0.000 0.428 0.434
## .t1_pri_con_05 ~~
## .t4_pri_con_05 0.451 0.040 11.406 0.000 0.451 0.469
## .t3_pri_con_06 ~~
## .t4_pri_con_06 0.165 0.022 7.349 0.000 0.165 0.313
## .t1_pri_con_06 ~~
## .t4_pri_con_06 0.150 0.023 6.484 0.000 0.150 0.274
## .t3_pri_con_07 ~~
## .t4_pri_con_07 0.180 0.022 8.021 0.000 0.180 0.361
## .t1_pri_con_07 ~~
## .t4_pri_con_07 0.144 0.024 6.053 0.000 0.144 0.266
## .t3_pri_con_08 ~~
## .t4_pri_con_08 0.112 0.017 6.558 0.000 0.112 0.311
## .t1_pri_con_08 ~~
## .t4_pri_con_08 0.080 0.018 4.501 0.000 0.080 0.206
## .t3_pri_con_09 ~~
## .t4_pri_con_09 0.075 0.016 4.784 0.000 0.075 0.214
## .t1_pri_con_09 ~~
## .t4_pri_con_09 0.059 0.015 3.865 0.000 0.059 0.173
## .t1_pri_con_04 ~~
## .t3_pri_con_04 0.083 0.017 4.728 0.000 0.083 0.222
## .t1_pri_con_05 ~~
## .t3_pri_con_05 0.537 0.042 12.707 0.000 0.537 0.536
## .t1_pri_con_06 ~~
## .t3_pri_con_06 0.192 0.024 7.939 0.000 0.192 0.337
## .t1_pri_con_07 ~~
## .t3_pri_con_07 0.202 0.024 8.501 0.000 0.202 0.386
## .t1_pri_con_08 ~~
## .t3_pri_con_08 0.099 0.018 5.472 0.000 0.099 0.255
## .t1_pri_con_09 ~~
## .t3_pri_con_09 0.053 0.015 3.535 0.000 0.053 0.162
## t1_pri_con_f ~~
## t5_pri_con_f 0.516 0.036 14.152 0.000 0.735 0.735
## t3_pri_con_f ~~
## t5_pri_con_f 0.550 0.038 14.621 0.000 0.766 0.766
## t4_pri_con_f ~~
## t5_pri_con_f 0.579 0.039 15.021 0.000 0.805 0.805
## t1_pri_con_f ~~
## t3_pri_con_f 0.566 0.038 15.061 0.000 0.827 0.827
## t4_pri_con_f 0.526 0.036 14.493 0.000 0.768 0.768
## t3_pri_con_f ~~
## t4_pri_con_f 0.542 0.037 14.705 0.000 0.775 0.775
## t1_inf_sha_att_f ~~
## t5_inf_sh_tt_f 0.053 0.008 6.448 0.000 0.454 0.454
## t3_inf_sha_att_f ~~
## t5_inf_sh_tt_f 0.061 0.009 6.744 0.000 0.548 0.548
## t4_inf_sha_att_f ~~
## t5_inf_sh_tt_f 0.065 0.009 6.874 0.000 0.620 0.620
## t1_inf_sha_att_f ~~
## t3_inf_sh_tt_f 0.068 0.010 6.808 0.000 0.557 0.557
## t4_inf_sh_tt_f 0.061 0.009 6.704 0.000 0.534 0.534
## t3_inf_sha_att_f ~~
## t4_inf_sh_tt_f 0.061 0.009 6.755 0.000 0.558 0.558
## .t1_inf_sha_att_01 ~~
## .t5_nf_sh_tt_01 0.314 0.038 8.288 0.000 0.314 0.410
## .t3_inf_sha_att_01 ~~
## .t5_nf_sh_tt_01 0.373 0.040 9.344 0.000 0.373 0.466
## .t4_inf_sha_att_01 ~~
## .t5_nf_sh_tt_01 0.436 0.044 9.816 0.000 0.436 0.500
## .t1_inf_sha_att_01 ~~
## .t3_nf_sh_tt_01 0.253 0.035 7.224 0.000 0.253 0.353
## .t4_nf_sh_tt_01 0.273 0.038 7.199 0.000 0.273 0.349
## .t3_inf_sha_att_01 ~~
## .t4_nf_sh_tt_01 0.311 0.040 7.716 0.000 0.311 0.381
## .t1_inf_sha_att_02 ~~
## .t5_nf_sh_tt_02 0.317 0.034 9.235 0.000 0.317 0.442
## .t3_inf_sha_att_02 ~~
## .t5_nf_sh_tt_02 0.371 0.035 10.667 0.000 0.371 0.531
## .t4_inf_sha_att_02 ~~
## .t5_nf_sh_tt_02 0.374 0.036 10.304 0.000 0.374 0.537
## .t1_inf_sha_att_02 ~~
## .t3_nf_sh_tt_02 0.299 0.034 8.886 0.000 0.299 0.414
## .t4_nf_sh_tt_02 0.333 0.034 9.709 0.000 0.333 0.463
## .t3_inf_sha_att_02 ~~
## .t4_nf_sh_tt_02 0.387 0.035 11.146 0.000 0.387 0.554
## .t1_inf_sha_att_03 ~~
## .t5_nf_sh_tt_03 0.067 0.014 4.864 0.000 0.067 0.218
## .t3_inf_sha_att_03 ~~
## .t5_nf_sh_tt_03 0.072 0.013 5.597 0.000 0.072 0.261
## .t4_inf_sha_att_03 ~~
## .t5_nf_sh_tt_03 0.161 0.021 7.633 0.000 0.161 0.314
## .t1_inf_sha_att_03 ~~
## .t3_nf_sh_tt_03 0.060 0.010 6.257 0.000 0.060 0.370
## .t4_nf_sh_tt_03 0.054 0.014 3.904 0.000 0.054 0.179
## .t3_inf_sha_att_03 ~~
## .t4_nf_sh_tt_03 0.069 0.013 5.155 0.000 0.069 0.254
## .t1_inf_sha_att_04 ~~
## .t5_nf_sh_tt_04 0.093 0.013 7.342 0.000 0.093 0.333
## .t3_inf_sha_att_04 ~~
## .t5_nf_sh_tt_04 0.097 0.012 7.809 0.000 0.097 0.349
## .t4_inf_sha_att_04 ~~
## .t5_nf_sh_tt_04 0.131 0.017 7.838 0.000 0.131 0.340
## .t1_inf_sha_att_04 ~~
## .t3_nf_sh_tt_04 0.056 0.010 5.366 0.000 0.056 0.283
## .t4_nf_sh_tt_04 0.066 0.013 5.266 0.000 0.066 0.244
## .t3_inf_sha_att_04 ~~
## .t4_nf_sh_tt_04 0.101 0.013 7.880 0.000 0.101 0.374
## .t1_inf_sha_att_05 ~~
## .t5_nf_sh_tt_05 -0.000 0.008 -0.059 0.953 -0.000 -0.005
## .t3_inf_sha_att_05 ~~
## .t5_nf_sh_tt_05 -0.000 0.009 -0.036 0.971 -0.000 -0.003
## .t4_inf_sha_att_05 ~~
## .t5_nf_sh_tt_05 0.011 0.009 1.218 0.223 0.011 0.096
## .t1_inf_sha_att_05 ~~
## .t3_nf_sh_tt_05 0.033 0.009 3.470 0.001 0.033 0.243
## .t4_nf_sh_tt_05 0.026 0.009 2.876 0.004 0.026 0.203
## .t3_inf_sha_att_05 ~~
## .t4_nf_sh_tt_05 0.050 0.010 4.981 0.000 0.050 0.331
## .t1_inf_sha_att_06 ~~
## .t5_nf_sh_tt_06 0.134 0.013 10.236 0.000 0.134 0.467
## .t3_inf_sha_att_06 ~~
## .t5_nf_sh_tt_06 0.142 0.014 10.008 0.000 0.142 0.464
## .t4_inf_sha_att_06 ~~
## .t5_nf_sh_tt_06 0.153 0.014 10.673 0.000 0.153 0.499
## .t1_inf_sha_att_06 ~~
## .t3_nf_sh_tt_06 0.126 0.013 9.371 0.000 0.126 0.455
## .t4_nf_sh_tt_06 0.110 0.013 8.637 0.000 0.110 0.395
## .t3_inf_sha_att_06 ~~
## .t4_nf_sh_tt_06 0.138 0.014 9.696 0.000 0.138 0.469
## .t1_inf_sha_att_07 ~~
## .t5_nf_sh_tt_07 0.205 0.022 9.294 0.000 0.205 0.416
## .t3_inf_sha_att_07 ~~
## .t5_nf_sh_tt_07 0.199 0.022 9.068 0.000 0.199 0.391
## .t4_inf_sha_att_07 ~~
## .t5_nf_sh_tt_07 0.216 0.022 9.588 0.000 0.216 0.419
## .t1_inf_sha_att_07 ~~
## .t3_nf_sh_tt_07 0.193 0.022 8.828 0.000 0.193 0.401
## .t4_nf_sh_tt_07 0.205 0.022 9.295 0.000 0.205 0.422
## .t3_inf_sha_att_07 ~~
## .t4_nf_sh_tt_07 0.158 0.021 7.374 0.000 0.158 0.315
## .t1_inf_sha_att_08 ~~
## .t5_nf_sh_tt_08 0.231 0.024 9.471 0.000 0.231 0.388
## .t3_inf_sha_att_08 ~~
## .t5_nf_sh_tt_08 0.227 0.024 9.288 0.000 0.227 0.375
## .t4_inf_sha_att_08 ~~
## .t5_nf_sh_tt_08 0.276 0.025 10.861 0.000 0.276 0.448
## .t1_inf_sha_att_08 ~~
## .t3_nf_sh_tt_08 0.231 0.025 9.433 0.000 0.231 0.396
## .t4_nf_sh_tt_08 0.229 0.025 9.281 0.000 0.229 0.385
## .t3_inf_sha_att_08 ~~
## .t4_nf_sh_tt_08 0.216 0.025 8.704 0.000 0.216 0.358
## .t1_inf_sha_att_10 ~~
## .t5_nf_sh_tt_10 0.032 0.013 2.410 0.016 0.032 0.228
## .t3_inf_sha_att_10 ~~
## .t5_nf_sh_tt_10 0.023 0.013 1.865 0.062 0.023 0.201
## .t4_inf_sha_att_10 ~~
## .t5_nf_sh_tt_10 0.050 0.012 4.061 0.000 0.050 0.418
## .t1_inf_sha_att_10 ~~
## .t3_nf_sh_tt_10 0.011 0.015 0.743 0.458 0.011 0.067
## .t4_nf_sh_tt_10 0.033 0.014 2.329 0.020 0.033 0.200
## .t3_inf_sha_att_10 ~~
## .t4_nf_sh_tt_10 0.027 0.013 1.986 0.047 0.027 0.197
## .t1_inf_sha_att_11 ~~
## .t5_nf_sh_tt_11 0.062 0.013 4.706 0.000 0.062 0.357
## .t3_inf_sha_att_11 ~~
## .t5_nf_sh_tt_11 0.034 0.013 2.647 0.008 0.034 0.201
## .t4_inf_sha_att_11 ~~
## .t5_nf_sh_tt_11 0.054 0.012 4.403 0.000 0.054 0.335
## .t1_inf_sha_att_11 ~~
## .t3_nf_sh_tt_11 0.050 0.014 3.537 0.000 0.050 0.275
## .t4_nf_sh_tt_11 0.054 0.014 3.978 0.000 0.054 0.311
## .t3_inf_sha_att_11 ~~
## .t4_nf_sh_tt_11 0.046 0.013 3.466 0.001 0.046 0.273
## t1_inf_sha_beh_f ~~
## t5_inf_sh_bh_f -0.035 0.008 -4.323 0.000 -0.168 -0.168
## t3_inf_sha_beh_f ~~
## t5_inf_sh_bh_f -0.031 0.007 -4.117 0.000 -0.158 -0.158
## t4_inf_sha_beh_f ~~
## t5_inf_sh_bh_f -0.041 0.008 -5.172 0.000 -0.213 -0.213
## t1_inf_sha_beh_f ~~
## t3_inf_sh_bh_f 0.084 0.010 8.860 0.000 0.614 0.614
## t4_inf_sh_bh_f 0.076 0.009 8.549 0.000 0.551 0.551
## t3_inf_sha_beh_f ~~
## t4_inf_sh_bh_f 0.080 0.009 8.862 0.000 0.626 0.626
## .t1_inf_sha_beh_01 ~~
## .t5_nf_sh_bh_01 -0.088 0.026 -3.411 0.001 -0.088 -0.063
## .t3_inf_sha_beh_01 ~~
## .t5_nf_sh_bh_01 -0.075 0.027 -2.804 0.005 -0.075 -0.050
## .t4_inf_sha_beh_01 ~~
## .t5_nf_sh_bh_01 -0.059 0.030 -1.942 0.052 -0.059 -0.037
## .t1_inf_sha_beh_01 ~~
## .t3_nf_sh_bh_01 0.359 0.037 9.697 0.000 0.359 0.417
## .t4_nf_sh_bh_01 0.378 0.041 9.313 0.000 0.378 0.416
## .t3_inf_sha_beh_01 ~~
## .t4_nf_sh_bh_01 0.435 0.043 10.048 0.000 0.435 0.440
## .t1_inf_sha_beh_02 ~~
## .t5_nf_sh_bh_02 -0.008 0.017 -0.440 0.660 -0.008 -0.010
## .t3_inf_sha_beh_02 ~~
## .t5_nf_sh_bh_02 -0.043 0.016 -2.768 0.006 -0.043 -0.065
## .t4_inf_sha_beh_02 ~~
## .t5_nf_sh_bh_02 -0.041 0.017 -2.445 0.014 -0.041 -0.060
## .t1_inf_sha_beh_02 ~~
## .t3_nf_sh_bh_02 0.075 0.010 7.380 0.000 0.075 0.281
## .t4_nf_sh_bh_02 0.061 0.011 5.786 0.000 0.061 0.224
## .t3_inf_sha_beh_02 ~~
## .t4_nf_sh_bh_02 0.064 0.010 6.613 0.000 0.064 0.263
## .t1_inf_sha_beh_03 ~~
## .t5_nf_sh_bh_03 -0.002 0.005 -0.516 0.606 -0.002 -0.032
## .t3_inf_sha_beh_03 ~~
## .t5_nf_sh_bh_03 0.002 0.004 0.461 0.645 0.002 0.028
## .t4_inf_sha_beh_03 ~~
## .t5_nf_sh_bh_03 -0.002 0.006 -0.326 0.744 -0.002 -0.019
## .t1_inf_sha_beh_03 ~~
## .t3_nf_sh_bh_03 0.021 0.005 4.359 0.000 0.021 0.295
## .t4_nf_sh_bh_03 0.008 0.006 1.300 0.194 0.008 0.079
## .t3_inf_sha_beh_03 ~~
## .t4_nf_sh_bh_03 0.028 0.006 4.777 0.000 0.028 0.296
## .t1_inf_sha_beh_04 ~~
## .t5_nf_sh_bh_04 -0.016 0.005 -3.183 0.001 -0.016 -0.189
## .t3_inf_sha_beh_04 ~~
## .t5_nf_sh_bh_04 -0.009 0.005 -1.917 0.055 -0.009 -0.108
## .t4_inf_sha_beh_04 ~~
## .t5_nf_sh_bh_04 -0.035 0.006 -5.340 0.000 -0.035 -0.290
## .t1_inf_sha_beh_04 ~~
## .t3_nf_sh_bh_04 0.020 0.005 4.295 0.000 0.020 0.295
## .t4_nf_sh_bh_04 0.021 0.006 3.619 0.000 0.021 0.221
## .t3_inf_sha_beh_04 ~~
## .t4_nf_sh_bh_04 0.036 0.006 5.977 0.000 0.036 0.362
## .t1_inf_sha_beh_05 ~~
## .t5_nf_sh_bh_05 -0.004 0.004 -0.965 0.335 -0.004 -0.228
## .t3_inf_sha_beh_05 ~~
## .t5_nf_sh_bh_05 -0.001 0.004 -0.136 0.892 -0.001 -0.030
## .t4_inf_sha_beh_05 ~~
## .t5_nf_sh_bh_05 -0.013 0.005 -2.583 0.010 -0.013 -0.544
## .t1_inf_sha_beh_05 ~~
## .t3_nf_sh_bh_05 0.010 0.005 1.951 0.051 0.010 0.184
## .t4_nf_sh_bh_05 0.013 0.006 2.280 0.023 0.013 0.193
## .t3_inf_sha_beh_05 ~~
## .t4_nf_sh_bh_05 -0.001 0.006 -0.212 0.832 -0.001 -0.017
## .t1_inf_sha_beh_06 ~~
## .t5_nf_sh_bh_06 -0.022 0.007 -3.185 0.001 -0.022 -0.134
## .t3_inf_sha_beh_06 ~~
## .t5_nf_sh_bh_06 -0.020 0.007 -3.041 0.002 -0.020 -0.129
## .t4_inf_sha_beh_06 ~~
## .t5_nf_sh_bh_06 -0.029 0.008 -3.638 0.000 -0.029 -0.156
## .t1_inf_sha_beh_06 ~~
## .t3_nf_sh_bh_06 0.047 0.007 6.608 0.000 0.047 0.313
## .t4_nf_sh_bh_06 0.043 0.008 5.445 0.000 0.043 0.245
## .t3_inf_sha_beh_06 ~~
## .t4_nf_sh_bh_06 0.078 0.008 9.644 0.000 0.078 0.460
## .t1_inf_sha_beh_07 ~~
## .t5_nf_sh_bh_07 -0.020 0.014 -1.435 0.151 -0.020 -0.057
## .t3_inf_sha_beh_07 ~~
## .t5_nf_sh_bh_07 -0.043 0.014 -3.015 0.003 -0.043 -0.125
## .t4_inf_sha_beh_07 ~~
## .t5_nf_sh_bh_07 -0.033 0.015 -2.202 0.028 -0.033 -0.088
## .t1_inf_sha_beh_07 ~~
## .t3_nf_sh_bh_07 0.122 0.015 8.119 0.000 0.122 0.344
## .t4_nf_sh_bh_07 0.124 0.016 7.957 0.000 0.124 0.319
## .t3_inf_sha_beh_07 ~~
## .t4_nf_sh_bh_07 0.126 0.016 7.925 0.000 0.126 0.329
## .t1_inf_sha_beh_08 ~~
## .t5_nf_sh_bh_08 -0.084 0.023 -3.686 0.000 -0.084 -0.134
## .t3_inf_sha_beh_08 ~~
## .t5_nf_sh_bh_08 -0.038 0.022 -1.785 0.074 -0.038 -0.067
## .t4_inf_sha_beh_08 ~~
## .t5_nf_sh_bh_08 -0.049 0.023 -2.145 0.032 -0.049 -0.079
## .t1_inf_sha_beh_08 ~~
## .t3_nf_sh_bh_08 0.159 0.019 8.535 0.000 0.159 0.337
## .t4_nf_sh_bh_08 0.183 0.020 9.331 0.000 0.183 0.353
## .t3_inf_sha_beh_08 ~~
## .t4_nf_sh_bh_08 0.196 0.019 10.299 0.000 0.196 0.412
## .t1_inf_sha_beh_10 ~~
## .t5_nf_sh_bh_10 -0.028 0.012 -2.431 0.015 -0.028 -0.228
## .t3_inf_sha_beh_10 ~~
## .t5_nf_sh_bh_10 -0.028 0.011 -2.526 0.012 -0.028 -0.237
## .t4_inf_sha_beh_10 ~~
## .t5_nf_sh_bh_10 -0.020 0.011 -1.744 0.081 -0.020 -0.153
## .t1_inf_sha_beh_10 ~~
## .t3_nf_sh_bh_10 0.019 0.011 1.747 0.081 0.019 0.174
## .t4_nf_sh_bh_10 0.036 0.012 3.109 0.002 0.036 0.300
## .t3_inf_sha_beh_10 ~~
## .t4_nf_sh_bh_10 0.047 0.011 4.304 0.000 0.047 0.407
## .t1_inf_sha_beh_11 ~~
## .t5_nf_sh_bh_11 -0.010 0.012 -0.854 0.393 -0.010 -0.040
## .t3_inf_sha_beh_11 ~~
## .t5_nf_sh_bh_11 0.005 0.011 0.429 0.668 0.005 0.021
## .t4_inf_sha_beh_11 ~~
## .t5_nf_sh_bh_11 -0.018 0.011 -1.648 0.099 -0.018 -0.079
## .t1_inf_sha_beh_11 ~~
## .t3_nf_sh_bh_11 0.026 0.010 2.557 0.011 0.026 0.153
## .t4_nf_sh_bh_11 0.055 0.010 5.251 0.000 0.055 0.315
## .t3_inf_sha_beh_11 ~~
## .t4_nf_sh_bh_11 0.038 0.010 3.967 0.000 0.038 0.254
## .t1_inf_sha_att_01 ~~
## .t1_nf_sh_bh_01 0.171 0.030 5.685 0.000 0.171 0.233
## .t1_inf_sha_att_02 ~~
## .t1_nf_sh_bh_02 0.082 0.017 4.775 0.000 0.082 0.174
## .t1_inf_sha_att_03 ~~
## .t1_nf_sh_bh_03 0.019 0.006 2.975 0.003 0.019 0.166
## .t1_inf_sha_att_04 ~~
## .t1_nf_sh_bh_04 0.030 0.006 4.608 0.000 0.030 0.258
## .t1_inf_sha_att_05 ~~
## .t1_nf_sh_bh_05 0.019 0.006 3.023 0.003 0.019 0.254
## .t1_inf_sha_att_06 ~~
## .t1_nf_sh_bh_06 0.046 0.008 5.602 0.000 0.046 0.229
## .t1_inf_sha_att_07 ~~
## .t1_nf_sh_bh_07 0.062 0.015 4.167 0.000 0.062 0.151
## .t1_inf_sha_att_08 ~~
## .t1_nf_sh_bh_08 0.112 0.018 6.129 0.000 0.112 0.206
## .t1_inf_sha_att_10 ~~
## .t1_nf_sh_bh_10 -0.002 0.013 -0.168 0.867 -0.002 -0.015
## .t1_inf_sha_att_11 ~~
## .t1_nf_sh_bh_11 0.036 0.012 2.941 0.003 0.036 0.189
## .t3_inf_sha_att_01 ~~
## .t3_nf_sh_bh_01 0.192 0.031 6.099 0.000 0.192 0.229
## .t3_inf_sha_att_02 ~~
## .t3_nf_sh_bh_02 0.064 0.014 4.520 0.000 0.064 0.157
## .t3_inf_sha_att_03 ~~
## .t3_nf_sh_bh_03 0.032 0.006 5.266 0.000 0.032 0.319
## .t3_inf_sha_att_04 ~~
## .t3_nf_sh_bh_04 0.023 0.006 3.637 0.000 0.023 0.193
## .t3_inf_sha_att_05 ~~
## .t3_nf_sh_bh_05 0.022 0.007 3.287 0.001 0.022 0.233
## .t3_inf_sha_att_06 ~~
## .t3_nf_sh_bh_06 0.018 0.008 2.266 0.023 0.018 0.088
## .t3_inf_sha_att_07 ~~
## .t3_nf_sh_bh_07 0.098 0.016 6.194 0.000 0.098 0.236
## .t3_inf_sha_att_08 ~~
## .t3_nf_sh_bh_08 0.094 0.018 5.342 0.000 0.094 0.185
## .t3_inf_sha_att_10 ~~
## .t3_nf_sh_bh_10 0.025 0.012 2.130 0.033 0.025 0.211
## .t3_inf_sha_att_11 ~~
## .t3_nf_sh_bh_11 0.012 0.011 1.058 0.290 0.012 0.074
## .t4_inf_sha_att_01 ~~
## .t4_nf_sh_bh_01 0.160 0.036 4.398 0.000 0.160 0.166
## .t4_inf_sha_att_02 ~~
## .t4_nf_sh_bh_02 0.050 0.015 3.332 0.001 0.050 0.120
## .t4_inf_sha_att_03 ~~
## .t4_nf_sh_bh_03 0.042 0.011 3.685 0.000 0.042 0.163
## .t4_inf_sha_att_04 ~~
## .t4_nf_sh_bh_04 0.051 0.010 5.080 0.000 0.051 0.222
## .t4_inf_sha_att_05 ~~
## .t4_nf_sh_bh_05 0.018 0.008 2.332 0.020 0.018 0.157
## .t4_inf_sha_att_06 ~~
## .t4_nf_sh_bh_06 0.048 0.009 5.162 0.000 0.048 0.198
## .t4_inf_sha_att_07 ~~
## .t4_nf_sh_bh_07 0.098 0.016 5.991 0.000 0.098 0.213
## .t4_inf_sha_att_08 ~~
## .t4_nf_sh_bh_08 0.107 0.018 5.933 0.000 0.107 0.189
## .t4_inf_sha_att_10 ~~
## .t4_nf_sh_bh_10 0.004 0.011 0.381 0.703 0.004 0.033
## .t4_inf_sha_att_11 ~~
## .t4_nf_sh_bh_11 0.026 0.011 2.513 0.012 0.026 0.167
## .t5_inf_sha_att_01 ~~
## .t5_nf_sh_bh_01 -0.048 0.027 -1.795 0.073 -0.048 -0.033
## .t5_inf_sha_att_02 ~~
## .t5_nf_sh_bh_02 -0.011 0.028 -0.399 0.690 -0.011 -0.010
## .t5_inf_sha_att_03 ~~
## .t5_nf_sh_bh_03 -0.028 0.009 -3.107 0.002 -0.028 -0.137
## .t5_inf_sha_att_04 ~~
## .t5_nf_sh_bh_04 -0.024 0.008 -2.938 0.003 -0.024 -0.119
## .t5_inf_sha_att_05 ~~
## .t5_nf_sh_bh_05 -0.013 0.006 -2.300 0.021 -0.013 -0.523
## .t5_inf_sha_att_06 ~~
## .t5_nf_sh_bh_06 0.015 0.009 1.696 0.090 0.015 0.063
## .t5_inf_sha_att_07 ~~
## .t5_nf_sh_bh_07 0.027 0.015 1.777 0.076 0.027 0.065
## .t5_inf_sha_att_08 ~~
## .t5_nf_sh_bh_08 -0.039 0.023 -1.744 0.081 -0.039 -0.057
## .t5_inf_sha_att_10 ~~
## .t5_nf_sh_bh_10 -0.005 0.012 -0.442 0.658 -0.005 -0.046
## .t5_inf_sha_att_11 ~~
## .t5_nf_sh_bh_11 -0.009 0.013 -0.739 0.460 -0.009 -0.041
## t1_pri_con_f ~~
## t1_inf_sh_tt_f -0.065 0.012 -5.363 0.000 -0.222 -0.222
## t3_inf_sh_tt_f -0.040 0.011 -3.572 0.000 -0.142 -0.142
## t4_inf_sh_tt_f -0.065 0.011 -5.787 0.000 -0.247 -0.247
## t5_inf_sh_tt_f -0.064 0.011 -5.615 0.000 -0.238 -0.238
## t1_inf_sh_bh_f -0.035 0.012 -2.920 0.003 -0.111 -0.111
## t3_inf_sh_bh_f -0.021 0.011 -1.856 0.063 -0.070 -0.070
## t4_inf_sh_bh_f -0.036 0.011 -3.229 0.001 -0.125 -0.125
## t5_inf_sh_bh_f 0.013 0.016 0.795 0.426 0.029 0.029
## t3_pri_con_f ~~
## t1_inf_sh_tt_f -0.050 0.012 -4.229 0.000 -0.167 -0.167
## t3_inf_sh_tt_f -0.041 0.011 -3.652 0.000 -0.143 -0.143
## t4_inf_sh_tt_f -0.040 0.011 -3.793 0.000 -0.151 -0.151
## t5_inf_sh_tt_f -0.044 0.011 -4.053 0.000 -0.161 -0.161
## t1_inf_sh_bh_f -0.030 0.012 -2.472 0.013 -0.093 -0.093
## t3_inf_sh_bh_f -0.017 0.011 -1.484 0.138 -0.055 -0.055
## t4_inf_sh_bh_f -0.031 0.011 -2.745 0.006 -0.105 -0.105
## t5_inf_sh_bh_f -0.006 0.017 -0.383 0.701 -0.014 -0.014
## t4_pri_con_f ~~
## t1_inf_sh_tt_f -0.059 0.012 -4.960 0.000 -0.199 -0.199
## t3_inf_sh_tt_f -0.048 0.011 -4.268 0.000 -0.169 -0.169
## t4_inf_sh_tt_f -0.056 0.011 -5.095 0.000 -0.210 -0.210
## t5_inf_sh_tt_f -0.051 0.011 -4.609 0.000 -0.185 -0.185
## t1_inf_sh_bh_f -0.034 0.012 -2.790 0.005 -0.105 -0.105
## t3_inf_sh_bh_f -0.034 0.011 -3.004 0.003 -0.113 -0.113
## t4_inf_sh_bh_f -0.040 0.011 -3.485 0.000 -0.133 -0.133
## t5_inf_sh_bh_f 0.013 0.017 0.785 0.433 0.029 0.029
## t5_pri_con_f ~~
## t1_inf_sh_tt_f -0.053 0.012 -4.413 0.000 -0.174 -0.174
## t3_inf_sh_tt_f -0.040 0.011 -3.468 0.001 -0.135 -0.135
## t4_inf_sh_tt_f -0.051 0.011 -4.618 0.000 -0.187 -0.187
## t5_inf_sh_tt_f -0.068 0.012 -5.820 0.000 -0.243 -0.243
## t1_inf_sh_bh_f -0.028 0.012 -2.293 0.022 -0.085 -0.085
## t3_inf_sh_bh_f -0.019 0.011 -1.643 0.100 -0.061 -0.061
## t4_inf_sh_bh_f -0.031 0.012 -2.714 0.007 -0.103 -0.103
## t5_inf_sh_bh_f 0.021 0.017 1.215 0.224 0.044 0.044
## t1_inf_sha_att_f ~~
## t1_inf_sh_bh_f 0.062 0.007 8.498 0.000 0.452 0.452
## t3_inf_sh_bh_f 0.051 0.006 7.973 0.000 0.398 0.398
## t4_inf_sh_bh_f 0.042 0.006 7.118 0.000 0.330 0.330
## t5_inf_sh_bh_f -0.024 0.007 -3.328 0.001 -0.124 -0.124
## t3_inf_sha_att_f ~~
## t1_inf_sh_bh_f 0.048 0.006 7.575 0.000 0.364 0.364
## t3_inf_sh_bh_f 0.061 0.007 8.833 0.000 0.500 0.500
## t4_inf_sh_bh_f 0.040 0.006 7.062 0.000 0.330 0.330
## t5_inf_sh_bh_f -0.036 0.007 -4.886 0.000 -0.193 -0.193
## t4_inf_sha_att_f ~~
## t1_inf_sh_bh_f 0.046 0.006 7.630 0.000 0.374 0.374
## t3_inf_sh_bh_f 0.047 0.006 8.049 0.000 0.414 0.414
## t4_inf_sh_bh_f 0.053 0.006 8.450 0.000 0.462 0.462
## t5_inf_sh_bh_f -0.033 0.007 -4.735 0.000 -0.188 -0.188
## t5_inf_sha_att_f ~~
## t1_inf_sh_bh_f 0.048 0.006 7.717 0.000 0.377 0.377
## t3_inf_sh_bh_f 0.046 0.006 7.877 0.000 0.395 0.395
## t4_inf_sh_bh_f 0.048 0.006 8.027 0.000 0.412 0.412
## t5_inf_sh_bh_f -0.031 0.007 -4.509 0.000 -0.176 -0.176
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 3.706 0.035 104.702 0.000 3.706 3.506
## .t1_pri_con_05 3.780 0.044 86.154 0.000 3.780 2.892
## .t1_pri_con_06 3.285 0.039 83.582 0.000 3.285 2.799
## .t1_pri_con_07 3.612 0.042 85.909 0.000 3.612 2.877
## .t1_pri_con_08 3.615 0.039 92.412 0.000 3.615 3.094
## .t1_pri_con_09 4.094 0.035 116.793 0.000 4.094 3.911
## .t3_pri_con_04 3.674 0.035 103.711 0.000 3.674 3.478
## .t3_pri_con_05 3.683 0.044 83.818 0.000 3.683 2.818
## .t3_pri_con_06 3.212 0.038 84.812 0.000 3.212 2.844
## .t3_pri_con_07 3.482 0.042 83.833 0.000 3.482 2.811
## .t3_pri_con_08 3.562 0.039 91.437 0.000 3.562 3.068
## .t3_pri_con_09 3.985 0.036 110.746 0.000 3.985 3.715
## .t4_pri_con_04 3.580 0.036 100.345 0.000 3.580 3.369
## .t4_pri_con_05 3.689 0.043 85.018 0.000 3.689 2.861
## .t4_pri_con_06 3.156 0.038 83.074 0.000 3.156 2.791
## .t4_pri_con_07 3.322 0.041 80.327 0.000 3.322 2.697
## .t4_pri_con_08 3.505 0.038 91.273 0.000 3.505 3.066
## .t4_pri_con_09 3.910 0.036 109.434 0.000 3.910 3.675
## .t5_pri_con_04 3.590 0.036 100.643 0.000 3.590 3.369
## .t5_pri_con_05 3.597 0.044 81.186 0.000 3.597 2.721
## .t5_pri_con_06 3.120 0.038 81.062 0.000 3.120 2.715
## .t5_pri_con_07 3.282 0.042 78.096 0.000 3.282 2.615
## .t5_pri_con_08 3.434 0.039 88.333 0.000 3.434 2.958
## .t5_pri_con_09 3.874 0.036 108.380 0.000 3.874 3.629
## .t1_nf_sh_tt_01 1.710 0.038 45.395 0.000 1.710 1.521
## .t1_nf_sh_tt_02 1.937 0.037 52.388 0.000 1.937 1.756
## .t1_nf_sh_tt_03 2.845 0.035 82.072 0.000 2.845 2.748
## .t1_nf_sh_tt_04 3.018 0.034 87.793 0.000 3.018 2.940
## .t1_nf_sh_tt_05 2.722 0.035 77.209 0.000 2.722 2.585
## .t1_nf_sh_tt_06 2.468 0.036 67.932 0.000 2.468 2.275
## .t1_nf_sh_tt_07 3.059 0.036 84.155 0.000 3.059 2.818
## .t1_nf_sh_tt_08 2.361 0.036 66.357 0.000 2.361 2.222
## .t1_nf_sh_tt_10 2.265 0.036 62.773 0.000 2.265 2.103
## .t1_nf_sh_tt_11 2.303 0.035 65.314 0.000 2.303 2.188
## .t3_nf_sh_tt_01 1.802 0.037 48.063 0.000 1.802 1.609
## .t3_nf_sh_tt_02 1.911 0.035 54.045 0.000 1.911 1.809
## .t3_nf_sh_tt_03 3.035 0.034 88.811 0.000 3.035 2.973
## .t3_nf_sh_tt_04 3.132 0.034 91.055 0.000 3.132 3.047
## .t3_nf_sh_tt_05 2.842 0.035 82.346 0.000 2.842 2.756
## .t3_nf_sh_tt_06 2.556 0.035 72.064 0.000 2.556 2.412
## .t3_nf_sh_tt_07 3.214 0.035 91.096 0.000 3.214 3.051
## .t3_nf_sh_tt_08 2.457 0.035 70.979 0.000 2.457 2.377
## .t3_nf_sh_tt_10 2.319 0.035 66.764 0.000 2.319 2.236
## .t3_nf_sh_tt_11 2.393 0.035 68.843 0.000 2.393 2.305
## .t4_nf_sh_tt_01 1.937 0.041 47.765 0.000 1.937 1.601
## .t4_nf_sh_tt_02 1.940 0.036 53.578 0.000 1.940 1.796
## .t4_nf_sh_tt_03 2.831 0.037 77.249 0.000 2.831 2.590
## .t4_nf_sh_tt_04 3.000 0.034 87.968 0.000 3.000 2.944
## .t4_nf_sh_tt_05 2.681 0.033 81.450 0.000 2.681 2.726
## .t4_nf_sh_tt_06 2.368 0.034 68.962 0.000 2.368 2.308
## .t4_nf_sh_tt_07 3.125 0.034 90.916 0.000 3.125 3.042
## .t4_nf_sh_tt_08 2.261 0.034 66.244 0.000 2.261 2.218
## .t4_nf_sh_tt_10 2.215 0.034 65.894 0.000 2.215 2.205
## .t4_nf_sh_tt_11 2.296 0.033 68.947 0.000 2.296 2.307
## .t5_nf_sh_tt_01 1.996 0.041 49.046 0.000 1.996 1.646
## .t5_nf_sh_tt_02 1.985 0.037 54.042 0.000 1.985 1.812
## .t5_nf_sh_tt_03 2.840 0.036 77.951 0.000 2.840 2.612
## .t5_nf_sh_tt_04 3.046 0.034 89.607 0.000 3.046 3.000
## .t5_nf_sh_tt_05 2.727 0.033 81.571 0.000 2.727 2.731
## .t5_nf_sh_tt_06 2.421 0.036 67.652 0.000 2.421 2.265
## .t5_nf_sh_tt_07 3.161 0.034 91.747 0.000 3.161 3.072
## .t5_nf_sh_tt_08 2.320 0.034 68.148 0.000 2.320 2.282
## .t5_nf_sh_tt_10 2.269 0.034 67.717 0.000 2.269 2.268
## .t5_nf_sh_tt_11 2.332 0.034 68.877 0.000 2.332 2.307
## .t1_nf_sh_bh_01 1.743 0.036 47.799 0.000 1.743 1.602
## .t1_nf_sh_bh_02 1.260 0.020 61.591 0.000 1.260 2.064
## .t1_nf_sh_bh_03 2.732 0.034 80.480 0.000 2.732 2.693
## .t1_nf_sh_bh_04 2.774 0.034 82.232 0.000 2.774 2.752
## .t1_nf_sh_bh_05 2.599 0.032 79.995 0.000 2.599 2.678
## .t1_nf_sh_bh_06 2.494 0.033 75.548 0.000 2.494 2.529
## .t1_nf_sh_bh_07 2.951 0.034 85.761 0.000 2.951 2.870
## .t1_nf_sh_bh_08 2.234 0.034 65.520 0.000 2.234 2.195
## .t1_nf_sh_bh_10 1.796 0.030 59.220 0.000 1.796 1.984
## .t1_nf_sh_bh_11 1.728 0.029 59.764 0.000 1.728 2.002
## .t3_nf_sh_bh_01 1.777 0.037 48.057 0.000 1.777 1.609
## .t3_nf_sh_bh_02 1.246 0.018 69.171 0.000 1.246 2.315
## .t3_nf_sh_bh_03 2.677 0.032 84.861 0.000 2.677 2.840
## .t3_nf_sh_bh_04 2.742 0.031 87.082 0.000 2.742 2.914
## .t3_nf_sh_bh_05 2.566 0.031 83.726 0.000 2.566 2.802
## .t3_nf_sh_bh_06 2.450 0.031 78.827 0.000 2.450 2.638
## .t3_nf_sh_bh_07 2.944 0.034 87.791 0.000 2.944 2.939
## .t3_nf_sh_bh_08 2.239 0.032 69.539 0.000 2.239 2.330
## .t3_nf_sh_bh_10 1.785 0.029 61.200 0.000 1.785 2.049
## .t3_nf_sh_bh_11 1.719 0.027 63.285 0.000 1.719 2.119
## .t4_nf_sh_bh_01 1.915 0.041 46.493 0.000 1.915 1.558
## .t4_nf_sh_bh_02 1.249 0.019 64.576 0.000 1.249 2.161
## .t4_nf_sh_bh_03 2.727 0.033 82.974 0.000 2.727 2.778
## .t4_nf_sh_bh_04 2.812 0.033 85.450 0.000 2.812 2.861
## .t4_nf_sh_bh_05 2.590 0.032 81.356 0.000 2.590 2.724
## .t4_nf_sh_bh_06 2.450 0.032 75.484 0.000 2.450 2.528
## .t4_nf_sh_bh_07 2.966 0.034 87.943 0.000 2.966 2.945
## .t4_nf_sh_bh_08 2.231 0.033 67.860 0.000 2.231 2.273
## .t4_nf_sh_bh_10 1.808 0.030 61.109 0.000 1.808 2.046
## .t4_nf_sh_bh_11 1.757 0.027 64.129 0.000 1.757 2.147
## .t5_nf_sh_bh_01 2.958 0.049 60.056 0.000 2.958 2.023
## .t5_nf_sh_bh_02 3.084 0.055 56.215 0.000 3.084 1.897
## .t5_nf_sh_bh_03 2.507 0.045 56.063 0.000 2.507 1.888
## .t5_nf_sh_bh_04 2.493 0.045 55.591 0.000 2.493 1.872
## .t5_nf_sh_bh_05 2.565 0.044 57.862 0.000 2.565 1.949
## .t5_nf_sh_bh_06 2.604 0.045 58.311 0.000 2.604 1.965
## .t5_nf_sh_bh_07 2.482 0.044 56.031 0.000 2.482 1.888
## .t5_nf_sh_bh_08 2.725 0.045 60.170 0.000 2.725 2.030
## .t5_nf_sh_bh_10 2.832 0.046 60.926 0.000 2.832 2.055
## .t5_nf_sh_bh_11 2.857 0.047 61.091 0.000 2.857 2.061
## t1_pri_con_f 0.000 0.000 0.000
## t3_pri_con_f 0.000 0.000 0.000
## t4_pri_con_f 0.000 0.000 0.000
## t5_pri_con_f 0.000 0.000 0.000
## .t1_pri_con_f1 0.000 0.000 0.000
## .t1_pri_con_f2 0.000 0.000 0.000
## .t3_pri_con_f1 0.000 0.000 0.000
## .t3_pri_con_f2 0.000 0.000 0.000
## .t4_pri_con_f1 0.000 0.000 0.000
## .t4_pri_con_f2 0.000 0.000 0.000
## .t5_pri_con_f1 0.000 0.000 0.000
## .t5_pri_con_f2 0.000 0.000 0.000
## t1_inf_sh_tt_f 0.000 0.000 0.000
## t3_inf_sh_tt_f 0.000 0.000 0.000
## t4_inf_sh_tt_f 0.000 0.000 0.000
## t5_inf_sh_tt_f 0.000 0.000 0.000
## .t1_nf_sh_tt_f1 0.000 0.000 0.000
## .t1_nf_sh_tt_f2 0.000 0.000 0.000
## .t1_nf_sh_tt_f3 0.000 0.000 0.000
## .t1_nf_sh_tt_f4 0.000 0.000 0.000
## .t1_nf_sh_tt_f5 0.000 0.000 0.000
## .t3_nf_sh_tt_f1 0.000 0.000 0.000
## .t3_nf_sh_tt_f2 0.000 0.000 0.000
## .t3_nf_sh_tt_f3 0.000 0.000 0.000
## .t3_nf_sh_tt_f4 0.000 0.000 0.000
## .t3_nf_sh_tt_f5 0.000 0.000 0.000
## .t4_nf_sh_tt_f1 0.000 0.000 0.000
## .t4_nf_sh_tt_f2 0.000 0.000 0.000
## .t4_nf_sh_tt_f3 0.000 0.000 0.000
## .t4_nf_sh_tt_f4 0.000 0.000 0.000
## .t4_nf_sh_tt_f5 0.000 0.000 0.000
## .t5_nf_sh_tt_f1 0.000 0.000 0.000
## .t5_nf_sh_tt_f2 0.000 0.000 0.000
## .t5_nf_sh_tt_f3 0.000 0.000 0.000
## .t5_nf_sh_tt_f4 0.000 0.000 0.000
## .t5_nf_sh_tt_f5 0.000 0.000 0.000
## t1_inf_sh_bh_f 0.000 0.000 0.000
## t3_inf_sh_bh_f 0.000 0.000 0.000
## t4_inf_sh_bh_f 0.000 0.000 0.000
## t5_inf_sh_bh_f 0.000 0.000 0.000
## .t1_nf_sh_bh_f1 0.000 0.000 0.000
## .t1_nf_sh_bh_f2 0.000 0.000 0.000
## .t1_nf_sh_bh_f3 0.000 0.000 0.000
## .t1_nf_sh_bh_f4 0.000 0.000 0.000
## .t1_nf_sh_bh_f5 0.000 0.000 0.000
## .t3_nf_sh_bh_f1 0.000 0.000 0.000
## .t3_nf_sh_bh_f2 0.000 0.000 0.000
## .t3_nf_sh_bh_f3 0.000 0.000 0.000
## .t3_nf_sh_bh_f4 0.000 0.000 0.000
## .t3_nf_sh_bh_f5 0.000 0.000 0.000
## .t4_nf_sh_bh_f1 0.000 0.000 0.000
## .t4_nf_sh_bh_f2 0.000 0.000 0.000
## .t4_nf_sh_bh_f3 0.000 0.000 0.000
## .t4_nf_sh_bh_f4 0.000 0.000 0.000
## .t4_nf_sh_bh_f5 0.000 0.000 0.000
## .t5_nf_sh_bh_f1 0.000 0.000 0.000
## .t5_nf_sh_bh_f2 0.000 0.000 0.000
## .t5_nf_sh_bh_f3 0.000 0.000 0.000
## .t5_nf_sh_bh_f4 0.000 0.000 0.000
## .t5_nf_sh_bh_f5 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .t1_pri_con_04 0.347 0.024 14.322 0.000 0.347 0.311
## .t1_pri_con_05 0.977 0.053 18.566 0.000 0.977 0.572
## .t1_pri_con_06 0.593 0.035 17.043 0.000 0.593 0.430
## .t1_pri_con_07 0.572 0.034 16.821 0.000 0.572 0.363
## .t1_pri_con_08 0.419 0.027 15.608 0.000 0.419 0.307
## .t1_pri_con_09 0.321 0.021 15.357 0.000 0.321 0.293
## .t3_pri_con_04 0.399 0.025 15.980 0.000 0.399 0.358
## .t3_pri_con_05 1.028 0.054 19.021 0.000 1.028 0.602
## .t3_pri_con_06 0.546 0.032 17.239 0.000 0.546 0.428
## .t3_pri_con_07 0.481 0.029 16.369 0.000 0.481 0.314
## .t3_pri_con_08 0.358 0.024 15.045 0.000 0.358 0.266
## .t3_pri_con_09 0.339 0.021 15.970 0.000 0.339 0.295
## .t4_pri_con_04 0.373 0.024 15.375 0.000 0.373 0.330
## .t4_pri_con_05 0.945 0.050 18.790 0.000 0.945 0.568
## .t4_pri_con_06 0.509 0.030 16.962 0.000 0.509 0.398
## .t4_pri_con_07 0.514 0.031 16.639 0.000 0.514 0.339
## .t4_pri_con_08 0.363 0.024 15.086 0.000 0.363 0.278
## .t4_pri_con_09 0.359 0.022 16.267 0.000 0.359 0.317
## .t5_pri_con_04 0.318 0.022 14.204 0.000 0.318 0.280
## .t5_pri_con_05 0.970 0.051 18.902 0.000 0.970 0.555
## .t5_pri_con_06 0.488 0.029 16.860 0.000 0.488 0.369
## .t5_pri_con_07 0.526 0.031 16.995 0.000 0.526 0.334
## .t5_pri_con_08 0.360 0.024 15.331 0.000 0.360 0.267
## .t5_pri_con_09 0.331 0.021 15.833 0.000 0.331 0.291
## .t1_nf_sh_tt_01 0.684 0.058 11.812 0.000 0.684 0.541
## .t1_nf_sh_tt_02 0.742 0.054 13.838 0.000 0.742 0.610
## .t1_nf_sh_tt_03 0.180 0.014 12.905 0.000 0.180 0.168
## .t1_nf_sh_tt_04 0.197 0.014 14.107 0.000 0.197 0.187
## .t1_nf_sh_tt_05 0.111 0.013 8.796 0.000 0.111 0.100
## .t1_nf_sh_tt_06 0.260 0.016 16.243 0.000 0.260 0.221
## .t1_nf_sh_tt_07 0.466 0.032 14.613 0.000 0.466 0.395
## .t1_nf_sh_tt_08 0.576 0.032 17.903 0.000 0.576 0.510
## .t1_nf_sh_tt_10 0.195 0.026 7.401 0.000 0.195 0.168
## .t1_nf_sh_tt_11 0.186 0.025 7.396 0.000 0.186 0.168
## .t3_nf_sh_tt_01 0.747 0.057 13.194 0.000 0.747 0.596
## .t3_nf_sh_tt_02 0.700 0.050 14.083 0.000 0.700 0.627
## .t3_nf_sh_tt_03 0.147 0.013 11.116 0.000 0.147 0.141
## .t3_nf_sh_tt_04 0.196 0.014 13.963 0.000 0.196 0.186
## .t3_nf_sh_tt_05 0.161 0.015 10.847 0.000 0.161 0.151
## .t3_nf_sh_tt_06 0.294 0.019 15.894 0.000 0.294 0.262
## .t3_nf_sh_tt_07 0.497 0.032 15.629 0.000 0.497 0.448
## .t3_nf_sh_tt_08 0.592 0.032 18.279 0.000 0.592 0.554
## .t3_nf_sh_tt_10 0.131 0.025 5.317 0.000 0.131 0.122
## .t3_nf_sh_tt_11 0.177 0.024 7.245 0.000 0.177 0.164
## .t4_nf_sh_tt_01 0.892 0.066 13.463 0.000 0.892 0.610
## .t4_nf_sh_tt_02 0.697 0.055 12.663 0.000 0.697 0.598
## .t4_nf_sh_tt_03 0.504 0.030 16.843 0.000 0.504 0.422
## .t4_nf_sh_tt_04 0.374 0.025 14.776 0.000 0.374 0.360
## .t4_nf_sh_tt_05 0.143 0.015 9.849 0.000 0.143 0.148
## .t4_nf_sh_tt_06 0.296 0.018 16.317 0.000 0.296 0.281
## .t4_nf_sh_tt_07 0.507 0.032 15.618 0.000 0.507 0.481
## .t4_nf_sh_tt_08 0.614 0.034 18.105 0.000 0.614 0.591
## .t4_nf_sh_tt_10 0.141 0.024 5.922 0.000 0.141 0.140
## .t4_nf_sh_tt_11 0.161 0.022 7.315 0.000 0.161 0.162
## .t5_nf_sh_tt_01 0.855 0.070 12.237 0.000 0.855 0.582
## .t5_nf_sh_tt_02 0.696 0.055 12.582 0.000 0.696 0.580
## .t5_nf_sh_tt_03 0.519 0.030 17.217 0.000 0.519 0.439
## .t5_nf_sh_tt_04 0.393 0.025 15.883 0.000 0.393 0.382
## .t5_nf_sh_tt_05 0.099 0.014 7.299 0.000 0.099 0.099
## .t5_nf_sh_tt_06 0.317 0.019 16.498 0.000 0.317 0.278
## .t5_nf_sh_tt_07 0.522 0.034 15.484 0.000 0.522 0.493
## .t5_nf_sh_tt_08 0.616 0.034 17.944 0.000 0.616 0.596
## .t5_nf_sh_tt_10 0.103 0.023 4.574 0.000 0.103 0.103
## .t5_nf_sh_tt_11 0.164 0.022 7.430 0.000 0.164 0.161
## .t1_nf_sh_bh_01 0.793 0.060 13.240 0.000 0.793 0.670
## .t1_nf_sh_bh_02 0.302 0.016 18.320 0.000 0.302 0.810
## .t1_nf_sh_bh_03 0.072 0.007 10.563 0.000 0.072 0.070
## .t1_nf_sh_bh_04 0.067 0.007 9.892 0.000 0.067 0.066
## .t1_nf_sh_bh_05 0.050 0.007 6.750 0.000 0.050 0.053
## .t1_nf_sh_bh_06 0.153 0.009 16.308 0.000 0.153 0.158
## .t1_nf_sh_bh_07 0.360 0.024 15.099 0.000 0.360 0.341
## .t1_nf_sh_bh_08 0.515 0.027 18.870 0.000 0.515 0.497
## .t1_nf_sh_bh_10 0.116 0.019 6.138 0.000 0.116 0.141
## .t1_nf_sh_bh_11 0.194 0.017 11.740 0.000 0.194 0.261
## .t3_nf_sh_bh_01 0.934 0.061 15.318 0.000 0.934 0.765
## .t3_nf_sh_bh_02 0.238 0.013 17.882 0.000 0.238 0.821
## .t3_nf_sh_bh_03 0.069 0.006 10.820 0.000 0.069 0.078
## .t3_nf_sh_bh_04 0.072 0.007 10.991 0.000 0.072 0.081
## .t3_nf_sh_bh_05 0.056 0.007 7.581 0.000 0.056 0.066
## .t3_nf_sh_bh_06 0.145 0.009 15.819 0.000 0.145 0.168
## .t3_nf_sh_bh_07 0.351 0.023 15.154 0.000 0.351 0.349
## .t3_nf_sh_bh_08 0.435 0.024 18.404 0.000 0.435 0.471
## .t3_nf_sh_bh_10 0.105 0.017 6.176 0.000 0.105 0.139
## .t3_nf_sh_bh_11 0.147 0.014 10.520 0.000 0.147 0.223
## .t4_nf_sh_bh_01 1.045 0.074 14.181 0.000 1.045 0.691
## .t4_nf_sh_bh_02 0.249 0.015 16.828 0.000 0.249 0.747
## .t4_nf_sh_bh_03 0.130 0.011 11.989 0.000 0.130 0.135
## .t4_nf_sh_bh_04 0.138 0.011 12.613 0.000 0.138 0.143
## .t4_nf_sh_bh_05 0.094 0.011 8.947 0.000 0.094 0.104
## .t4_nf_sh_bh_06 0.197 0.012 15.832 0.000 0.197 0.210
## .t4_nf_sh_bh_07 0.419 0.027 15.719 0.000 0.419 0.413
## .t4_nf_sh_bh_08 0.519 0.028 18.805 0.000 0.519 0.539
## .t4_nf_sh_bh_10 0.125 0.017 7.158 0.000 0.125 0.160
## .t4_nf_sh_bh_11 0.156 0.015 10.783 0.000 0.156 0.233
## .t5_nf_sh_bh_01 -2.452 0.362 -6.781 0.000 -2.452 -1.147
## .t5_nf_sh_bh_02 1.813 0.118 15.341 0.000 1.813 0.686
## .t5_nf_sh_bh_03 0.080 0.007 11.660 0.000 0.080 0.045
## .t5_nf_sh_bh_04 0.103 0.007 13.710 0.000 0.103 0.058
## .t5_nf_sh_bh_05 0.006 0.007 0.923 0.356 0.006 0.004
## .t5_nf_sh_bh_06 0.172 0.010 16.581 0.000 0.172 0.098
## .t5_nf_sh_bh_07 0.335 0.029 11.685 0.000 0.335 0.194
## .t5_nf_sh_bh_08 0.760 0.041 18.366 0.000 0.760 0.422
## .t5_nf_sh_bh_10 -0.133 0.043 -3.073 0.002 -0.133 -0.070
## .t5_nf_sh_bh_11 0.331 0.039 8.563 0.000 0.331 0.172
## t1_pri_con_f 0.669 0.043 15.569 0.000 1.000 1.000
## t3_pri_con_f 0.700 0.044 15.965 0.000 1.000 1.000
## t4_pri_con_f 0.701 0.044 15.968 0.000 1.000 1.000
## t5_pri_con_f 0.737 0.046 16.075 0.000 1.000 1.000
## .t1_pri_con_f1 0.102 0.019 5.459 0.000 0.132 0.132
## .t1_pri_con_f2 0.108 0.022 4.890 0.000 0.107 0.107
## .t3_pri_con_f1 0.017 0.015 1.109 0.267 0.024 0.024
## .t3_pri_con_f2 0.114 0.020 5.735 0.000 0.108 0.108
## .t4_pri_con_f1 0.056 0.016 3.393 0.001 0.073 0.073
## .t4_pri_con_f2 0.063 0.019 3.330 0.001 0.063 0.063
## .t5_pri_con_f1 0.081 0.017 4.649 0.000 0.099 0.099
## .t5_pri_con_f2 0.060 0.019 3.074 0.002 0.057 0.057
## t1_inf_sh_tt_f 0.127 0.017 7.326 0.000 1.000 1.000
## t3_inf_sh_tt_f 0.117 0.016 7.305 0.000 1.000 1.000
## t4_inf_sh_tt_f 0.102 0.014 7.280 0.000 1.000 1.000
## t5_inf_sh_tt_f 0.107 0.015 7.269 0.000 1.000 1.000
## .t1_nf_sh_tt_f1 0.453 0.052 8.774 0.000 0.781 0.781
## .t1_nf_sh_tt_f2 0.070 0.014 5.027 0.000 0.079 0.079
## .t1_nf_sh_tt_f3 0.133 0.016 8.137 0.000 0.134 0.134
## .t1_nf_sh_tt_f4 0.145 0.023 6.340 0.000 0.203 0.203
## .t1_nf_sh_tt_f5 0.707 0.044 16.071 0.000 0.733 0.733
## .t3_nf_sh_tt_f1 0.390 0.047 8.377 0.000 0.770 0.770
## .t3_nf_sh_tt_f2 0.139 0.016 8.865 0.000 0.156 0.156
## .t3_nf_sh_tt_f3 0.107 0.016 6.464 0.000 0.118 0.118
## .t3_nf_sh_tt_f4 0.090 0.021 4.208 0.000 0.146 0.146
## .t3_nf_sh_tt_f5 0.706 0.043 16.422 0.000 0.748 0.748
## .t4_nf_sh_tt_f1 0.470 0.054 8.634 0.000 0.822 0.822
## .t4_nf_sh_tt_f2 0.033 0.018 1.799 0.072 0.047 0.047
## .t4_nf_sh_tt_f3 0.131 0.017 7.630 0.000 0.159 0.159
## .t4_nf_sh_tt_f4 0.092 0.022 4.298 0.000 0.169 0.169
## .t4_nf_sh_tt_f5 0.661 0.041 16.309 0.000 0.762 0.762
## .t5_nf_sh_tt_f1 0.508 0.058 8.782 0.000 0.826 0.826
## .t5_nf_sh_tt_f2 -0.030 0.017 -1.785 0.074 -0.045 -0.045
## .t5_nf_sh_tt_f3 0.168 0.018 9.198 0.000 0.187 0.187
## .t5_nf_sh_tt_f4 0.058 0.021 2.761 0.006 0.107 0.107
## .t5_nf_sh_tt_f5 0.679 0.041 16.607 0.000 0.757 0.757
## t1_inf_sh_bh_f 0.148 0.015 9.689 0.000 1.000 1.000
## t3_inf_sh_bh_f 0.127 0.013 9.666 0.000 1.000 1.000
## t4_inf_sh_bh_f 0.127 0.013 9.609 0.000 1.000 1.000
## t5_inf_sh_bh_f 0.297 0.031 9.647 0.000 1.000 1.000
## .t1_nf_sh_bh_f1 0.243 0.047 5.215 0.000 0.621 0.621
## .t1_nf_sh_bh_f2 0.127 0.012 10.872 0.000 0.133 0.133
## .t1_nf_sh_bh_f3 0.090 0.011 8.079 0.000 0.101 0.101
## .t1_nf_sh_bh_f4 0.013 0.016 0.810 0.418 0.019 0.019
## .t1_nf_sh_bh_f5 0.478 0.030 15.803 0.000 0.679 0.679
## .t3_nf_sh_bh_f1 0.159 0.040 3.976 0.000 0.557 0.557
## .t3_nf_sh_bh_f2 0.109 0.011 10.249 0.000 0.133 0.133
## .t3_nf_sh_bh_f3 0.094 0.011 8.802 0.000 0.120 0.120
## .t3_nf_sh_bh_f4 0.066 0.016 4.079 0.000 0.101 0.101
## .t3_nf_sh_bh_f5 0.460 0.028 16.172 0.000 0.703 0.703
## .t4_nf_sh_bh_f1 0.340 0.055 6.158 0.000 0.728 0.728
## .t4_nf_sh_bh_f2 0.122 0.014 8.966 0.000 0.147 0.147
## .t4_nf_sh_bh_f3 0.121 0.014 8.795 0.000 0.149 0.149
## .t4_nf_sh_bh_f4 0.008 0.017 0.468 0.640 0.013 0.013
## .t4_nf_sh_bh_f5 0.462 0.029 15.913 0.000 0.704 0.704
## .t5_nf_sh_bh_f1 4.293 0.398 10.792 0.000 0.935 0.935
## .t5_nf_sh_bh_f2 0.024 0.010 2.425 0.015 0.014 0.014
## .t5_nf_sh_bh_f3 0.119 0.013 9.030 0.000 0.069 0.069
## .t5_nf_sh_bh_f4 0.024 0.023 1.041 0.298 0.017 0.017
## .t5_nf_sh_bh_f5 1.579 0.090 17.618 0.000 0.777 0.777Extract factor scores.
d_fs_all <- lavPredict(get(paste("fit", name, sep = "_")), type = "ov") %>% as.data.frame() %>% mutate(t1_pri_con_fs = rowMeans(select(.,
starts_with("t1_pri"))), t3_pri_con_fs = rowMeans(select(., starts_with("t3_pri"))), t4_pri_con_fs = rowMeans(select(.,
starts_with("t4_pri"))), t5_pri_con_fs = rowMeans(select(., starts_with("t5_pri"))), t1_inf_sha_att_fs = rowMeans(select(.,
starts_with("t1_inf_sha_att"))), t3_inf_sha_att_fs = rowMeans(select(., starts_with("t3_inf_sha_att"))), t4_inf_sha_att_fs = rowMeans(select(.,
starts_with("t4_inf_sha_att"))), t5_inf_sha_att_fs = rowMeans(select(., starts_with("t5_inf_sha_att"))), t1_inf_sha_beh_fs = rowMeans(select(.,
starts_with("t1_inf_sha_beh"))), t3_inf_sha_beh_fs = rowMeans(select(., starts_with("t3_inf_sha_beh"))), t4_inf_sha_beh_fs = rowMeans(select(.,
starts_with("t4_inf_sha_beh"))), t5_inf_sha_beh_fs = rowMeans(select(., starts_with("t5_inf_sha_beh")))) %>% select(contains("_fs"))
d_wide_all <- cbind(d_fs_all, d_wide_all)Run new model.
model <- '
# between relations
pri_con_b =~ 1*t1_pri_con_fs + 1*t3_pri_con_fs + 1*t4_pri_con_fs + 1*t5_pri_con_fs
inf_sha_beh_b =~ 1*t1_inf_sha_beh_fs + 1*t3_inf_sha_beh_fs + 1*t4_inf_sha_beh_fs + 1*t5_inf_sha_beh_fs
inf_sha_att_b =~ 1*t1_inf_sha_att_fs + 1*t3_inf_sha_att_fs + 1*t4_inf_sha_att_fs + 1*t5_inf_sha_att_fs
# within person changes
t1_pri_con_w =~ 1*t1_pri_con_fs
t3_pri_con_w =~ 1*t3_pri_con_fs
t4_pri_con_w =~ 1*t4_pri_con_fs
t5_pri_con_w =~ 1*t5_pri_con_fs
t1_inf_sha_beh_w =~ 1*t1_inf_sha_beh_fs
t3_inf_sha_beh_w =~ 1*t3_inf_sha_beh_fs
t4_inf_sha_beh_w =~ 1*t4_inf_sha_beh_fs
t5_inf_sha_beh_w =~ 1*t5_inf_sha_beh_fs
t1_inf_sha_att_w =~ 1*t1_inf_sha_att_fs
t3_inf_sha_att_w =~ 1*t3_inf_sha_att_fs
t4_inf_sha_att_w =~ 1*t4_inf_sha_att_fs
t5_inf_sha_att_w =~ 1*t5_inf_sha_att_fs
# within person effects
t3_pri_con_w ~ a1*t1_pri_con_w + a2*t1_inf_sha_att_w + a3*t1_inf_sha_beh_w
t3_inf_sha_att_w ~ b1*t1_pri_con_w + b2*t1_inf_sha_att_w + b3*t1_inf_sha_beh_w
t3_inf_sha_beh_w ~ c1*t1_pri_con_w + c2*t1_inf_sha_att_w + c3*t1_inf_sha_beh_w
t4_pri_con_w ~ a1*t3_pri_con_w + a2*t3_inf_sha_att_w + a3*t3_inf_sha_beh_w
t4_inf_sha_att_w ~ b1*t3_pri_con_w + b2*t3_inf_sha_att_w + b3*t3_inf_sha_beh_w
t4_inf_sha_beh_w ~ c1*t3_pri_con_w + c2*t3_inf_sha_att_w + c3*t3_inf_sha_beh_w
t5_pri_con_w ~ a1*t4_pri_con_w + a2*t4_inf_sha_att_w + a3*t4_inf_sha_beh_w
t5_inf_sha_att_w ~ b1*t4_pri_con_w + b2*t4_inf_sha_att_w + b3*t4_inf_sha_beh_w
t5_inf_sha_beh_w ~ c1*t4_pri_con_w + c2*t4_inf_sha_att_w + c3*t4_inf_sha_beh_w
# covariances
pri_con_b ~~ cor_b_1*inf_sha_att_b + cor_b_2*inf_sha_beh_b
inf_sha_att_b ~~ cor_b_3*inf_sha_beh_b
t1_pri_con_w ~~ cor_w_1*t1_inf_sha_att_w + cor_w_2*t1_inf_sha_beh_w
t1_inf_sha_att_w ~~ cor_w_3*t1_inf_sha_beh_w
t3_pri_con_w ~~ a*t3_inf_sha_att_w + b*t3_inf_sha_beh_w
t3_inf_sha_att_w ~~ c*t3_inf_sha_beh_w
t4_pri_con_w ~~ a*t4_inf_sha_att_w + b*t4_inf_sha_beh_w
t4_inf_sha_att_w ~~ c*t4_inf_sha_beh_w
t5_pri_con_w ~~ a*t5_inf_sha_att_w + b*t5_inf_sha_beh_w
t5_inf_sha_att_w ~~ c*t5_inf_sha_beh_w
# setting variances of observed variables to zero
t1_pri_con_fs ~~ 0*t1_pri_con_fs
t3_pri_con_fs ~~ 0*t3_pri_con_fs
t4_pri_con_fs ~~ 0*t4_pri_con_fs
t5_pri_con_fs ~~ 0*t5_pri_con_fs
t1_inf_sha_att_fs ~~ 0*t1_inf_sha_att_fs
t3_inf_sha_att_fs ~~ 0*t3_inf_sha_att_fs
t4_inf_sha_att_fs ~~ 0*t4_inf_sha_att_fs
t5_inf_sha_att_fs ~~ 0*t5_inf_sha_att_fs
t1_inf_sha_beh_fs ~~ 0*t1_inf_sha_beh_fs
t3_inf_sha_beh_fs ~~ 0*t3_inf_sha_beh_fs
t4_inf_sha_beh_fs ~~ 0*t4_inf_sha_beh_fs
t5_inf_sha_beh_fs ~~ 0*t5_inf_sha_beh_fs
# control variables
t1_pri_con_fs ~ age + edu_num + male
t3_pri_con_fs ~ age + edu_num + male
t4_pri_con_fs ~ age + edu_num + male
t5_pri_con_fs ~ age + edu_num + male
t1_inf_sha_beh_fs ~ age + edu_num + male
t3_inf_sha_beh_fs ~ age + edu_num + male
t4_inf_sha_beh_fs ~ age + edu_num + male
t5_inf_sha_beh_fs ~ age + edu_num + male
t1_inf_sha_att_fs ~ age + edu_num + male
t3_inf_sha_att_fs ~ age + edu_num + male
t4_inf_sha_att_fs ~ age + edu_num + male
t5_inf_sha_att_fs ~ age + edu_num + male
'
fit <- sem(model, data = d_wide_all, orthogonal = TRUE, missing = "ML")
summary(fit, standardized = TRUE, fit.measures = TRUE, ci = TRUE)## lavaan 0.6-7 ended normally after 198 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 105
## Number of equality constraints 24
##
## Used Total
## Number of observations 803 893
## Number of missing patterns 1
##
## Model Test User Model:
##
## Test statistic 308.866
## Degrees of freedom 45
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 5562.601
## Degrees of freedom 102
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.952
## Tucker-Lewis Index (TLI) 0.890
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -8286.383
## Loglikelihood unrestricted model (H1) -8131.950
##
## Akaike (AIC) 16734.767
## Bayesian (BIC) 17114.524
## Sample-size adjusted Bayesian (BIC) 16857.303
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.085
## 90 Percent confidence interval - lower 0.077
## 90 Percent confidence interval - upper 0.095
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.082
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b =~
## t1_pri_con_fs 1.000 1.000 1.000 0.721 0.852
## t3_pri_con_fs 1.000 1.000 1.000 0.721 0.842
## t4_pri_con_fs 1.000 1.000 1.000 0.721 0.831
## t5_pri_con_fs 1.000 1.000 1.000 0.721 0.829
## inf_sha_beh_b =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.418 0.649
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.418 0.707
## t4_nf_sh_bh_fs 1.000 1.000 1.000 0.418 0.696
## t5_nf_sh_bh_fs 1.000 1.000 1.000 0.418 0.284
## inf_sha_att_b =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.461 0.668
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.461 0.697
## t4_nf_sh_tt_fs 1.000 1.000 1.000 0.461 0.734
## t5_nf_sh_tt_fs 1.000 1.000 1.000 0.461 0.711
## t1_pri_con_w =~
## t1_pri_con_fs 1.000 1.000 1.000 0.412 0.487
## t3_pri_con_w =~
## t3_pri_con_fs 1.000 1.000 1.000 0.432 0.505
## t4_pri_con_w =~
## t4_pri_con_fs 1.000 1.000 1.000 0.453 0.522
## t5_pri_con_w =~
## t5_pri_con_fs 1.000 1.000 1.000 0.449 0.516
## t1_inf_sha_beh_w =~
## t1_nf_sh_bh_fs 1.000 1.000 1.000 0.472 0.732
## t3_inf_sha_beh_w =~
## t3_nf_sh_bh_fs 1.000 1.000 1.000 0.390 0.659
## t4_inf_sha_beh_w =~
## t4_nf_sh_bh_fs 1.000 1.000 1.000 0.406 0.676
## t5_inf_sha_beh_w =~
## t5_nf_sh_bh_fs 1.000 1.000 1.000 1.409 0.955
## t1_inf_sha_att_w =~
## t1_nf_sh_tt_fs 1.000 1.000 1.000 0.496 0.719
## t3_inf_sha_att_w =~
## t3_nf_sh_tt_fs 1.000 1.000 1.000 0.454 0.686
## t4_inf_sha_att_w =~
## t4_nf_sh_tt_fs 1.000 1.000 1.000 0.405 0.644
## t5_inf_sha_att_w =~
## t5_nf_sh_tt_fs 1.000 1.000 1.000 0.435 0.670
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## t3_pri_con_w ~
## t1_pr_cn_ (a1) 0.263 0.043 6.163 0.000 0.180 0.347 0.251 0.251
## t1_nf_s__ (a2) 0.011 0.028 0.408 0.683 -0.043 0.066 0.013 0.013
## t1_nf_s__ (a3) -0.039 0.033 -1.202 0.229 -0.104 0.025 -0.043 -0.043
## t3_inf_sha_att_w ~
## t1_pr_cn_ (b1) 0.084 0.032 2.599 0.009 0.021 0.147 0.076 0.076
## t1_nf_s__ (b2) 0.075 0.034 2.209 0.027 0.008 0.141 0.082 0.082
## t1_nf_s__ (b3) 0.049 0.033 1.499 0.134 -0.015 0.114 0.051 0.051
## t3_inf_sha_beh_w ~
## t1_pr_cn_ (c1) 0.013 0.040 0.332 0.740 -0.065 0.091 0.014 0.014
## t1_nf_s__ (c2) 0.005 0.032 0.173 0.863 -0.057 0.067 0.007 0.007
## t1_nf_s__ (c3) 0.110 0.054 2.057 0.040 0.005 0.215 0.133 0.133
## t4_pri_con_w ~
## t3_pr_cn_ (a1) 0.263 0.043 6.163 0.000 0.180 0.347 0.252 0.252
## t3_nf_s__ (a2) 0.011 0.028 0.408 0.683 -0.043 0.066 0.011 0.011
## t3_nf_s__ (a3) -0.039 0.033 -1.202 0.229 -0.104 0.025 -0.034 -0.034
## t4_inf_sha_att_w ~
## t3_pr_cn_ (b1) 0.084 0.032 2.599 0.009 0.021 0.147 0.089 0.089
## t3_nf_s__ (b2) 0.075 0.034 2.209 0.027 0.008 0.141 0.084 0.084
## t3_nf_s__ (b3) 0.049 0.033 1.499 0.134 -0.015 0.114 0.047 0.047
## t4_inf_sha_beh_w ~
## t3_pr_cn_ (c1) 0.013 0.040 0.332 0.740 -0.065 0.091 0.014 0.014
## t3_nf_s__ (c2) 0.005 0.032 0.173 0.863 -0.057 0.067 0.006 0.006
## t3_nf_s__ (c3) 0.110 0.054 2.057 0.040 0.005 0.215 0.106 0.106
## t5_pri_con_w ~
## t4_pr_cn_ (a1) 0.263 0.043 6.163 0.000 0.180 0.347 0.265 0.265
## t4_nf_s__ (a2) 0.011 0.028 0.408 0.683 -0.043 0.066 0.010 0.010
## t4_nf_s__ (a3) -0.039 0.033 -1.202 0.229 -0.104 0.025 -0.036 -0.036
## t5_inf_sha_att_w ~
## t4_pr_cn_ (b1) 0.084 0.032 2.599 0.009 0.021 0.147 0.087 0.087
## t4_nf_s__ (b2) 0.075 0.034 2.209 0.027 0.008 0.141 0.070 0.070
## t4_nf_s__ (b3) 0.049 0.033 1.499 0.134 -0.015 0.114 0.046 0.046
## t5_inf_sha_beh_w ~
## t4_pr_cn_ (c1) 0.013 0.040 0.332 0.740 -0.065 0.091 0.004 0.004
## t4_nf_s__ (c2) 0.005 0.032 0.173 0.863 -0.057 0.067 0.002 0.002
## t4_nf_s__ (c3) 0.110 0.054 2.057 0.040 0.005 0.215 0.032 0.032
## t1_pri_con_fs ~
## age 0.011 0.002 5.240 0.000 0.007 0.015 0.011 0.187
## edu_num -0.029 0.017 -1.678 0.093 -0.062 0.005 -0.029 -0.059
## male -0.019 0.061 -0.303 0.762 -0.138 0.101 -0.019 -0.011
## t3_pri_con_fs ~
## age 0.011 0.002 5.034 0.000 0.007 0.015 0.011 0.180
## edu_num -0.035 0.017 -2.009 0.044 -0.068 -0.001 -0.035 -0.071
## male -0.023 0.062 -0.372 0.710 -0.144 0.098 -0.023 -0.013
## t4_pri_con_fs ~
## age 0.011 0.002 4.992 0.000 0.007 0.015 0.011 0.178
## edu_num -0.045 0.017 -2.596 0.009 -0.079 -0.011 -0.045 -0.091
## male -0.014 0.063 -0.220 0.826 -0.137 0.109 -0.014 -0.008
## t5_pri_con_fs ~
## age 0.012 0.002 5.736 0.000 0.008 0.016 0.012 0.204
## edu_num -0.039 0.017 -2.260 0.024 -0.073 -0.005 -0.039 -0.079
## male -0.019 0.062 -0.307 0.759 -0.142 0.103 -0.019 -0.011
## t1_inf_sha_beh_fs ~
## age -0.007 0.002 -4.311 0.000 -0.010 -0.004 -0.007 -0.153
## edu_num 0.051 0.013 3.984 0.000 0.026 0.077 0.051 0.139
## male -0.113 0.046 -2.433 0.015 -0.204 -0.022 -0.113 -0.087
## t3_inf_sha_beh_fs ~
## age -0.006 0.001 -4.397 0.000 -0.009 -0.004 -0.006 -0.155
## edu_num 0.070 0.012 5.999 0.000 0.047 0.093 0.070 0.207
## male -0.097 0.042 -2.307 0.021 -0.180 -0.015 -0.097 -0.082
## t4_inf_sha_beh_fs ~
## age -0.008 0.001 -5.440 0.000 -0.011 -0.005 -0.008 -0.192
## edu_num 0.058 0.012 4.871 0.000 0.035 0.082 0.058 0.169
## male -0.021 0.043 -0.490 0.624 -0.105 0.063 -0.021 -0.017
## t5_inf_sha_beh_fs ~
## age 0.007 0.004 1.772 0.076 -0.001 0.014 0.007 0.064
## edu_num -0.048 0.030 -1.607 0.108 -0.107 0.011 -0.048 -0.057
## male -0.013 0.108 -0.125 0.901 -0.225 0.198 -0.013 -0.005
## t1_inf_sha_att_fs ~
## age -0.003 0.002 -2.018 0.044 -0.007 -0.000 -0.003 -0.072
## edu_num 0.027 0.014 1.967 0.049 0.000 0.054 0.027 0.069
## male -0.239 0.050 -4.786 0.000 -0.336 -0.141 -0.239 -0.172
## t3_inf_sha_att_fs ~
## age -0.005 0.002 -3.208 0.001 -0.008 -0.002 -0.005 -0.114
## edu_num 0.047 0.013 3.548 0.000 0.021 0.073 0.047 0.124
## male -0.188 0.048 -3.945 0.000 -0.281 -0.095 -0.188 -0.141
## t4_inf_sha_att_fs ~
## age -0.006 0.002 -3.664 0.000 -0.009 -0.003 -0.006 -0.130
## edu_num 0.047 0.013 3.777 0.000 0.023 0.072 0.047 0.132
## male -0.178 0.045 -3.940 0.000 -0.266 -0.089 -0.178 -0.141
## t5_inf_sha_att_fs ~
## age -0.006 0.002 -3.766 0.000 -0.009 -0.003 -0.006 -0.134
## edu_num 0.051 0.013 3.954 0.000 0.026 0.077 0.051 0.138
## male -0.165 0.047 -3.531 0.000 -0.256 -0.073 -0.165 -0.126
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## pri_con_b ~~
## in___ (cr_b_1) -0.118 0.015 -7.810 0.000 -0.148 -0.089 -0.355 -0.355
## in___ (cr_b_2) -0.044 0.014 -3.104 0.002 -0.072 -0.016 -0.147 -0.147
## inf_sha_beh_b ~~
## in___ (cr_b_3) 0.127 0.011 11.406 0.000 0.105 0.149 0.659 0.659
## t1_pri_con_w ~~
## t1___ (cr_w_1) -0.013 0.010 -1.274 0.203 -0.033 0.007 -0.063 -0.063
## t1___ (cr_w_2) -0.014 0.010 -1.372 0.170 -0.034 0.006 -0.072 -0.072
## t1_inf_sha_beh_w ~~
## t1___ (cr_w_3) 0.048 0.011 4.299 0.000 0.026 0.070 0.205 0.205
## .t3_pri_con_w ~~
## .t3___ (a) -0.012 0.005 -2.134 0.033 -0.022 -0.001 -0.062 -0.062
## .t3___ (b) -0.002 0.006 -0.322 0.747 -0.015 0.010 -0.013 -0.013
## .t3_inf_sha_beh_w ~~
## .t3___ (c) 0.036 0.006 5.724 0.000 0.024 0.048 0.207 0.207
## .t4_pri_con_w ~~
## .t4___ (a) -0.012 0.005 -2.134 0.033 -0.022 -0.001 -0.067 -0.067
## .t4___ (b) -0.002 0.006 -0.322 0.747 -0.015 0.010 -0.012 -0.012
## .t4_inf_sha_beh_w ~~
## .t4___ (c) 0.036 0.006 5.724 0.000 0.024 0.048 0.222 0.222
## .t5_pri_con_w ~~
## .t5___ (a) -0.012 0.005 -2.134 0.033 -0.022 -0.001 -0.063 -0.063
## .t5___ (b) -0.002 0.006 -0.322 0.747 -0.015 0.010 -0.003 -0.003
## .t5_inf_sha_beh_w ~~
## .t5___ (c) 0.036 0.006 5.724 0.000 0.024 0.048 0.059 0.059
## pri_con_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b ~~
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
## t1___ 0.000 0.000 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 3.243 0.189 17.198 0.000 2.874 3.613 3.243 3.831
## .t3_pri_con_fs 3.207 0.191 16.797 0.000 2.833 3.581 3.207 3.744
## .t4_pri_con_fs 3.180 0.193 16.446 0.000 2.801 3.559 3.180 3.663
## .t5_pri_con_fs 3.024 0.193 15.677 0.000 2.646 3.402 3.024 3.477
## .t1_nf_sh_bh_fs 2.503 0.143 17.484 0.000 2.222 2.784 2.503 3.882
## .t3_nf_sh_bh_fs 2.339 0.130 18.010 0.000 2.084 2.593 2.339 3.952
## .t4_nf_sh_bh_fs 2.429 0.132 18.361 0.000 2.170 2.689 2.429 4.045
## .t5_nf_sh_bh_fs 2.613 0.334 7.827 0.000 1.958 3.267 2.613 1.771
## .t1_nf_sh_tt_fs 2.870 0.154 18.653 0.000 2.568 3.172 2.870 4.158
## .t3_nf_sh_tt_fs 2.887 0.147 19.636 0.000 2.598 3.175 2.887 4.361
## .t4_nf_sh_tt_fs 2.792 0.139 20.036 0.000 2.519 3.065 2.792 4.440
## .t5_nf_sh_tt_fs 2.818 0.144 19.575 0.000 2.536 3.100 2.818 4.340
## pri_con_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_beh_b 0.000 0.000 0.000 0.000 0.000
## inf_sha_att_b 0.000 0.000 0.000 0.000 0.000
## t1_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t4_pri_con_w 0.000 0.000 0.000 0.000 0.000
## .t5_pri_con_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t4_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## .t5_inf_sh_bh_w 0.000 0.000 0.000 0.000 0.000
## t1_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t3_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t4_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
## .t5_inf_sh_tt_w 0.000 0.000 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper Std.lv Std.all
## .t1_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t3_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t4_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t5_pri_con_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t4_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t5_nf_sh_tt_fs 0.000 0.000 0.000 0.000 0.000
## .t1_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t3_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t4_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## .t5_nf_sh_bh_fs 0.000 0.000 0.000 0.000 0.000
## pri_con_b 0.520 0.030 17.329 0.000 0.462 0.579 1.000 1.000
## inf_sha_beh_b 0.175 0.016 11.151 0.000 0.144 0.206 1.000 1.000
## inf_sha_att_b 0.213 0.014 14.980 0.000 0.185 0.241 1.000 1.000
## t1_pri_con_w 0.170 0.013 12.665 0.000 0.143 0.196 1.000 1.000
## .t3_pri_con_w 0.175 0.012 14.045 0.000 0.150 0.199 0.934 0.934
## .t4_pri_con_w 0.192 0.014 13.990 0.000 0.165 0.219 0.936 0.936
## .t5_pri_con_w 0.187 0.012 16.143 0.000 0.165 0.210 0.928 0.928
## t1_inf_sh_bh_w 0.223 0.017 13.215 0.000 0.190 0.256 1.000 1.000
## .t3_inf_sh_bh_w 0.149 0.013 11.276 0.000 0.123 0.175 0.982 0.982
## .t4_inf_sh_bh_w 0.163 0.011 14.544 0.000 0.141 0.185 0.988 0.988
## .t5_inf_sh_bh_w 1.985 0.101 19.667 0.000 1.787 2.182 0.999 0.999
## t1_inf_sh_tt_w 0.246 0.015 16.263 0.000 0.217 0.276 1.000 1.000
## .t3_inf_sh_tt_w 0.203 0.013 15.964 0.000 0.178 0.228 0.985 0.985
## .t4_inf_sh_tt_w 0.161 0.011 14.001 0.000 0.138 0.183 0.982 0.982
## .t5_inf_sh_tt_w 0.186 0.012 16.136 0.000 0.164 0.209 0.985 0.985fit_riclpm_5w <- fitThe results show the same between person effects. Within-person effects disappear, which is understandable given the longer interval. Effects hence remain stable also across longer time intervals and until 2018.
2.2 Mixed Models
In what follows, we also present the results of several mixed models. Using mixed models, we can include more data. However, one downside is that not all research questions can be answered in one single model.
2.2.1 Two Variables
2.2.1.1 Model 1
Measures overall correlation between privacy concerns and information sharing.
fit <- lmer(pri_con_m ~ 1 + inf_sha_beh_m + (1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: pri_con_m ~ 1 + inf_sha_beh_m + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 16584
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.758 -0.477 0.061 0.516 4.998
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.5807 0.7620
## wave (Intercept) 0.0035 0.0592
## Residual 0.2243 0.4736
## Number of obs: 8191, groups: id, 2735; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 3.65461 0.03721 98.21
## inf_sha_beh_m -0.02822 0.00913 -3.09
##
## Correlation of Fixed Effects:
## (Intr)
## inf_sh_bh_m -0.551std_beta(fit)2.2.1.2 Model 2
Measures how current levels of information sharing are affected by generel levels of privacy concern und current levels of privacy concern.
fit <- lmer(inf_sha_beh_m ~ pri_con_m_b + pri_con_m_w + (1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: inf_sha_beh_m ~ pri_con_m_b + pri_con_m_w + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 18196
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.589 -0.512 -0.069 0.474 4.228
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.1421 0.377
## wave (Intercept) 0.0749 0.274
## Residual 0.4329 0.658
## Number of obs: 8191, groups: id, 2735; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 2.24448 0.12293 18.26
## pri_con_m_b -0.06339 0.01150 -5.51
## pri_con_m_w -0.00259 0.01881 -0.14
##
## Correlation of Fixed Effects:
## (Intr) pr_cn_m_b
## pri_con_m_b 0.002
## pri_con_m_w 0.004 0.003std_beta(fit)Measures how current levels of privacy concern are affected by generel levels of information sharing und current levels of information sharing.
fit <- lmer(pri_con_m ~ inf_sha_beh_m_b + inf_sha_beh_m_w + (1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: pri_con_m ~ inf_sha_beh_m_b + inf_sha_beh_m_w + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 16576
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.726 -0.480 0.059 0.511 5.007
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.57905 0.7610
## wave (Intercept) 0.00345 0.0587
## Residual 0.22409 0.4734
## Number of obs: 8191, groups: id, 2735; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 3.60976 0.03130 115.32
## inf_sha_beh_m_b -0.11176 0.02451 -4.56
## inf_sha_beh_m_w -0.01542 0.00927 -1.66
##
## Correlation of Fixed Effects:
## (Intr) inf_sh_bh_m_b
## inf_sh_bh_m_b -0.091
## inf_sh_bh_m_w -0.144 0.090std_beta(fit)2.2.1.3 Model 3
Includes control variables.
fit <- lmer(inf_sha_beh_m ~ 1 + pri_con_m_b + pri_con_m_w + male + age + edu_num + (1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: inf_sha_beh_m ~ 1 + pri_con_m_b + pri_con_m_w + male + age + edu_num + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 16456
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.762 -0.519 -0.067 0.471 4.271
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.1167 0.342
## wave (Intercept) 0.0786 0.280
## Residual 0.4307 0.656
## Number of obs: 7506, groups: id, 2521; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 2.633209 0.140093 18.80
## pri_con_m_b -0.053749 0.011472 -4.69
## pri_con_m_w -0.006160 0.019520 -0.32
## male -0.131022 0.021633 -6.06
## age -0.009026 0.000679 -13.29
## edu_num 0.058070 0.006248 9.29
##
## Correlation of Fixed Effects:
## (Intr) pr_cn_m_b pr_cn_m_w male age
## pri_con_m_b 0.023
## pri_con_m_w 0.006 0.004
## male -0.295 -0.024 0.001
## age -0.280 -0.066 -0.012 0.156
## edu_num -0.228 0.012 -0.001 0.105 -0.077
## optimizer (nloptwrap) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.011047 (tol = 0.002, component 1)std_beta(fit)fit <- lmer(pri_con_m ~ 1 + inf_sha_beh_m_b + inf_sha_beh_m_w + male + age + edu_num + (1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: pri_con_m ~ 1 + inf_sha_beh_m_b + inf_sha_beh_m_w + male + age + edu_num + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 15113
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.705 -0.474 0.057 0.512 4.953
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.53582 0.7320
## wave (Intercept) 0.00448 0.0669
## Residual 0.22597 0.4754
## Number of obs: 7506, groups: id, 2521; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 3.029006 0.096670 31.33
## inf_sha_beh_m_b -0.112531 0.025204 -4.46
## inf_sha_beh_m_w -0.007509 0.009735 -0.77
## male 0.031984 0.032493 0.98
## age 0.013018 0.000996 13.07
## edu_num -0.032105 0.009520 -3.37
##
## Correlation of Fixed Effects:
## (Intr) inf_sh_bh_m_b inf_sh_bh_m_w male age
## inf_sh_bh_m_b 0.011
## inf_sh_bh_m_w -0.094 0.092
## male -0.627 0.066 0.022
## age -0.580 -0.017 0.085 0.139
## edu_num -0.489 -0.132 -0.026 0.090 -0.077std_beta(fit)2.2.2 Three Variables
2.2.2.1 Model 1
Measures how current levels of information sharing are affected by generel levels of privacy concern and current levels of privacy concern, as well as general levels of positive attitude toward information sharing and current levels of positive attitude toward information sharing.
fit <- lmer(inf_sha_beh_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_att_m_b + inf_sha_att_m_w + (1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: inf_sha_beh_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_att_m_b + inf_sha_att_m_w + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 17959
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.771 -0.511 -0.077 0.472 4.344
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.1243 0.353
## wave (Intercept) 0.0743 0.272
## Residual 0.4296 0.655
## Number of obs: 8176, groups: id, 2732; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 2.23710 0.12236 18.28
## pri_con_m_b -0.04412 0.01122 -3.93
## pri_con_m_w 0.00227 0.01877 0.12
## inf_sha_att_m_b 0.14891 0.01130 13.18
## inf_sha_att_m_w 0.12581 0.01964 6.40
##
## Correlation of Fixed Effects:
## (Intr) pr_cn_m_b pr_cn_m_w inf_sh_tt_m_b
## pri_con_m_b 0.002
## pri_con_m_w 0.004 0.003
## inf_sh_tt_m_b -0.004 0.119 0.000
## inf_sh_tt_m_w 0.000 0.004 0.031 0.003std_beta(fit)Measures how current levels of positive attitude toward information sharing are affected by generel levels of privacy concern and current levels of privacy concern, as well as general levels of information sharing and current levels of information sharing.
fit <- lmer(inf_sha_att_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_beh_m_b + inf_sha_beh_m_w + (1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: inf_sha_att_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_beh_m_b + inf_sha_beh_m_w + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 13896
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.147 -0.528 0.024 0.526 5.917
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.22725 0.4767
## wave (Intercept) 0.00198 0.0445
## Residual 0.20112 0.4485
## Number of obs: 8176, groups: id, 2732; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 2.2988 0.0232 98.90
## pri_con_m_b -0.1643 0.0115 -14.33
## pri_con_m_w -0.0300 0.0129 -2.34
## inf_sha_beh_m_b 0.2216 0.0166 13.36
## inf_sha_beh_m_w 0.1021 0.0085 12.02
##
## Correlation of Fixed Effects:
## (Intr) pr_cn_m_b pr_cn_m_w inf_sh_bh_m_b
## pri_con_m_b -0.005
## pri_con_m_w 0.015 0.000
## inf_sh_bh_m_b -0.115 0.100 -0.014
## inf_sh_bh_m_w -0.162 0.012 0.010 0.113std_beta(fit)Measures how current levels of privacy concern are affected by generel levels of positive attitude toward information sharing and current levels of positive attitude toward information sharing, as well as general levels of information sharing and current levels of information sharing.
fit <- lmer(pri_con_m ~ 1 + inf_sha_beh_m_b + inf_sha_beh_m_w + inf_sha_att_m_b + inf_sha_att_m_w + (1 | id) + (1 | wave),
d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: pri_con_m ~ 1 + inf_sha_beh_m_b + inf_sha_beh_m_w + inf_sha_att_m_b +
## inf_sha_att_m_w + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 16518
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.793 -0.479 0.058 0.517 5.013
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.57210 0.756
## wave (Intercept) 0.00372 0.061
## Residual 0.22358 0.473
## Number of obs: 8176, groups: id, 2732; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 3.60512 0.03212 112.23
## inf_sha_beh_m_b -0.05512 0.02658 -2.07
## inf_sha_beh_m_w -0.00915 0.00932 -0.98
## inf_sha_att_m_b -0.09501 0.01811 -5.25
## inf_sha_att_m_w -0.03141 0.01429 -2.20
##
## Correlation of Fixed Effects:
## (Intr) inf_sh_bh_m_b inf_sh_bh_m_w inf_sh_tt_m_b
## inf_sh_bh_m_b -0.090
## inf_sh_bh_m_w -0.142 0.110
## inf_sh_tt_m_b 0.020 -0.398 -0.068
## inf_sh_tt_m_w 0.010 -0.006 -0.084 0.005std_beta(fit)2.2.2.2 Model 2
Includes control variables
fit <- lmer(pri_con_m ~ 1 + inf_sha_att_m_b + inf_sha_att_m_w + inf_sha_beh_m_b + inf_sha_beh_m_w + male + age + edu_num +
(1 | id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: pri_con_m ~ 1 + inf_sha_att_m_b + inf_sha_att_m_w + inf_sha_beh_m_b +
## inf_sha_beh_m_w + male + age + edu_num + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 15063
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.771 -0.477 0.059 0.517 4.961
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.52997 0.7280
## wave (Intercept) 0.00471 0.0686
## Residual 0.22548 0.4749
## Number of obs: 7492, groups: id, 2518; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 3.045423 0.096674 31.50
## inf_sha_att_m_b -0.080142 0.018526 -4.33
## inf_sha_att_m_w -0.032246 0.014985 -2.15
## inf_sha_beh_m_b -0.064872 0.027276 -2.38
## inf_sha_beh_m_w -0.001667 0.009786 -0.17
## male 0.024006 0.032450 0.74
## age 0.012723 0.000996 12.77
## edu_num -0.030699 0.009489 -3.24
##
## Correlation of Fixed Effects:
## (Intr) inf_sh_tt_m_b inf_sh_tt_m_w inf_sh_bh_m_b inf_sh_bh_m_w male age
## inf_sh_tt_m_b -0.055
## inf_sh_tt_m_w 0.007 0.005
## inf_sh_bh_m_b 0.032 -0.392 -0.006
## inf_sh_bh_m_w -0.091 -0.059 -0.083 0.109
## male -0.626 0.075 -0.003 0.031 0.018
## age -0.580 0.087 -0.003 -0.050 0.080 0.146
## edu_num -0.483 -0.046 0.001 -0.103 -0.023 0.085 -0.081std_beta(fit)fit <- lmer(inf_sha_att_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_beh_m_b + inf_sha_beh_m_w + male + age + edu_num + (1 |
id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: inf_sha_att_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_beh_m_b +
## inf_sha_beh_m_w + male + age + edu_num + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 12590
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.144 -0.525 0.026 0.531 5.073
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.20364 0.4513
## wave (Intercept) 0.00202 0.0449
## Residual 0.20165 0.4491
## Number of obs: 7492, groups: id, 2518; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 2.731029 0.065973 41.40
## pri_con_m_b -0.162739 0.011542 -14.10
## pri_con_m_w -0.029148 0.013387 -2.18
## inf_sha_beh_m_b 0.205034 0.016916 12.12
## inf_sha_beh_m_w 0.096022 0.008887 10.81
## male -0.228948 0.021972 -10.42
## age -0.004718 0.000682 -6.92
## edu_num 0.032546 0.006417 5.07
##
## Correlation of Fixed Effects:
## (Intr) pr_cn_m_b pr_cn_m_w inf_sh_bh_m_b inf_sh_bh_m_w male age
## pri_con_m_b 0.051
## pri_con_m_w 0.009 0.001
## inf_sh_bh_m_b -0.004 0.105 -0.015
## inf_sh_bh_m_w -0.117 0.002 0.014 0.115
## male -0.627 -0.022 0.000 0.065 0.028
## age -0.591 -0.074 -0.007 -0.011 0.107 0.147
## edu_num -0.482 -0.002 0.002 -0.131 -0.031 0.091 -0.078std_beta(fit)fit <- lmer(inf_sha_beh_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_att_m_b + inf_sha_att_m_w + male + age + edu_num + (1 |
id) + (1 | wave), d_long)
summary(fit)## Linear mixed model fit by REML ['lmerMod']
## Formula: inf_sha_beh_m ~ 1 + pri_con_m_b + pri_con_m_w + inf_sha_att_m_b +
## inf_sha_att_m_w + male + age + edu_num + (1 | id) + (1 | wave)
## Data: d_long
##
## REML criterion at convergence: 16276
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.947 -0.509 -0.071 0.461 4.383
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 0.1049 0.324
## wave (Intercept) 0.0782 0.280
## Residual 0.4271 0.654
## Number of obs: 7492, groups: id, 2518; wave, 5
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 2.597421 0.139168 18.66
## pri_con_m_b -0.036462 0.011298 -3.23
## pri_con_m_w -0.001456 0.019478 -0.07
## inf_sha_att_m_b 0.125435 0.011555 10.86
## inf_sha_att_m_w 0.124057 0.020446 6.07
## male -0.107823 0.021206 -5.08
## age -0.008455 0.000665 -12.72
## edu_num 0.051049 0.006121 8.34
##
## Correlation of Fixed Effects:
## (Intr) pr_cn_m_b pr_cn_m_w inf_sh_tt_m_b inf_sh_tt_m_w male age
## pri_con_m_b 0.019
## pri_con_m_w 0.006 0.004
## inf_sh_tt_m_b -0.024 0.127 -0.001
## inf_sh_tt_m_w 0.000 0.004 0.031 0.003
## male -0.290 -0.010 0.001 0.104 -0.002
## age -0.277 -0.056 -0.012 0.075 0.004 0.164
## edu_num -0.220 -0.001 0.000 -0.101 -0.002 0.093 -0.084std_beta(fit)