Kaiser-Meyer-Olkin factor adequacy
Call: KMO(r = efa_data_good)
Overall MSA = 0.86
MSA for each item =
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2 TR3
0.92 0.81 0.84 0.88 0.90 0.91 0.91 0.85 0.82 0.90 0.82 0.86 0.89 0.78 0.83 Reporting SEM
Factor analyses
KMO
Correlation analysis
Bartlett test
R was not square, finding R from data$chisq
[1] 2696.202
$p.value
[1] 0
$df
[1] 105Correlation matrix
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1
IM1 1.0000000 0.71298839 0.62765341 0.5717989 0.6363378 0.5980382 0.4566975
IM2 0.7129884 1.00000000 0.76424232 0.3777349 0.4951644 0.4713969 0.3993353
IM3 0.6276534 0.76424232 1.00000000 0.3489456 0.4380046 0.4574709 0.4569422
EEF1 0.5717989 0.37773493 0.34894565 1.0000000 0.8524110 0.8290473 0.5084349
EEF2 0.6363378 0.49516444 0.43800459 0.8524110 1.0000000 0.8350601 0.5244719
EEF3 0.5980382 0.47139690 0.45747088 0.8290473 0.8350601 1.0000000 0.5100588
EEC1 0.4566975 0.39933528 0.45694225 0.5084349 0.5244719 0.5100588 1.0000000
EEC2 0.4991122 0.35714188 0.34545905 0.4999021 0.5537591 0.5226353 0.6016595
EEC3 0.4826965 0.31289345 0.33736676 0.5221128 0.5522218 0.5489497 0.7036203
ADT1 0.3786266 0.18286161 0.16547405 0.3980532 0.3945815 0.3520894 0.3230036
ADT2 0.2661312 0.09537928 0.07991806 0.2967496 0.2752524 0.2679828 0.2573973
ADT3 0.3792103 0.23339570 0.20075400 0.3814193 0.3623130 0.3312309 0.3153480
TR1 0.3017875 0.21919623 0.20833661 0.3018744 0.2912169 0.3026644 0.2978594
TR2 0.2670009 0.14827413 0.12213207 0.2348404 0.2317489 0.2647629 0.1774270
TR3 0.2590492 0.15320556 0.15241974 0.2947885 0.2792868 0.3180440 0.2402173
EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2
IM1 0.4991122 0.4826965 0.3786266 0.26613121 0.3792103 0.3017875 0.2670009
IM2 0.3571419 0.3128935 0.1828616 0.09537928 0.2333957 0.2191962 0.1482741
IM3 0.3454590 0.3373668 0.1654741 0.07991806 0.2007540 0.2083366 0.1221321
EEF1 0.4999021 0.5221128 0.3980532 0.29674963 0.3814193 0.3018744 0.2348404
EEF2 0.5537591 0.5522218 0.3945815 0.27525237 0.3623130 0.2912169 0.2317489
EEF3 0.5226353 0.5489497 0.3520894 0.26798284 0.3312309 0.3026644 0.2647629
EEC1 0.6016595 0.7036203 0.3230036 0.25739732 0.3153480 0.2978594 0.1774270
EEC2 1.0000000 0.8314447 0.3392768 0.26434963 0.3418399 0.2952047 0.1970603
EEC3 0.8314447 1.0000000 0.3817681 0.29589254 0.3378812 0.3420730 0.2573827
ADT1 0.3392768 0.3817681 1.0000000 0.79465892 0.7623566 0.4621698 0.4345880
ADT2 0.2643496 0.2958925 0.7946589 1.00000000 0.7981518 0.4348798 0.4134919
ADT3 0.3418399 0.3378812 0.7623566 0.79815177 1.0000000 0.4450446 0.3956410
TR1 0.2952047 0.3420730 0.4621698 0.43487979 0.4450446 1.0000000 0.8346070
TR2 0.1970603 0.2573827 0.4345880 0.41349191 0.3956410 0.8346070 1.0000000
TR3 0.2130674 0.2867810 0.4463040 0.41574612 0.4584716 0.8077895 0.8692773
TR3
IM1 0.2590492
IM2 0.1532056
IM3 0.1524197
EEF1 0.2947885
EEF2 0.2792868
EEF3 0.3180440
EEC1 0.2402173
EEC2 0.2130674
EEC3 0.2867810
ADT1 0.4463040
ADT2 0.4157461
ADT3 0.4584716
TR1 0.8077895
TR2 0.8692773
TR3 1.0000000
Outliers
Loading required namespace: GPArotationThreshold = 0.35
Loadings:
MR1 MR2 MR3 MR5 MR4
IM1 NA NA NA NA 0.576
IM2 NA NA NA NA 0.951
IM3 NA NA NA NA 0.819
EEF1 0.974 NA NA NA NA
EEF2 0.871 NA NA NA NA
EEF3 0.839 NA NA NA NA
EEC1 NA NA NA 0.569 NA
EEC2 NA NA NA 0.769 NA
EEC3 NA NA NA 1.032 NA
ADT1 NA NA 0.821 NA NA
ADT2 NA NA 0.955 NA NA
ADT3 NA NA 0.856 NA NA
TR1 NA 0.839 NA NA NA
TR2 NA 0.978 NA NA NA
TR3 NA 0.904 NA NA NA
MR1 MR2 MR3 MR5 MR4
SS loadings NA NA NA NA NA
Proportion Var NA NA NA NA NA
Cumulative Var NA NA NA NA NA
Factor Correlation Matrix: 1 2 3 4 5
1 1.000 0.309 0.400 0.607 0.529
2 0.309 1.000 0.511 0.299 0.197
3 0.400 0.511 1.000 0.379 0.205
4 0.607 0.299 0.379 1.000 0.418
5 0.529 0.197 0.205 0.418 1.000
1 2 3 4 5
1 1.000 0.310 0.400 0.610 0.529
2 0.310 1.000 0.512 0.301 0.197
3 0.400 0.512 1.000 0.380 0.206
4 0.610 0.301 0.380 1.000 0.419
5 0.529 0.197 0.206 0.419 1.000CFA
Without moderators
lavaan 0.6-21 ended normally after 32 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 21
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 97.263 91.856
Degrees of freedom 24 24
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.059
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1576.162 897.100
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.757
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.952 0.921
Tucker-Lewis Index (TLI) 0.929 0.882
Robust Comparative Fit Index (CFI) 0.953
Robust Tucker-Lewis Index (TLI) 0.929
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2356.016 -2356.016
Scaling correction factor 2.458
for the MLR correction
Loglikelihood unrestricted model (H1) -2307.385 -2307.385
Scaling correction factor 1.712
for the MLR correction
Akaike (AIC) 4754.032 4754.032
Bayesian (BIC) 4824.521 4824.521
Sample-size adjusted Bayesian (SABIC) 4757.979 4757.979
Root Mean Square Error of Approximation:
RMSEA 0.120 0.115
90 Percent confidence interval - lower 0.096 0.092
90 Percent confidence interval - upper 0.145 0.140
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.996 0.992
Robust RMSEA 0.119
90 Percent confidence interval - lower 0.094
90 Percent confidence interval - upper 0.145
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.994
Standardized Root Mean Square Residual:
SRMR 0.069 0.069
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.282 0.109 11.724 0.000 1.068 1.496
EEC3 1.331 0.094 14.135 0.000 1.146 1.515
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.046 0.052 20.013 0.000 0.944 1.149
EEF3 0.962 0.055 17.652 0.000 0.855 1.069
IM =~
IM1 1.000 1.000 1.000
IM2 1.005 0.161 6.240 0.000 0.690 1.321
IM3 1.001 0.180 5.570 0.000 0.649 1.353
Std.lv Std.all
0.971 0.738
1.245 0.872
1.292 0.947
1.082 0.909
1.132 0.934
1.041 0.904
0.953 0.817
0.958 0.887
0.954 0.820
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC ~~
EEF 0.678 0.122 5.569 0.000 0.439 0.917
IM 0.457 0.137 3.331 0.001 0.188 0.726
EEF ~~
IM 0.641 0.160 4.009 0.000 0.327 0.954
Std.lv Std.all
0.645 0.645
0.494 0.494
0.621 0.621
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.787 0.094 8.404 0.000 0.604 0.971
.EEC2 0.486 0.104 4.665 0.000 0.282 0.690
.EEC3 0.193 0.062 3.099 0.002 0.071 0.315
.EEF1 0.247 0.046 5.364 0.000 0.157 0.337
.EEF2 0.189 0.046 4.072 0.000 0.098 0.280
.EEF3 0.241 0.064 3.755 0.000 0.115 0.367
.IM1 0.452 0.166 2.717 0.007 0.126 0.778
.IM2 0.249 0.073 3.408 0.001 0.106 0.393
.IM3 0.442 0.218 2.032 0.042 0.016 0.869
EEC 0.943 0.149 6.307 0.000 0.650 1.236
EEF 1.171 0.186 6.307 0.000 0.807 1.535
IM 0.908 0.211 4.299 0.000 0.494 1.323
Std.lv Std.all
0.787 0.455
0.486 0.239
0.193 0.104
0.247 0.174
0.189 0.128
0.241 0.182
0.452 0.332
0.249 0.214
0.442 0.327
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.545
EEC2 0.761
EEC3 0.896
EEF1 0.826
EEF2 0.872
EEF3 0.818
IM1 0.668
IM2 0.786
IM3 0.673Cronbach’s Alpha: EEC EEF IM
0.882 0.940 0.874 Omega: EEC EEF IM
0.901 0.940 0.883 Average Variance Extracted (AVE): EEC EEF IM
0.739 0.839 0.705 Details
Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
28 EEC =~ IM1 21.674 0.326 0.317 0.271 0.271
29 EEC =~ IM2 13.178 -0.230 -0.224 -0.207 -0.207
34 EEF =~ IM1 37.173 0.445 0.481 0.412 0.412
35 EEF =~ IM2 13.077 -0.245 -0.265 -0.246 -0.246
37 IM =~ EEC1 12.874 0.306 0.292 0.222 0.222
39 IM =~ EEC3 12.216 -0.262 -0.249 -0.183 -0.183
40 IM =~ EEF1 11.737 -0.214 -0.204 -0.172 -0.172
43 EEC1 ~~ EEC2 10.825 -0.246 -0.246 -0.397 -0.397
51 EEC2 ~~ EEC3 10.266 0.430 0.430 1.405 1.405
77 IM1 ~~ IM3 16.808 -0.274 -0.274 -0.612 -0.612
78 IM2 ~~ IM3 41.023 0.463 0.463 1.394 1.394Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
43 EEC1 ~~ EEC2 10.825 -0.246 -0.246 -0.397 -0.397
51 EEC2 ~~ EEC3 10.266 0.430 0.430 1.405 1.405
77 IM1 ~~ IM3 16.808 -0.274 -0.274 -0.612 -0.612
78 IM2 ~~ IM3 41.023 0.463 0.463 1.394 1.394$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.080 0.000
EEC3 0.009 0.011 0.000
EEF1 0.118 -0.020 -0.054 0.000
EEF2 0.127 0.048 -0.030 0.006 0.000
EEF3 0.120 0.022 -0.006 0.010 -0.013 0.000
IM1 0.244 0.245 0.160 0.154 0.230 0.187 0.000
IM2 0.108 -0.038 -0.150 -0.158 -0.025 -0.033 -0.015 0.000
IM3 0.241 -0.013 -0.073 -0.158 -0.053 -0.005 -0.058 0.046 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -1.089 0.000
EEC3 0.121 0.079 0.000
EEF1 1.017 -0.141 -0.371 0.000
EEF2 1.232 0.341 -0.211 0.039 0.000
EEF3 1.188 0.175 -0.047 0.077 -0.110 0.000
IM1 2.495 2.329 1.604 1.399 2.057 1.746 0.000
IM2 1.729 -0.571 -2.391 -1.924 -0.454 -0.578 -0.440 0.000
IM3 2.428 -0.173 -1.005 -1.778 -0.771 -0.078 -1.686 0.966 0.000Modified measurement model (without moderators)
lavaan 0.6-21 ended normally after 35 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 22
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 57.245 50.238
Degrees of freedom 23 23
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.139
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1576.162 897.100
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.757
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.968
Tucker-Lewis Index (TLI) 0.965 0.950
Robust Comparative Fit Index (CFI) 0.979
Robust Tucker-Lewis Index (TLI) 0.968
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2336.007 -2336.007
Scaling correction factor 2.310
for the MLR correction
Loglikelihood unrestricted model (H1) -2307.385 -2307.385
Scaling correction factor 1.712
for the MLR correction
Akaike (AIC) 4716.014 4716.014
Bayesian (BIC) 4789.859 4789.859
Sample-size adjusted Bayesian (SABIC) 4720.148 4720.148
Root Mean Square Error of Approximation:
RMSEA 0.084 0.075
90 Percent confidence interval - lower 0.057 0.048
90 Percent confidence interval - upper 0.111 0.101
P-value H_0: RMSEA <= 0.050 0.022 0.061
P-value H_0: RMSEA >= 0.080 0.617 0.396
Robust RMSEA 0.080
90 Percent confidence interval - lower 0.050
90 Percent confidence interval - upper 0.110
P-value H_0: Robust RMSEA <= 0.050 0.052
P-value H_0: Robust RMSEA >= 0.080 0.524
Standardized Root Mean Square Residual:
SRMR 0.047 0.047
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.285 0.110 11.663 0.000 1.069 1.501
EEC3 1.334 0.094 14.256 0.000 1.151 1.518
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.044 0.054 19.351 0.000 0.938 1.150
EEF3 0.957 0.055 17.307 0.000 0.849 1.066
IM =~
IM1 1.000 1.000 1.000
IM2 0.692 0.098 7.048 0.000 0.499 0.884
IM3 0.658 0.107 6.123 0.000 0.447 0.868
Std.lv Std.all
0.969 0.737
1.245 0.873
1.293 0.947
1.085 0.911
1.132 0.934
1.039 0.902
1.139 0.977
0.788 0.729
0.749 0.644
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.370 0.154 2.410 0.016 0.069 0.671
EEC ~~
EEF 0.677 0.121 5.579 0.000 0.439 0.915
IM 0.603 0.112 5.386 0.000 0.384 0.823
EEF ~~
IM 0.836 0.131 6.393 0.000 0.579 1.092
Std.lv Std.all
0.370 0.563
0.645 0.645
0.546 0.546
0.676 0.676
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.791 0.094 8.378 0.000 0.606 0.976
.EEC2 0.485 0.105 4.615 0.000 0.279 0.691
.EEC3 0.191 0.062 3.052 0.002 0.068 0.313
.EEF1 0.241 0.045 5.361 0.000 0.153 0.330
.EEF2 0.188 0.046 4.134 0.000 0.099 0.278
.EEF3 0.246 0.064 3.866 0.000 0.121 0.371
.IM1 0.063 0.091 0.689 0.491 -0.116 0.241
.IM2 0.546 0.164 3.325 0.001 0.224 0.868
.IM3 0.791 0.226 3.502 0.000 0.349 1.234
EEC 0.939 0.149 6.310 0.000 0.647 1.230
EEF 1.176 0.188 6.268 0.000 0.809 1.544
IM 1.298 0.195 6.642 0.000 0.915 1.681
Std.lv Std.all
0.791 0.457
0.485 0.238
0.191 0.102
0.241 0.170
0.188 0.128
0.246 0.186
0.063 0.046
0.546 0.468
0.791 0.585
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.543
EEC2 0.762
EEC3 0.898
EEF1 0.830
EEF2 0.872
EEF3 0.814
IM1 0.954
IM2 0.532
IM3 0.415Cronbach’s Alpha: EEC EEF IM
0.882 0.940 0.874 Omega: EEC EEF IM
0.901 0.940 0.770 Average Variance Extracted (AVE): EEC EEF IM
0.739 0.839 0.639 Details
Only larger ones[1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
<0 rows> (or 0-length row.names)Residuals[1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
<0 rows> (or 0-length row.names)$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.077 0.000
EEC3 0.010 0.009 0.000
EEF1 0.119 -0.021 -0.056 0.000
EEF2 0.129 0.049 -0.030 0.003 0.000
EEF3 0.124 0.025 -0.003 0.010 -0.010 0.000
IM1 0.098 0.056 -0.036 -0.041 0.028 0.003 0.000
IM2 0.150 0.014 -0.095 -0.092 0.045 0.033 0.001 0.000
IM3 0.302 0.064 0.006 -0.066 0.044 0.086 -0.002 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -2.108 0.000
EEC3 0.285 0.434 0.000
EEF1 1.724 -0.450 -1.594 0.000
EEF2 2.005 1.112 -0.902 0.110 0.000
EEF3 1.824 0.542 -0.082 0.398 -0.495 0.000
IM1 1.470 1.374 -1.867 -1.289 0.893 0.093 0.000
IM2 2.401 0.291 -2.108 -2.353 1.156 0.855 0.021 0.000
IM3 2.810 0.852 0.086 -1.299 0.802 2.029 -0.066 0.000 0.000With moderators
lavaan 0.6-21 ended normally after 48 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 40
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 176.186 160.521
Degrees of freedom 80 80
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.098
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2786.003 1953.933
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.426
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.964 0.956
Tucker-Lewis Index (TLI) 0.953 0.943
Robust Comparative Fit Index (CFI) 0.966
Robust Tucker-Lewis Index (TLI) 0.956
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3914.271 -3914.271
Scaling correction factor 2.031
for the MLR correction
Loglikelihood unrestricted model (H1) -3826.178 -3826.178
Scaling correction factor 1.409
for the MLR correction
Akaike (AIC) 7908.542 7908.542
Bayesian (BIC) 8042.806 8042.806
Sample-size adjusted Bayesian (SABIC) 7916.059 7916.059
Root Mean Square Error of Approximation:
RMSEA 0.075 0.069
90 Percent confidence interval - lower 0.060 0.054
90 Percent confidence interval - upper 0.090 0.084
P-value H_0: RMSEA <= 0.050 0.004 0.020
P-value H_0: RMSEA >= 0.080 0.316 0.110
Robust RMSEA 0.072
90 Percent confidence interval - lower 0.056
90 Percent confidence interval - upper 0.088
P-value H_0: Robust RMSEA <= 0.050 0.014
P-value H_0: Robust RMSEA >= 0.080 0.222
Standardized Root Mean Square Residual:
SRMR 0.061 0.061
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
IM =~
IM1 1.000 1.000 1.000
IM2 1.004 0.166 6.056 0.000 0.679 1.329
IM3 1.000 0.185 5.407 0.000 0.637 1.363
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.044 0.053 19.717 0.000 0.941 1.148
EEF3 0.961 0.056 17.286 0.000 0.852 1.069
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.280 0.109 11.765 0.000 1.067 1.493
EEC3 1.333 0.095 14.075 0.000 1.147 1.518
TR =~
TR1 1.000 1.000 1.000
TR2 1.086 0.048 22.568 0.000 0.991 1.180
TR3 1.048 0.050 20.819 0.000 0.949 1.147
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.031 0.068 15.192 0.000 0.898 1.164
ADT3 1.140 0.076 15.022 0.000 0.992 1.289
Std.lv Std.all
0.954 0.818
0.958 0.886
0.954 0.820
1.083 0.910
1.131 0.933
1.041 0.904
0.971 0.738
1.243 0.871
1.294 0.948
1.318 0.886
1.431 0.940
1.381 0.921
0.923 0.881
0.951 0.899
1.052 0.879
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
IM ~~
EEF 0.642 0.164 3.919 0.000 0.321 0.963
EEC 0.457 0.140 3.273 0.001 0.183 0.730
TR 0.306 0.137 2.231 0.026 0.037 0.575
ADT 0.241 0.116 2.073 0.038 0.013 0.468
EEF ~~
EEC 0.678 0.122 5.554 0.000 0.439 0.917
TR 0.459 0.114 4.026 0.000 0.236 0.683
ADT 0.414 0.103 4.033 0.000 0.213 0.615
EEC ~~
TR 0.405 0.104 3.909 0.000 0.202 0.608
ADT 0.363 0.086 4.223 0.000 0.194 0.531
TR ~~
ADT 0.639 0.107 5.973 0.000 0.429 0.849
Std.lv Std.all
0.621 0.621
0.493 0.493
0.244 0.244
0.273 0.273
0.645 0.645
0.322 0.322
0.414 0.414
0.316 0.316
0.405 0.405
0.526 0.526
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.451 0.173 2.613 0.009 0.113 0.789
.IM2 0.250 0.075 3.331 0.001 0.103 0.397
.IM3 0.443 0.219 2.018 0.044 0.013 0.873
.EEF1 0.244 0.046 5.351 0.000 0.155 0.333
.EEF2 0.191 0.047 4.038 0.000 0.098 0.283
.EEF3 0.242 0.064 3.776 0.000 0.116 0.367
.EEC1 0.787 0.094 8.414 0.000 0.604 0.971
.EEC2 0.491 0.104 4.727 0.000 0.287 0.694
.EEC3 0.188 0.062 3.017 0.003 0.066 0.310
.TR1 0.476 0.084 5.699 0.000 0.312 0.640
.TR2 0.267 0.068 3.942 0.000 0.134 0.400
.TR3 0.342 0.088 3.886 0.000 0.169 0.514
.ADT1 0.245 0.057 4.258 0.000 0.132 0.357
.ADT2 0.215 0.054 4.001 0.000 0.110 0.320
.ADT3 0.326 0.089 3.658 0.000 0.151 0.500
IM 0.910 0.218 4.175 0.000 0.483 1.337
EEF 1.174 0.186 6.295 0.000 0.808 1.539
EEC 0.943 0.149 6.313 0.000 0.650 1.235
TR 1.737 0.173 10.042 0.000 1.398 2.076
ADT 0.851 0.125 6.810 0.000 0.606 1.096
Std.lv Std.all
0.451 0.331
0.250 0.214
0.443 0.327
0.244 0.172
0.191 0.130
0.242 0.183
0.787 0.455
0.491 0.241
0.188 0.101
0.476 0.215
0.267 0.115
0.342 0.152
0.245 0.223
0.215 0.192
0.326 0.227
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.669
IM2 0.786
IM3 0.673
EEF1 0.828
EEF2 0.870
EEF3 0.817
EEC1 0.545
EEC2 0.759
EEC3 0.899
TR1 0.785
TR2 0.885
TR3 0.848
ADT1 0.777
ADT2 0.808
ADT3 0.773Cronbach’s Alpha: IM EEF EEC TR ADT
0.874 0.940 0.882 0.939 0.914 Omega: IM EEF EEC TR ADT
0.883 0.940 0.901 0.941 0.917 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.705 0.839 0.739 0.840 0.785 $type
[1] "cor.bentler"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.012 0.000
IM3 -0.043 0.037 0.000
EEF1 0.110 -0.123 -0.115 0.000
EEF2 0.163 -0.019 -0.037 0.004 0.000
EEF3 0.139 -0.026 -0.003 0.006 -0.008 0.000
EEC1 0.159 0.077 0.158 0.076 0.081 0.080 0.000
EEC2 0.148 -0.024 -0.007 -0.011 0.030 0.015 -0.041 0.000
EEC3 0.100 -0.102 -0.046 -0.034 -0.018 -0.004 0.004 0.005 0.000
TR1 0.125 0.028 0.031 0.043 0.025 0.045 0.091 0.051 0.076 0.000
TR2 0.080 -0.055 -0.066 -0.040 -0.050 -0.009 -0.042 -0.062 -0.025 0.001
TR3 0.076 -0.046 -0.032 0.025 0.003 0.050 0.025 -0.041 0.011 -0.008
ADT1 0.182 -0.031 -0.032 0.066 0.054 0.022 0.059 0.028 0.043 0.052
ADT2 0.065 -0.123 -0.122 -0.042 -0.072 -0.069 -0.011 -0.053 -0.049 0.016
ADT3 0.183 0.020 0.004 0.050 0.023 0.002 0.052 0.032 0.000 0.036
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.003 0.000
ADT1 -0.001 0.020 0.000
ADT2 -0.031 -0.019 0.002 0.000
ADT3 -0.039 0.033 -0.012 0.008 0.000
$cov.z
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.236 0.000
IM3 -0.931 0.619 0.000
EEF1 1.278 -1.580 -1.428 0.000
EEF2 1.922 -0.306 -0.568 0.030 0.000
EEF3 1.633 -0.448 -0.052 0.060 -0.088 0.000
EEC1 2.496 1.601 2.336 0.920 1.119 1.101 0.000
EEC2 2.252 -0.414 -0.115 -0.114 0.319 0.172 -0.764 0.000
EEC3 1.531 -1.845 -0.779 -0.330 -0.182 -0.039 0.070 0.066 0.000
TR1 1.727 0.607 0.588 0.656 0.372 0.654 1.383 0.836 1.245 0.000
TR2 1.260 -1.215 -1.375 -0.531 -0.662 -0.114 -0.631 -0.933 -0.385 0.033
TR3 1.090 -0.927 -0.601 0.367 0.040 0.698 0.387 -0.639 0.174 -0.225
ADT1 2.112 -0.628 -0.584 0.772 0.589 0.231 0.893 0.360 0.555 0.805
ADT2 0.775 -2.617 -2.225 -0.460 -0.786 -0.697 -0.172 -0.678 -0.628 0.267
ADT3 2.215 0.440 0.068 0.574 0.246 0.024 0.803 0.413 0.003 0.565
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.064 0.000
ADT1 -0.015 0.298 0.000
ADT2 -0.474 -0.306 0.026 0.000
ADT3 -0.563 0.520 -0.139 0.095 0.000
$summary
cov
srmr 0.061
srmr.se 0.035
srmr.exactfit.z 0.000
srmr.exactfit.pvalue 0.500
usrmr 0.000
usrmr.se 0.061
usrmr.ci.lower -0.101
usrmr.ci.upper 0.101
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -0.816
usrmr.closefit.pvalue 0.793 IM EEF EEC TR ADT
IM 1.000
EEF 0.621 1.000
EEC 0.493 0.645 1.000
TR 0.244 0.322 0.316 1.000
ADT 0.273 0.414 0.405 0.526 1.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC TR ADT
IM "1" "0.62 (0)" "0.49 (0)" "0.24 (0.005)" "0.27 (0.009)"
EEF "0.62 (0)" "1" "0.64 (0)" "0.32 (0)" "0.41 (0)"
EEC "0.49 (0)" "0.64 (0)" "1" "0.32 (0)" "0.41 (0)"
TR "0.24 (0.005)" "0.32 (0)" "0.32 (0)" "1" "0.53 (0)"
ADT "0.27 (0.009)" "0.41 (0)" "0.41 (0)" "0.53 (0)" "1" Details
Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
46 IM =~ EEF1 12.053 -0.216 -0.206 -0.173 -0.173
49 IM =~ EEC1 12.950 0.307 0.292 0.222 0.222
51 IM =~ EEC3 12.411 -0.262 -0.250 -0.183 -0.183
56 IM =~ ADT2 13.134 -0.172 -0.164 -0.155 -0.155
58 EEF =~ IM1 37.946 0.448 0.486 0.416 0.416
59 EEF =~ IM2 13.298 -0.247 -0.267 -0.248 -0.248
68 EEF =~ ADT2 10.367 -0.140 -0.152 -0.144 -0.144
70 EEC =~ IM1 22.180 0.329 0.320 0.274 0.274
71 EEC =~ IM2 13.358 -0.231 -0.225 -0.208 -0.208
94 ADT =~ IM1 22.844 0.306 0.282 0.242 0.242
107 IM1 ~~ IM3 17.001 -0.275 -0.275 -0.615 -0.615
120 IM2 ~~ IM3 41.632 0.465 0.465 1.396 1.396Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
107 IM1 ~~ IM3 17.001 -0.275 -0.275 -0.615 -0.615
120 IM2 ~~ IM3 41.632 0.465 0.465 1.396 1.396$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.015 0.000
IM3 -0.058 0.047 0.000
EEF1 0.152 -0.159 -0.159 0.000
EEF2 0.230 -0.024 -0.053 0.005 0.000
EEF3 0.186 -0.033 -0.004 0.009 -0.012 0.000
EEC1 0.244 0.109 0.242 0.118 0.129 0.121 0.000
EEC2 0.246 -0.036 -0.011 -0.019 0.052 0.025 -0.078 0.000
EEC3 0.160 -0.150 -0.073 -0.055 -0.030 -0.006 0.007 0.011 0.000
TR1 0.218 0.045 0.054 0.075 0.046 0.077 0.178 0.108 0.155 0.000
TR2 0.141 -0.090 -0.116 -0.073 -0.093 -0.015 -0.084 -0.135 -0.051 0.003
TR3 0.132 -0.074 -0.055 0.045 0.005 0.087 0.050 -0.087 0.022 -0.018
ADT1 0.222 -0.035 -0.039 0.082 0.069 0.027 0.082 0.042 0.062 0.081
ADT2 0.080 -0.140 -0.150 -0.053 -0.092 -0.083 -0.016 -0.080 -0.071 0.026
ADT3 0.255 0.026 0.005 0.072 0.033 0.003 0.083 0.054 0.000 0.064
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.007 0.000
ADT1 -0.002 0.031 0.000
ADT2 -0.050 -0.031 0.003 0.000
ADT3 -0.071 0.059 -0.015 0.010 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.236 0.000
IM3 -0.931 0.619 0.000
EEF1 1.278 -1.580 -1.428 0.000
EEF2 1.922 -0.306 -0.568 0.030 0.000
EEF3 1.633 -0.448 -0.052 0.060 -0.088 0.000
EEC1 2.496 1.601 2.336 0.920 1.119 1.101 0.000
EEC2 2.252 -0.414 -0.115 -0.114 0.319 0.172 -0.764 0.000
EEC3 1.531 -1.845 -0.779 -0.330 -0.182 -0.039 0.070 0.066 0.000
TR1 1.727 0.607 0.588 0.656 0.372 0.654 1.383 0.836 1.245 0.000
TR2 1.260 -1.215 -1.375 -0.531 -0.662 -0.114 -0.631 -0.933 -0.385 0.033
TR3 1.090 -0.927 -0.601 0.367 0.040 0.698 0.387 -0.639 0.174 -0.225
ADT1 2.112 -0.628 -0.584 0.772 0.589 0.231 0.893 0.360 0.555 0.805
ADT2 0.775 -2.617 -2.225 -0.460 -0.786 -0.697 -0.172 -0.678 -0.628 0.267
ADT3 2.215 0.440 0.068 0.574 0.246 0.024 0.803 0.413 0.003 0.565
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.064 0.000
ADT1 -0.015 0.298 0.000
ADT2 -0.474 -0.306 0.026 0.000
ADT3 -0.563 0.520 -0.139 0.095 0.000Modified model with moderation
lavaan 0.6-21 ended normally after 51 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 132.727 117.589
Degrees of freedom 79 79
P-value (Chi-square) 0.000 0.003
Scaling correction factor 1.129
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2786.003 1953.933
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.426
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.980 0.979
Tucker-Lewis Index (TLI) 0.973 0.972
Robust Comparative Fit Index (CFI) 0.983
Robust Tucker-Lewis Index (TLI) 0.978
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3892.542 -3892.542
Scaling correction factor 1.948
for the MLR correction
Loglikelihood unrestricted model (H1) -3826.178 -3826.178
Scaling correction factor 1.409
for the MLR correction
Akaike (AIC) 7867.083 7867.083
Bayesian (BIC) 8004.703 8004.703
Sample-size adjusted Bayesian (SABIC) 7874.788 7874.788
Root Mean Square Error of Approximation:
RMSEA 0.057 0.048
90 Percent confidence interval - lower 0.039 0.030
90 Percent confidence interval - upper 0.073 0.064
P-value H_0: RMSEA <= 0.050 0.247 0.560
P-value H_0: RMSEA >= 0.080 0.009 0.000
Robust RMSEA 0.051
90 Percent confidence interval - lower 0.030
90 Percent confidence interval - upper 0.070
P-value H_0: Robust RMSEA <= 0.050 0.447
P-value H_0: Robust RMSEA >= 0.080 0.004
Standardized Root Mean Square Residual:
SRMR 0.047 0.047
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
IM =~
IM1 1.000 1.000 1.000
IM2 0.672 0.104 6.446 0.000 0.468 0.876
IM3 0.637 0.113 5.659 0.000 0.416 0.858
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.042 0.054 19.124 0.000 0.935 1.148
EEF3 0.956 0.056 16.964 0.000 0.845 1.066
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.283 0.109 11.720 0.000 1.069 1.498
EEC3 1.338 0.094 14.202 0.000 1.153 1.523
TR =~
TR1 1.000 1.000 1.000
TR2 1.086 0.048 22.586 0.000 0.992 1.181
TR3 1.048 0.050 20.873 0.000 0.950 1.147
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.028 0.068 15.079 0.000 0.895 1.162
ADT3 1.142 0.076 15.002 0.000 0.992 1.291
Std.lv Std.all
1.157 0.991
0.777 0.719
0.737 0.634
1.086 0.912
1.131 0.933
1.038 0.902
0.968 0.736
1.243 0.871
1.296 0.949
1.318 0.886
1.431 0.941
1.381 0.921
0.923 0.882
0.949 0.897
1.054 0.880
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.388 0.162 2.399 0.016 0.071 0.705
IM ~~
EEF 0.837 0.130 6.415 0.000 0.581 1.092
EEC 0.602 0.112 5.384 0.000 0.383 0.822
TR 0.452 0.124 3.637 0.000 0.209 0.696
ADT 0.407 0.113 3.603 0.000 0.186 0.628
EEF ~~
EEC 0.677 0.122 5.564 0.000 0.438 0.915
TR 0.460 0.115 4.011 0.000 0.235 0.684
ADT 0.416 0.103 4.020 0.000 0.213 0.619
EEC ~~
TR 0.403 0.103 3.913 0.000 0.201 0.605
ADT 0.362 0.086 4.234 0.000 0.195 0.530
TR ~~
ADT 0.639 0.107 5.973 0.000 0.429 0.849
Std.lv Std.all
0.388 0.574
0.666 0.666
0.538 0.538
0.297 0.297
0.381 0.381
0.643 0.643
0.321 0.321
0.415 0.415
0.316 0.316
0.405 0.405
0.526 0.526
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.023 0.112 0.208 0.836 -0.196 0.242
.IM2 0.564 0.172 3.278 0.001 0.227 0.901
.IM3 0.810 0.229 3.539 0.000 0.361 1.258
.EEF1 0.238 0.045 5.334 0.000 0.151 0.326
.EEF2 0.191 0.046 4.110 0.000 0.100 0.282
.EEF3 0.247 0.064 3.875 0.000 0.122 0.372
.EEC1 0.792 0.094 8.416 0.000 0.608 0.977
.EEC2 0.491 0.105 4.693 0.000 0.286 0.696
.EEC3 0.184 0.062 2.948 0.003 0.062 0.306
.TR1 0.477 0.083 5.719 0.000 0.313 0.640
.TR2 0.266 0.068 3.924 0.000 0.133 0.399
.TR3 0.342 0.088 3.887 0.000 0.170 0.515
.ADT1 0.244 0.057 4.272 0.000 0.132 0.356
.ADT2 0.218 0.054 4.046 0.000 0.112 0.324
.ADT3 0.323 0.089 3.628 0.000 0.148 0.497
IM 1.338 0.210 6.376 0.000 0.926 1.749
EEF 1.180 0.188 6.261 0.000 0.810 1.549
EEC 0.938 0.148 6.315 0.000 0.647 1.229
TR 1.736 0.173 10.047 0.000 1.397 2.075
ADT 0.852 0.125 6.806 0.000 0.607 1.097
Std.lv Std.all
0.023 0.017
0.564 0.483
0.810 0.599
0.238 0.168
0.191 0.130
0.247 0.186
0.792 0.458
0.491 0.241
0.184 0.099
0.477 0.215
0.266 0.115
0.342 0.152
0.244 0.223
0.218 0.195
0.323 0.225
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.983
IM2 0.517
IM3 0.401
EEF1 0.832
EEF2 0.870
EEF3 0.814
EEC1 0.542
EEC2 0.759
EEC3 0.901
TR1 0.785
TR2 0.885
TR3 0.848
ADT1 0.777
ADT2 0.805
ADT3 0.775Cronbach’s Alpha: IM EEF EEC TR ADT
0.874 0.940 0.882 0.939 0.914 Omega: IM EEF EEC TR ADT
0.766 0.940 0.901 0.941 0.917 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.640 0.840 0.739 0.840 0.785 Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
57 IM =~ ADT2 12.251 -0.137 -0.158 -0.150 -0.150
69 EEF =~ ADT2 10.153 -0.139 -0.151 -0.143 -0.143Residuals[1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
<0 rows> (or 0-length row.names)$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.000 0.000
IM3 -0.001 0.000 0.000
EEF1 -0.042 -0.076 -0.050 0.000
EEF2 0.029 0.063 0.063 0.002 0.000
EEF3 0.003 0.049 0.103 0.009 -0.009 0.000
EEC1 0.098 0.163 0.315 0.120 0.132 0.125 0.000
EEC2 0.058 0.031 0.081 -0.019 0.054 0.028 -0.074 0.000
EEC3 -0.038 -0.080 0.022 -0.057 -0.029 -0.003 0.008 0.009 0.000
TR1 0.071 0.048 0.072 0.075 0.046 0.079 0.179 0.109 0.155 0.000
TR2 -0.018 -0.086 -0.097 -0.074 -0.093 -0.014 -0.083 -0.135 -0.052 0.003
TR3 -0.021 -0.070 -0.036 0.045 0.006 0.088 0.051 -0.087 0.021 -0.017
ADT1 0.055 -0.066 -0.058 0.080 0.068 0.026 0.082 0.042 0.061 0.080
ADT2 -0.090 -0.172 -0.168 -0.054 -0.093 -0.083 -0.014 -0.079 -0.071 0.027
ADT3 0.065 -0.010 -0.016 0.069 0.031 0.002 0.083 0.053 -0.001 0.063
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.007 0.000
ADT1 -0.002 0.031 0.000
ADT2 -0.049 -0.029 0.004 0.000
ADT3 -0.072 0.058 -0.017 0.011 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.004 0.000
IM3 -0.011 0.000 0.000
EEF1 -0.799 -1.268 -0.715 0.000
EEF2 0.600 1.081 0.881 0.041 0.000
EEF3 0.062 0.878 1.725 0.180 -0.208 0.000
EEC1 1.360 2.635 2.815 1.502 1.802 1.688 0.000
EEC2 1.003 0.465 0.880 -0.284 0.908 0.447 -0.997 0.000
EEC3 -0.780 -1.266 0.246 -0.983 -0.529 -0.056 0.123 0.128 0.000
TR1 1.207 0.795 0.630 1.039 0.701 1.044 1.729 1.196 1.951 0.000
TR2 -0.386 -0.984 -0.879 -1.200 -1.798 -0.219 -0.800 -1.664 -1.196 0.085
TR3 -0.438 -0.860 -0.301 0.782 0.100 1.358 0.520 -1.019 0.390 -0.426
ADT1 1.121 -1.006 -0.847 1.406 1.319 0.509 1.255 0.657 1.402 1.259
ADT2 -2.253 -2.489 -2.012 -1.079 -2.051 -1.742 -0.220 -1.300 -1.738 0.502
ADT3 1.470 -0.149 -0.175 1.194 0.546 0.043 1.181 0.781 -0.026 0.942
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.143 0.000
ADT1 -0.043 0.522 0.000
ADT2 -1.116 -0.599 0.119 0.000
ADT3 -1.099 1.002 -0.502 0.313 0.000ADT group
lavaan 0.6-21 ended normally after 66 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 109
0 103
Model Test User Model:
Standard Scaled
Test Statistic 243.395 239.955
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.014
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 102.367 102.367
0 137.589 137.589
Model Test Baseline Model:
Test statistic 2411.026 1894.314
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.273
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.961 0.951
Tucker-Lewis Index (TLI) 0.948 0.935
Robust Comparative Fit Index (CFI) 0.961
Robust Tucker-Lewis Index (TLI) 0.948
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3719.941 -3719.941
Scaling correction factor 1.590
for the MLR correction
Loglikelihood unrestricted model (H1) -3598.243 -3598.243
Scaling correction factor 1.253
for the MLR correction
Akaike (AIC) 7663.882 7663.882
Bayesian (BIC) 8039.819 8039.819
Sample-size adjusted Bayesian (SABIC) 7684.929 7684.929
Root Mean Square Error of Approximation:
RMSEA 0.071 0.070
90 Percent confidence interval - lower 0.053 0.051
90 Percent confidence interval - upper 0.089 0.087
P-value H_0: RMSEA <= 0.050 0.029 0.039
P-value H_0: RMSEA >= 0.080 0.215 0.177
Robust RMSEA 0.070
90 Percent confidence interval - lower 0.052
90 Percent confidence interval - upper 0.088
P-value H_0: Robust RMSEA <= 0.050 0.038
P-value H_0: Robust RMSEA >= 0.080 0.193
Standardized Root Mean Square Residual:
SRMR 0.065 0.065
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Group 1 [1]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM =~
IM1 1.000 0.833 0.892
IM2 0.772 0.097 7.926 0.000 0.643 0.689
IM3 0.635 0.146 4.337 0.000 0.529 0.472
EEF =~
EEF1 1.000 0.878 0.903
EEF2 1.055 0.068 15.478 0.000 0.926 0.911
EEF3 0.940 0.071 13.241 0.000 0.825 0.863
EEC =~
EEC1 1.000 0.952 0.735
EEC2 1.154 0.130 8.898 0.000 1.098 0.833
EEC3 1.262 0.121 10.462 0.000 1.201 0.933
TR =~
TR1 1.000 1.279 0.873
TR2 1.078 0.077 14.075 0.000 1.379 0.930
TR3 1.062 0.080 13.259 0.000 1.359 0.899
ADT =~
ADT1 1.000 0.421 0.709
ADT2 1.285 0.270 4.769 0.000 0.541 0.894
ADT3 1.021 0.242 4.217 0.000 0.429 0.659
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.370 0.235 1.575 0.115 0.370 0.552
IM ~~
EEF 0.471 0.088 5.329 0.000 0.644 0.644
EEC 0.359 0.098 3.642 0.000 0.452 0.452
TR 0.269 0.128 2.096 0.036 0.252 0.252
ADT 0.020 0.049 0.411 0.681 0.058 0.058
EEF ~~
EEC 0.519 0.120 4.310 0.000 0.621 0.621
TR 0.364 0.124 2.929 0.003 0.324 0.324
ADT 0.078 0.051 1.525 0.127 0.210 0.210
EEC ~~
TR 0.413 0.120 3.437 0.001 0.339 0.339
ADT 0.090 0.049 1.826 0.068 0.225 0.225
TR ~~
ADT 0.252 0.075 3.359 0.001 0.468 0.468
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.468 0.089 61.104 0.000 5.468 5.853
.IM2 5.835 0.089 65.243 0.000 5.835 6.249
.IM3 5.633 0.108 52.396 0.000 5.633 5.019
.EEF1 5.642 0.093 60.584 0.000 5.642 5.803
.EEF2 5.780 0.097 59.340 0.000 5.780 5.684
.EEF3 5.826 0.092 63.599 0.000 5.826 6.092
.EEC1 4.569 0.124 36.840 0.000 4.569 3.529
.EEC2 4.734 0.126 37.505 0.000 4.734 3.592
.EEC3 4.780 0.123 38.756 0.000 4.780 3.712
.TR1 4.284 0.140 30.517 0.000 4.284 2.923
.TR2 4.239 0.142 29.835 0.000 4.239 2.858
.TR3 3.991 0.145 27.568 0.000 3.991 2.640
.ADT1 6.156 0.057 108.355 0.000 6.156 10.378
.ADT2 6.101 0.058 105.291 0.000 6.101 10.085
.ADT3 6.128 0.062 98.276 0.000 6.128 9.413
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.178 0.086 2.075 0.038 0.178 0.204
.IM2 0.458 0.243 1.887 0.059 0.458 0.525
.IM3 0.980 0.385 2.543 0.011 0.980 0.778
.EEF1 0.175 0.058 3.026 0.002 0.175 0.185
.EEF2 0.176 0.062 2.833 0.005 0.176 0.171
.EEF3 0.234 0.073 3.197 0.001 0.234 0.256
.EEC1 0.771 0.149 5.173 0.000 0.771 0.460
.EEC2 0.531 0.143 3.721 0.000 0.531 0.306
.EEC3 0.216 0.100 2.168 0.030 0.216 0.130
.TR1 0.511 0.131 3.898 0.000 0.511 0.238
.TR2 0.297 0.094 3.168 0.002 0.297 0.135
.TR3 0.438 0.164 2.662 0.008 0.438 0.192
.ADT1 0.175 0.050 3.532 0.000 0.175 0.497
.ADT2 0.074 0.059 1.239 0.215 0.074 0.201
.ADT3 0.240 0.050 4.744 0.000 0.240 0.565
IM 0.695 0.122 5.672 0.000 1.000 1.000
EEF 0.770 0.161 4.781 0.000 1.000 1.000
EEC 0.906 0.180 5.031 0.000 1.000 1.000
TR 1.637 0.253 6.462 0.000 1.000 1.000
ADT 0.177 0.054 3.281 0.001 1.000 1.000
Group 2 [0]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM =~
IM1 1.000 1.305 1.015
IM2 0.683 0.155 4.392 0.000 0.891 0.749
IM3 0.682 0.169 4.039 0.000 0.890 0.755
EEF =~
EEF1 1.000 1.148 0.899
EEF2 1.053 0.078 13.481 0.000 1.208 0.938
EEF3 0.968 0.089 10.930 0.000 1.111 0.909
EEC =~
EEC1 1.000 0.861 0.692
EEC2 1.404 0.228 6.166 0.000 1.209 0.873
EEC3 1.451 0.180 8.067 0.000 1.250 0.961
TR =~
TR1 1.000 1.117 0.853
TR2 1.191 0.089 13.413 0.000 1.330 0.956
TR3 1.054 0.081 13.078 0.000 1.177 0.917
ADT =~
ADT1 1.000 0.532 0.690
ADT2 0.965 0.242 3.981 0.000 0.513 0.643
ADT3 1.258 0.446 2.823 0.005 0.669 0.739
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.370 0.195 1.898 0.058 0.370 0.606
IM ~~
EEF 0.960 0.196 4.904 0.000 0.641 0.641
EEC 0.608 0.169 3.589 0.000 0.540 0.540
TR 0.290 0.171 1.692 0.091 0.199 0.199
ADT 0.285 0.141 2.028 0.043 0.411 0.411
EEF ~~
EEC 0.569 0.178 3.204 0.001 0.576 0.576
TR 0.166 0.140 1.186 0.236 0.129 0.129
ADT 0.187 0.118 1.588 0.112 0.306 0.306
EEC ~~
TR 0.064 0.113 0.561 0.575 0.066 0.066
ADT 0.117 0.075 1.564 0.118 0.256 0.256
TR ~~
ADT 0.198 0.115 1.716 0.086 0.333 0.333
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 4.806 0.127 37.952 0.000 4.806 3.740
.IM2 5.476 0.117 46.727 0.000 5.476 4.604
.IM3 5.291 0.116 45.533 0.000 5.291 4.487
.EEF1 4.893 0.126 38.905 0.000 4.893 3.833
.EEF2 5.049 0.127 39.794 0.000 5.049 3.921
.EEF3 5.107 0.120 42.410 0.000 5.107 4.179
.EEC1 3.893 0.123 31.719 0.000 3.893 3.125
.EEC2 3.816 0.136 27.965 0.000 3.816 2.755
.EEC3 3.913 0.128 30.533 0.000 3.913 3.008
.TR1 3.233 0.129 25.072 0.000 3.233 2.470
.TR2 3.252 0.137 23.721 0.000 3.252 2.337
.TR3 2.942 0.126 23.263 0.000 2.942 2.292
.ADT1 4.573 0.076 60.205 0.000 4.573 5.932
.ADT2 4.524 0.079 57.496 0.000 4.524 5.665
.ADT3 4.320 0.089 48.430 0.000 4.320 4.772
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 -0.051 0.229 -0.223 0.823 -0.051 -0.031
.IM2 0.621 0.203 3.054 0.002 0.621 0.439
.IM3 0.599 0.201 2.979 0.003 0.599 0.430
.EEF1 0.312 0.068 4.583 0.000 0.312 0.191
.EEF2 0.198 0.069 2.886 0.004 0.198 0.119
.EEF3 0.259 0.113 2.284 0.022 0.259 0.173
.EEC1 0.810 0.109 7.425 0.000 0.810 0.522
.EEC2 0.455 0.164 2.777 0.005 0.455 0.237
.EEC3 0.129 0.076 1.697 0.090 0.129 0.076
.TR1 0.466 0.095 4.888 0.000 0.466 0.272
.TR2 0.168 0.080 2.117 0.034 0.168 0.087
.TR3 0.261 0.079 3.297 0.001 0.261 0.159
.ADT1 0.311 0.105 2.976 0.003 0.311 0.524
.ADT2 0.374 0.097 3.865 0.000 0.374 0.587
.ADT3 0.372 0.197 1.886 0.059 0.372 0.454
IM 1.703 0.370 4.606 0.000 1.000 1.000
EEF 1.318 0.287 4.586 0.000 1.000 1.000
EEC 0.742 0.217 3.425 0.001 1.000 1.000
TR 1.247 0.205 6.074 0.000 1.000 1.000
ADT 0.283 0.154 1.833 0.067 1.000 1.000Trust group
lavaan 0.6-21 ended normally after 77 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 91
0 121
Model Test User Model:
Standard Scaled
Test Statistic 262.830 269.653
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.000
Scaling correction factor 0.975
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 147.547 147.547
0 122.107 122.107
Model Test Baseline Model:
Test statistic 2374.404 1855.689
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.280
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.952 0.932
Tucker-Lewis Index (TLI) 0.936 0.910
Robust Comparative Fit Index (CFI) 0.948
Robust Tucker-Lewis Index (TLI) 0.931
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3699.711 -3699.711
Scaling correction factor 1.652
for the MLR correction
Loglikelihood unrestricted model (H1) -3568.296 -3568.296
Scaling correction factor 1.255
for the MLR correction
Akaike (AIC) 7623.423 7623.423
Bayesian (BIC) 7999.360 7999.360
Sample-size adjusted Bayesian (SABIC) 7644.470 7644.470
Root Mean Square Error of Approximation:
RMSEA 0.079 0.082
90 Percent confidence interval - lower 0.062 0.064
90 Percent confidence interval - upper 0.096 0.098
P-value H_0: RMSEA <= 0.050 0.004 0.002
P-value H_0: RMSEA >= 0.080 0.478 0.576
Robust RMSEA 0.081
90 Percent confidence interval - lower 0.064
90 Percent confidence interval - upper 0.097
P-value H_0: Robust RMSEA <= 0.050 0.002
P-value H_0: Robust RMSEA >= 0.080 0.537
Standardized Root Mean Square Residual:
SRMR 0.069 0.069
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Group 1 [1]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM =~
IM1 1.000 0.970 0.967
IM2 0.669 0.121 5.533 0.000 0.649 0.663
IM3 0.711 0.127 5.583 0.000 0.689 0.607
EEF =~
EEF1 1.000 0.857 0.903
EEF2 1.026 0.084 12.209 0.000 0.879 0.876
EEF3 0.854 0.097 8.844 0.000 0.732 0.827
EEC =~
EEC1 1.000 0.874 0.747
EEC2 1.306 0.169 7.722 0.000 1.141 0.846
EEC3 1.354 0.146 9.283 0.000 1.184 0.914
TR =~
TR1 1.000 0.282 0.360
TR2 1.507 0.516 2.919 0.004 0.425 0.738
TR3 2.140 0.816 2.624 0.009 0.603 0.821
ADT =~
ADT1 1.000 0.907 0.927
ADT2 0.918 0.085 10.784 0.000 0.833 0.912
ADT3 0.951 0.075 12.612 0.000 0.862 0.820
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.399 0.303 1.317 0.188 0.399 0.604
IM ~~
EEF 0.574 0.090 6.360 0.000 0.690 0.690
EEC 0.453 0.150 3.018 0.003 0.535 0.535
TR 0.039 0.043 0.919 0.358 0.144 0.144
ADT 0.248 0.121 2.046 0.041 0.282 0.282
EEF ~~
EEC 0.414 0.089 4.668 0.000 0.553 0.553
TR 0.042 0.038 1.115 0.265 0.175 0.175
ADT 0.254 0.094 2.710 0.007 0.327 0.327
EEC ~~
TR 0.041 0.043 0.947 0.343 0.165 0.165
ADT 0.294 0.093 3.163 0.002 0.371 0.371
TR ~~
ADT 0.107 0.058 1.852 0.064 0.417 0.417
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.385 0.105 51.215 0.000 5.385 5.369
.IM2 5.824 0.103 56.761 0.000 5.824 5.950
.IM3 5.626 0.119 47.275 0.000 5.626 4.956
.EEF1 5.593 0.099 56.225 0.000 5.593 5.894
.EEF2 5.736 0.105 54.520 0.000 5.736 5.715
.EEF3 5.824 0.093 62.817 0.000 5.824 6.585
.EEC1 4.549 0.123 37.099 0.000 4.549 3.889
.EEC2 4.681 0.141 33.088 0.000 4.681 3.469
.EEC3 4.758 0.136 35.042 0.000 4.758 3.673
.TR1 5.121 0.082 62.456 0.000 5.121 6.547
.TR2 5.231 0.060 86.683 0.000 5.231 9.087
.TR3 4.824 0.077 62.595 0.000 4.824 6.562
.ADT1 5.824 0.103 56.761 0.000 5.824 5.950
.ADT2 5.813 0.096 60.751 0.000 5.813 6.368
.ADT3 5.758 0.110 52.222 0.000 5.758 5.474
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.066 0.119 0.553 0.580 0.066 0.065
.IM2 0.537 0.310 1.731 0.083 0.537 0.561
.IM3 0.814 0.342 2.376 0.017 0.814 0.631
.EEF1 0.167 0.065 2.575 0.010 0.167 0.185
.EEF2 0.234 0.072 3.250 0.001 0.234 0.232
.EEF3 0.247 0.085 2.921 0.003 0.247 0.316
.EEC1 0.604 0.121 5.000 0.000 0.604 0.442
.EEC2 0.519 0.165 3.151 0.002 0.519 0.285
.EEC3 0.277 0.112 2.482 0.013 0.277 0.165
.TR1 0.532 0.129 4.118 0.000 0.532 0.870
.TR2 0.151 0.044 3.454 0.001 0.151 0.455
.TR3 0.176 0.104 1.689 0.091 0.176 0.326
.ADT1 0.135 0.058 2.318 0.020 0.135 0.141
.ADT2 0.140 0.058 2.428 0.015 0.140 0.168
.ADT3 0.363 0.174 2.084 0.037 0.363 0.328
IM 0.940 0.223 4.221 0.000 1.000 1.000
EEF 0.734 0.119 6.178 0.000 1.000 1.000
EEC 0.764 0.166 4.595 0.000 1.000 1.000
TR 0.079 0.060 1.319 0.187 1.000 1.000
ADT 0.823 0.153 5.395 0.000 1.000 1.000
Group 2 [0]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM =~
IM1 1.000 1.246 1.000
IM2 0.677 0.139 4.880 0.000 0.843 0.743
IM3 0.604 0.155 3.883 0.000 0.752 0.643
EEF =~
EEF1 1.000 1.174 0.907
EEF2 1.058 0.066 15.985 0.000 1.242 0.955
EEF3 0.983 0.070 13.976 0.000 1.154 0.920
EEC =~
EEC1 1.000 0.973 0.711
EEC2 1.264 0.162 7.800 0.000 1.231 0.872
EEC3 1.328 0.133 9.965 0.000 1.293 0.967
TR =~
TR1 1.000 0.792 0.782
TR2 0.987 0.117 8.449 0.000 0.781 0.800
TR3 1.066 0.127 8.403 0.000 0.844 0.784
ADT =~
ADT1 1.000 0.795 0.817
ADT2 1.090 0.114 9.539 0.000 0.867 0.853
ADT3 1.296 0.153 8.463 0.000 1.031 0.892
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.378 0.151 2.501 0.012 0.378 0.555
IM ~~
EEF 0.940 0.189 4.976 0.000 0.642 0.642
EEC 0.628 0.154 4.076 0.000 0.518 0.518
TR 0.347 0.124 2.800 0.005 0.352 0.352
ADT 0.376 0.144 2.610 0.009 0.379 0.379
EEF ~~
EEC 0.750 0.184 4.064 0.000 0.656 0.656
TR 0.205 0.101 2.036 0.042 0.221 0.221
ADT 0.343 0.134 2.553 0.011 0.367 0.367
EEC ~~
TR 0.123 0.090 1.362 0.173 0.160 0.160
ADT 0.238 0.105 2.275 0.023 0.308 0.308
TR ~~
ADT 0.203 0.086 2.363 0.018 0.322 0.322
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 4.967 0.113 43.848 0.000 4.967 3.986
.IM2 5.537 0.103 53.629 0.000 5.537 4.875
.IM3 5.347 0.106 50.305 0.000 5.347 4.573
.EEF1 5.041 0.118 42.835 0.000 5.041 3.894
.EEF2 5.190 0.118 43.901 0.000 5.190 3.991
.EEF3 5.215 0.114 45.728 0.000 5.215 4.157
.EEC1 4.008 0.125 32.191 0.000 4.008 2.926
.EEC2 3.992 0.128 31.113 0.000 3.992 2.828
.EEC3 4.058 0.122 33.362 0.000 4.058 3.033
.TR1 2.760 0.092 29.988 0.000 2.760 2.726
.TR2 2.653 0.089 29.879 0.000 2.653 2.716
.TR3 2.471 0.098 25.257 0.000 2.471 2.296
.ADT1 5.058 0.088 57.170 0.000 5.058 5.197
.ADT2 4.975 0.092 53.861 0.000 4.975 4.896
.ADT3 4.868 0.105 46.293 0.000 4.868 4.208
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 -0.000 0.165 -0.000 1.000 -0.000 -0.000
.IM2 0.579 0.173 3.345 0.001 0.579 0.449
.IM3 0.802 0.301 2.662 0.008 0.802 0.586
.EEF1 0.297 0.062 4.768 0.000 0.297 0.177
.EEF2 0.148 0.054 2.748 0.006 0.148 0.087
.EEF3 0.241 0.087 2.763 0.006 0.241 0.153
.EEC1 0.928 0.138 6.737 0.000 0.928 0.495
.EEC2 0.478 0.139 3.435 0.001 0.478 0.240
.EEC3 0.118 0.066 1.794 0.073 0.118 0.066
.TR1 0.399 0.100 3.989 0.000 0.399 0.389
.TR2 0.343 0.100 3.442 0.001 0.343 0.360
.TR3 0.446 0.145 3.080 0.002 0.446 0.385
.ADT1 0.314 0.082 3.841 0.000 0.314 0.332
.ADT2 0.281 0.082 3.435 0.001 0.281 0.272
.ADT3 0.275 0.086 3.199 0.001 0.275 0.205
IM 1.553 0.313 4.956 0.000 1.000 1.000
EEF 1.379 0.273 5.051 0.000 1.000 1.000
EEC 0.948 0.227 4.181 0.000 1.000 1.000
TR 0.627 0.116 5.408 0.000 1.000 1.000
ADT 0.633 0.168 3.771 0.000 1.000 1.000
Chi-Squared Difference Test
Df AIC BIC Chisq Chisq diff RMSEA Df diff Pr(>Chisq)
fit_config 158 7623.4 7999.4 262.83
fit_metric 168 7616.8 7959.2 276.24 13.4109 0.056726 10 0.2016
fit_scalar 178 7603.4 7912.2 282.78 6.5358 0.000000 10 0.7684 config metric scalar
chisq 262.83003373 276.24092032 282.77671030
df 158.00000000 168.00000000 178.00000000
cfi 0.95156633 0.94999043 0.95159096
rmsea 0.07911547 0.07796293 0.07451942
srmr 0.06854373 0.06919511 0.07127234<NA>
NA <NA>
NA <NA>
NA <NA>
NA lhs op rhs block group level mi epc sepc.lv sepc.all sepc.nox
470 ADT2 ~~ ADT3 2 2 1 10.808 0.241 0.241 0.793 0.793
276 EEC1 ~~ ADT1 1 1 1 10.730 0.139 0.139 0.448 0.448SEM
Without moderation
Without control variable
No moderation - without PEB control variablelavaan 0.6-21 ended normally after 64 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 56
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 186.252 175.197
Degrees of freedom 139 139
P-value (Chi-square) 0.005 0.020
Scaling correction factor 1.063
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2854.597 2297.134
Degrees of freedom 180 180
P-value 0.000 0.000
Scaling correction factor 1.243
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.982 0.983
Tucker-Lewis Index (TLI) 0.977 0.978
Robust Comparative Fit Index (CFI) 0.985
Robust Tucker-Lewis Index (TLI) 0.981
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3885.007 -3885.007
Scaling correction factor 1.701
for the MLR correction
Loglikelihood unrestricted model (H1) -3791.881 -3791.881
Scaling correction factor 1.246
for the MLR correction
Akaike (AIC) 7882.014 7882.014
Bayesian (BIC) 8069.983 8069.983
Sample-size adjusted Bayesian (SABIC) 7892.538 7892.538
Root Mean Square Error of Approximation:
RMSEA 0.040 0.035
90 Percent confidence interval - lower 0.023 0.016
90 Percent confidence interval - upper 0.054 0.050
P-value H_0: RMSEA <= 0.050 0.867 0.953
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.036
90 Percent confidence interval - lower 0.015
90 Percent confidence interval - upper 0.052
P-value H_0: Robust RMSEA <= 0.050 0.926
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.044 0.044
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EEC =~
EEC1 1.000 0.968 0.737
EEC2 1.285 0.110 11.684 0.000 1.244 0.873
EEC3 1.331 0.093 14.261 0.000 1.288 0.946
EEF =~
EEF1 1.000 1.084 0.912
EEF2 1.041 0.054 19.249 0.000 1.129 0.933
EEF3 0.955 0.056 17.032 0.000 1.036 0.901
ADT =~
ADT1 1.000 0.922 0.881
ADT2 1.030 0.069 15.031 0.000 0.950 0.898
ADT3 1.142 0.076 14.983 0.000 1.054 0.880
TR =~
TR1 1.000 1.318 0.886
TR2 1.086 0.048 22.568 0.000 1.431 0.941
TR3 1.048 0.050 20.862 0.000 1.381 0.921
IM =~
IM1 1.000 1.151 0.989
IM2 0.675 0.110 6.159 0.000 0.777 0.720
IM3 0.640 0.120 5.339 0.000 0.737 0.634
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.094 0.227 0.412 0.680 0.081 0.030
rwrd0_2 (b_02) 0.200 0.260 0.770 0.441 0.174 0.065
rwrd1_2 (b_12) 0.222 0.255 0.869 0.385 0.193 0.071
rwrd0_3 (b_03) -0.137 0.275 -0.497 0.619 -0.119 -0.045
rwrd1_3 (b_13) -0.220 0.236 -0.932 0.351 -0.191 -0.072
TR (b_TR) 0.125 0.063 1.970 0.049 0.143 0.143
ADT (b_AD) 0.372 0.108 3.453 0.001 0.298 0.298
EEF ~
rwrd1_1 (c_11) 0.213 0.180 1.180 0.238 0.196 0.071
rwrd0_2 (c_02) -0.114 0.204 -0.556 0.578 -0.105 -0.039
rwrd1_2 (c_12) 0.201 0.180 1.118 0.263 0.186 0.068
rwrd0_3 (c_03) -0.197 0.171 -1.150 0.250 -0.182 -0.068
rwrd1_3 (c_13) -0.059 0.177 -0.331 0.740 -0.054 -0.020
IM (c_IM) 0.543 0.082 6.616 0.000 0.577 0.577
TR (c_TR) 0.052 0.057 0.914 0.361 0.063 0.063
ADT (c_AD) 0.189 0.084 2.260 0.024 0.161 0.161
EEC ~
rwrd1_1 (d_11) 0.227 0.208 1.094 0.274 0.235 0.085
rwrd0_2 (d_02) 0.186 0.215 0.866 0.386 0.192 0.072
rwrd1_2 (d_12) 0.336 0.188 1.788 0.074 0.347 0.127
rwrd0_3 (d_03) 0.076 0.176 0.433 0.665 0.079 0.030
rwrd1_3 (d_13) 0.015 0.196 0.075 0.940 0.015 0.006
IM (d_IM) 0.359 0.081 4.421 0.000 0.426 0.426
TR (d_TR) 0.067 0.056 1.211 0.226 0.091 0.091
ADT (d_AD) 0.201 0.079 2.530 0.011 0.192 0.192
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.385 0.162 2.382 0.017 0.385 0.572
ADT ~~
TR 0.639 0.107 5.968 0.000 0.525 0.525
.EEC ~~
.EEF 0.244 0.074 3.314 0.001 0.409 0.409
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEC1 0.789 0.094 8.435 0.000 0.789 0.457
.EEC2 0.482 0.104 4.637 0.000 0.482 0.237
.EEC3 0.196 0.062 3.144 0.002 0.196 0.106
.EEF1 0.238 0.045 5.312 0.000 0.238 0.168
.EEF2 0.191 0.046 4.109 0.000 0.191 0.130
.EEF3 0.248 0.064 3.892 0.000 0.248 0.188
.ADT1 0.245 0.057 4.288 0.000 0.245 0.224
.ADT2 0.217 0.054 4.012 0.000 0.217 0.194
.ADT3 0.323 0.089 3.615 0.000 0.323 0.225
.TR1 0.477 0.083 5.717 0.000 0.477 0.215
.TR2 0.266 0.068 3.930 0.000 0.266 0.115
.TR3 0.343 0.088 3.880 0.000 0.343 0.152
.IM1 0.030 0.122 0.241 0.809 0.030 0.022
.IM2 0.561 0.172 3.264 0.001 0.561 0.482
.IM3 0.807 0.232 3.484 0.000 0.807 0.597
.EEC 0.603 0.097 6.230 0.000 0.643 0.643
.EEF 0.592 0.123 4.810 0.000 0.504 0.504
ADT 0.851 0.125 6.804 0.000 1.000 1.000
TR 1.736 0.173 10.049 0.000 1.000 1.000
.IM 1.095 0.171 6.389 0.000 0.826 0.826
R-Square:
Estimate
EEC1 0.543
EEC2 0.763
EEC3 0.894
EEF1 0.832
EEF2 0.870
EEF3 0.812
ADT1 0.776
ADT2 0.806
ADT3 0.775
TR1 0.785
TR2 0.885
TR3 0.848
IM1 0.978
IM2 0.518
IM3 0.403
EEC 0.357
EEF 0.496
IM 0.174
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.094 0.227 0.412 0.680 0.081 0.030
reward2_IM 0.022 0.266 0.082 0.935 0.019 0.005
reward3_IM -0.083 0.276 -0.300 0.764 -0.072 -0.027
reward_vrgd_IM 0.011 0.149 0.073 0.942 0.009 0.003
reward_EEF_ec1 0.213 0.180 1.180 0.238 0.196 0.071
reward_EEF_ec2 0.315 0.218 1.443 0.149 0.290 0.107
reward_EEF_ec3 0.138 0.189 0.730 0.465 0.128 0.048
reward_man_EEF 0.222 0.112 1.976 0.048 0.205 0.075
ind_rwrd_EEF_1 0.051 0.125 0.407 0.684 0.047 0.017
ind_rwrd_EEF_2 0.012 0.144 0.082 0.935 0.011 0.003
ind_rwrd_EEF_3 -0.045 0.151 -0.298 0.766 -0.041 -0.016
ind_rw__IM_EEF 0.006 0.081 0.073 0.942 0.005 0.002
tt_rwrd_mn_EEF 0.228 0.136 1.674 0.094 0.210 0.077
reward_EEC_ec1 0.227 0.208 1.094 0.274 0.235 0.085
reward_EEC_ec2 0.150 0.203 0.738 0.460 0.154 0.055
reward_EEC_ec3 -0.062 0.185 -0.333 0.739 -0.064 -0.024
reward_man_EEC 0.105 0.114 0.921 0.357 0.108 0.039
ind_rwrd_EEC_1 0.034 0.084 0.402 0.688 0.035 0.013
ind_rwrd_EEC_2 0.008 0.095 0.082 0.935 0.008 0.002
ind_rwrd_EEC_3 -0.030 0.099 -0.299 0.765 -0.031 -0.012
ind_rw__IM_EEC 0.004 0.054 0.073 0.942 0.004 0.001
tt_rwrd_mn_EEC 0.109 0.126 0.864 0.387 0.112 0.040
eco2_vs_c1_EEF -0.062 0.144 -0.435 0.664 -0.058 -0.021
eco3_vs_c1_EEF -0.234 0.130 -1.796 0.072 -0.216 -0.080
eco1_vs_c2_EEF 0.062 0.144 0.435 0.664 0.058 0.021
eco_main_EEF -0.148 0.114 -1.296 0.195 -0.137 -0.050
eco2_vs_ec1_IM 0.164 0.172 0.954 0.340 0.142 0.053
eco3_vs_ec1_IM -0.225 0.182 -1.238 0.216 -0.196 -0.073
eco1_vs_ec2_IM -0.164 0.172 -0.954 0.340 -0.142 -0.053
in_1__2_IM_EEF -0.089 0.096 -0.928 0.353 -0.082 -0.031
in_2__1_IM_EEF 0.089 0.096 0.928 0.353 0.082 0.031
in_3__1_IM_EEF -0.122 0.105 -1.169 0.242 -0.113 -0.042
ind_c_m_IM_EEF -0.017 0.079 -0.210 0.834 -0.015 -0.006
tt_c1_vs_2_EEF -0.027 0.164 -0.161 0.872 -0.024 -0.010
tt_c2_vs_1_EEF 0.027 0.164 0.161 0.872 0.024 0.010
tt_c3_vs_1_EEF -0.356 0.159 -2.247 0.025 -0.329 -0.122
tot_eco_mn_EEF -0.165 0.135 -1.218 0.223 -0.152 -0.056
eco2_vs_c1_EEC 0.147 0.150 0.983 0.326 0.152 0.057
eco3_vs_c1_EEC -0.068 0.137 -0.498 0.619 -0.070 -0.025
eco_main_EEC 0.040 0.125 0.317 0.751 0.041 0.016
in_2__1_IM_EEC 0.059 0.064 0.916 0.359 0.061 0.023
in_3__1_IM_EEC -0.081 0.072 -1.114 0.265 -0.083 -0.031
ind_c_m_IM_EEC -0.011 0.053 -0.209 0.835 -0.011 -0.004
tt_c2_vs_1_EEC 0.206 0.163 1.267 0.205 0.213 0.080
tt_c3_vs_1_EEC -0.149 0.143 -1.040 0.298 -0.154 -0.056
tot_eco_mn_EEC 0.029 0.130 0.220 0.826 0.030 0.012
reward_IM_eco1 0.094 0.227 0.412 0.680 0.081 0.030
reward_IM_eco2 0.022 0.266 0.082 0.935 0.019 0.005
reward_IM_eco3 -0.083 0.276 -0.300 0.764 -0.072 -0.027
reward_main_IM 0.011 0.149 0.073 0.942 0.009 0.003
eco3_vs_c2_EEF -0.172 0.151 -1.133 0.257 -0.158 -0.059
in_3__2_IM_EEF -0.211 0.123 -1.718 0.086 -0.195 -0.073
tt_c3_vs_2_EEF -0.383 0.176 -2.172 0.030 -0.353 -0.131
eco3_vs_c2_EEC -0.215 0.141 -1.527 0.127 -0.222 -0.082
in_3__2_IM_EEC -0.140 0.088 -1.592 0.111 -0.144 -0.054
tt_c3_vs_2_EEC -0.355 0.162 -2.187 0.029 -0.366 -0.136 lhs op
85 ind_reward_EEF_eco1 :=
86 ind_reward_EEF_eco2 :=
87 ind_reward_EEF_eco3 :=
88 ind_reward_main_IM_EEF :=
89 tot_reward_main_EEF :=
94 ind_reward_EEC_eco1 :=
95 ind_reward_EEC_eco2 :=
96 ind_reward_EEC_eco3 :=
97 ind_reward_main_IM_EEC :=
98 tot_reward_main_EEC :=
106 ind_eco1_vs_eco2_IM_EEF :=
107 ind_eco2_vs_eco1_IM_EEF :=
108 ind_eco3_vs_eco1_IM_EEF :=
109 ind_eco_main_IM_EEF :=
110 tot_eco1_vs_eco2_EEF :=
111 tot_eco2_vs_eco1_EEF :=
112 tot_eco3_vs_eco1_EEF :=
113 tot_eco_main_EEF :=
117 ind_eco2_vs_eco1_IM_EEC :=
118 ind_eco3_vs_eco1_IM_EEC :=
119 ind_eco_main_IM_EEC :=
120 tot_eco2_vs_eco1_EEC :=
121 tot_eco3_vs_eco1_EEC :=
122 tot_eco_main_EEC :=
128 ind_eco3_vs_eco2_IM_EEF :=
129 tot_eco3_vs_eco2_EEF :=
131 ind_eco3_vs_eco2_IM_EEC :=
132 tot_eco3_vs_eco2_EEC :=
rhs label
85 (b_r1e1-0)*c_IM ind_reward_EEF_eco1
86 (b_r1e2-b_r0e2)*c_IM ind_reward_EEF_eco2
87 (b_r1e3-b_r0e3)*c_IM ind_reward_EEF_eco3
88 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3*c_IM ind_reward_main_IM_EEF
89 reward_main_EEF+ind_reward_main_IM_EEF tot_reward_main_EEF
94 (b_r1e1-0)*d_IM ind_reward_EEC_eco1
95 (b_r1e2-b_r0e2)*d_IM ind_reward_EEC_eco2
96 (b_r1e3-b_r0e3)*d_IM ind_reward_EEC_eco3
97 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3*d_IM ind_reward_main_IM_EEC
98 reward_main_EEC+ind_reward_main_IM_EEC tot_reward_main_EEC
106 eco1_vs_eco2_IM*c_IM ind_eco1_vs_eco2_IM_EEF
107 eco2_vs_eco1_IM*c_IM ind_eco2_vs_eco1_IM_EEF
108 eco3_vs_eco1_IM*c_IM ind_eco3_vs_eco1_IM_EEF
109 (ind_eco2_vs_eco1_IM_EEF+ind_eco3_vs_eco1_IM_EEF)/2 ind_eco_main_IM_EEF
110 eco1_vs_eco2_EEF+ind_eco1_vs_eco2_IM_EEF tot_eco1_vs_eco2_EEF
111 eco2_vs_eco1_EEF+ind_eco2_vs_eco1_IM_EEF tot_eco2_vs_eco1_EEF
112 eco3_vs_eco1_EEF+ind_eco3_vs_eco1_IM_EEF tot_eco3_vs_eco1_EEF
113 eco_main_EEF+ind_eco_main_IM_EEF tot_eco_main_EEF
117 eco2_vs_eco1_IM*d_IM ind_eco2_vs_eco1_IM_EEC
118 eco3_vs_eco1_IM*d_IM ind_eco3_vs_eco1_IM_EEC
119 (ind_eco2_vs_eco1_IM_EEC+ind_eco3_vs_eco1_IM_EEC)/2 ind_eco_main_IM_EEC
120 eco2_vs_eco1_EEC+ind_eco2_vs_eco1_IM_EEC tot_eco2_vs_eco1_EEC
121 eco3_vs_eco1_EEC+ind_eco3_vs_eco1_IM_EEC tot_eco3_vs_eco1_EEC
122 eco_main_EEC+ind_eco_main_IM_EEC tot_eco_main_EEC
128 ind_eco3_vs_eco1_IM_EEF-ind_eco2_vs_eco1_IM_EEF ind_eco3_vs_eco2_IM_EEF
129 tot_eco3_vs_eco1_EEF-tot_eco2_vs_eco1_EEF tot_eco3_vs_eco2_EEF
131 ind_eco3_vs_eco1_IM_EEC-ind_eco2_vs_eco1_IM_EEC ind_eco3_vs_eco2_IM_EEC
132 tot_eco3_vs_eco1_EEC-tot_eco2_vs_eco1_EEC tot_eco3_vs_eco2_EEC
est se z pvalue ci.lower ci.upper std.lv std.all std.nox
85 0.051 0.116 0.439 0.661 -0.140 0.299 0.047 0.017 0.047
86 0.012 0.162 0.073 0.942 -0.329 0.289 0.011 0.003 0.011
87 -0.045 0.197 -0.229 0.819 -0.396 0.451 -0.041 -0.016 -0.041
88 0.006 0.088 0.067 0.947 -0.133 0.227 0.005 0.002 0.005
89 0.228 0.131 1.740 0.082 0.002 0.547 0.210 0.077 0.210
94 0.034 0.077 0.436 0.663 -0.095 0.220 0.035 0.013 0.035
95 0.008 0.111 0.070 0.944 -0.219 0.232 0.008 0.002 0.008
96 -0.030 0.139 -0.214 0.831 -0.282 0.328 -0.031 -0.012 -0.031
97 0.004 0.059 0.066 0.947 -0.094 0.146 0.004 0.001 0.004
98 0.109 0.138 0.790 0.430 -0.157 0.409 0.112 0.040 0.112
106 -0.089 0.098 -0.912 0.362 -0.279 0.104 -0.082 -0.031 -0.082
107 0.089 0.098 0.912 0.362 -0.104 0.279 0.082 0.031 0.082
108 -0.122 0.103 -1.189 0.235 -0.404 0.035 -0.113 -0.042 -0.113
109 -0.017 0.075 -0.220 0.826 -0.239 0.103 -0.015 -0.006 -0.015
110 -0.027 0.172 -0.154 0.877 -0.276 0.450 -0.024 -0.010 -0.024
111 0.027 0.172 0.154 0.877 -0.450 0.276 0.024 0.010 0.024
112 -0.356 0.133 -2.681 0.007 -0.667 -0.140 -0.329 -0.122 -0.329
113 -0.165 0.125 -1.314 0.189 -0.520 0.029 -0.152 -0.056 -0.152
117 0.059 0.068 0.869 0.385 -0.081 0.219 0.061 0.023 0.061
118 -0.081 0.079 -1.018 0.309 -0.302 0.024 -0.083 -0.031 -0.083
119 -0.011 0.054 -0.204 0.838 -0.183 0.074 -0.011 -0.004 -0.011
120 0.206 0.161 1.283 0.200 -0.121 0.515 0.213 0.080 0.213
121 -0.149 0.141 -1.058 0.290 -0.427 0.130 -0.154 -0.056 -0.154
122 0.029 0.130 0.220 0.826 -0.246 0.282 0.030 0.012 0.030
128 -0.211 0.132 -1.601 0.109 -0.558 0.026 -0.195 -0.073 -0.195
129 -0.383 0.178 -2.153 0.031 -0.802 -0.023 -0.353 -0.131 -0.353
131 -0.140 0.101 -1.385 0.166 -0.422 0.017 -0.144 -0.054 -0.144
132 -0.355 0.154 -2.308 0.021 -0.669 -0.055 -0.366 -0.136 -0.366With control variable
No moderation - without PEB control variablelavaan 0.6-21 ended normally after 63 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 59
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 200.318 189.145
Degrees of freedom 151 151
P-value (Chi-square) 0.004 0.019
Scaling correction factor 1.059
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2915.592 2374.313
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.228
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.982 0.982
Tucker-Lewis Index (TLI) 0.977 0.977
Robust Comparative Fit Index (CFI) 0.985
Robust Tucker-Lewis Index (TLI) 0.981
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3861.543 -3861.543
Scaling correction factor 1.676
for the MLR correction
Loglikelihood unrestricted model (H1) -3761.384 -3761.384
Scaling correction factor 1.232
for the MLR correction
Akaike (AIC) 7841.086 7841.086
Bayesian (BIC) 8039.124 8039.124
Sample-size adjusted Bayesian (SABIC) 7852.173 7852.173
Root Mean Square Error of Approximation:
RMSEA 0.039 0.035
90 Percent confidence interval - lower 0.023 0.016
90 Percent confidence interval - upper 0.053 0.049
P-value H_0: RMSEA <= 0.050 0.895 0.964
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.036
90 Percent confidence interval - lower 0.015
90 Percent confidence interval - upper 0.051
P-value H_0: Robust RMSEA <= 0.050 0.942
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.046 0.046
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EEC =~
EEC1 1.000 0.962 0.735
EEC2 1.284 0.110 11.700 0.000 1.235 0.872
EEC3 1.329 0.093 14.296 0.000 1.279 0.945
EEF =~
EEF1 1.000 1.074 0.911
EEF2 1.040 0.052 19.971 0.000 1.117 0.931
EEF3 0.954 0.056 17.077 0.000 1.025 0.900
ADT =~
ADT1 1.000 0.922 0.881
ADT2 1.029 0.068 15.139 0.000 0.949 0.898
ADT3 1.143 0.076 15.054 0.000 1.054 0.881
TR =~
TR1 1.000 1.318 0.886
TR2 1.087 0.048 22.515 0.000 1.432 0.941
TR3 1.048 0.050 20.913 0.000 1.381 0.920
IM =~
IM1 1.000 1.108 0.961
IM2 0.713 0.104 6.831 0.000 0.790 0.736
IM3 0.681 0.121 5.636 0.000 0.754 0.652
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.211 0.214 0.985 0.325 0.190 0.069
rwrd0_2 (b_02) 0.249 0.237 1.049 0.294 0.225 0.084
rwrd1_2 (b_12) 0.325 0.232 1.403 0.161 0.293 0.108
rwrd0_3 (b_03) 0.013 0.253 0.052 0.959 0.012 0.004
rwrd1_3 (b_13) -0.079 0.198 -0.398 0.691 -0.071 -0.027
TR (b_TR) 0.098 0.055 1.791 0.073 0.116 0.116
ADT (b_AD) 0.352 0.100 3.514 0.000 0.293 0.293
PEB_yes (b_PE) 1.036 0.168 6.169 0.000 0.935 0.400
EEF ~
rwrd1_1 (c_11) 0.230 0.182 1.260 0.208 0.214 0.078
rwrd0_2 (c_02) -0.107 0.194 -0.549 0.583 -0.099 -0.037
rwrd1_2 (c_12) 0.214 0.179 1.197 0.231 0.199 0.073
rwrd0_3 (c_03) -0.153 0.170 -0.900 0.368 -0.142 -0.053
rwrd1_3 (c_13) -0.013 0.177 -0.075 0.940 -0.012 -0.005
IM (c_IM) 0.514 0.083 6.166 0.000 0.530 0.530
TR (c_TR) 0.045 0.054 0.839 0.401 0.055 0.055
ADT (c_AD) 0.206 0.080 2.572 0.010 0.177 0.177
PEB_yes (c_PE) 0.361 0.167 2.161 0.031 0.336 0.144
EEC ~
rwrd1_1 (d_11) 0.234 0.211 1.109 0.267 0.244 0.088
rwrd0_2 (d_02) 0.189 0.218 0.867 0.386 0.196 0.074
rwrd1_2 (d_12) 0.340 0.194 1.752 0.080 0.353 0.130
rwrd0_3 (d_03) 0.101 0.176 0.573 0.567 0.105 0.039
rwrd1_3 (d_13) 0.041 0.196 0.207 0.836 0.042 0.016
IM (d_IM) 0.346 0.090 3.835 0.000 0.399 0.399
TR (d_TR) 0.063 0.055 1.140 0.254 0.086 0.086
ADT (d_AD) 0.210 0.082 2.557 0.011 0.201 0.201
PEB_yes (d_PE) 0.195 0.162 1.205 0.228 0.203 0.087
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.350 0.161 2.170 0.030 0.350 0.549
ADT ~~
TR 0.639 0.107 5.975 0.000 0.525 0.525
.EEC ~~
.EEF 0.222 0.068 3.283 0.001 0.388 0.388
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEC1 0.787 0.093 8.433 0.000 0.787 0.460
.EEC2 0.482 0.103 4.660 0.000 0.482 0.240
.EEC3 0.197 0.062 3.150 0.002 0.197 0.107
.EEF1 0.235 0.045 5.290 0.000 0.235 0.169
.EEF2 0.192 0.045 4.293 0.000 0.192 0.133
.EEF3 0.248 0.064 3.904 0.000 0.248 0.191
.ADT1 0.245 0.056 4.347 0.000 0.245 0.223
.ADT2 0.218 0.054 4.026 0.000 0.218 0.194
.ADT3 0.322 0.088 3.658 0.000 0.322 0.225
.TR1 0.477 0.083 5.715 0.000 0.477 0.215
.TR2 0.265 0.068 3.893 0.000 0.265 0.114
.TR3 0.344 0.088 3.922 0.000 0.344 0.153
.IM1 0.102 0.098 1.047 0.295 0.102 0.077
.IM2 0.528 0.170 3.117 0.002 0.528 0.459
.IM3 0.770 0.236 3.262 0.001 0.770 0.575
.EEC 0.590 0.094 6.242 0.000 0.637 0.637
.EEF 0.554 0.109 5.098 0.000 0.480 0.480
ADT 0.851 0.125 6.833 0.000 1.000 1.000
TR 1.736 0.173 10.049 0.000 1.000 1.000
.IM 0.837 0.151 5.554 0.000 0.682 0.682
R-Square:
Estimate
EEC1 0.540
EEC2 0.760
EEC3 0.893
EEF1 0.831
EEF2 0.867
EEF3 0.809
ADT1 0.777
ADT2 0.806
ADT3 0.775
TR1 0.785
TR2 0.886
TR3 0.847
IM1 0.923
IM2 0.541
IM3 0.425
EEC 0.363
EEF 0.520
IM 0.318
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.211 0.214 0.985 0.325 0.190 0.069
reward2_IM 0.076 0.249 0.305 0.760 0.069 0.023
reward3_IM -0.092 0.246 -0.374 0.708 -0.083 -0.031
reward_vrgd_IM 0.065 0.137 0.473 0.636 0.059 0.020
reward_EEF_ec1 0.230 0.182 1.260 0.208 0.214 0.078
reward_EEF_ec2 0.320 0.211 1.522 0.128 0.298 0.110
reward_EEF_ec3 0.140 0.188 0.742 0.458 0.130 0.049
reward_man_EEF 0.230 0.113 2.034 0.042 0.214 0.079
ind_rwrd_EEF_1 0.108 0.114 0.950 0.342 0.101 0.037
ind_rwrd_EEF_2 0.039 0.127 0.307 0.759 0.036 0.012
ind_rwrd_EEF_3 -0.047 0.127 -0.371 0.711 -0.044 -0.017
ind_rw__IM_EEF 0.033 0.070 0.475 0.635 0.031 0.011
tt_rwrd_mn_EEF 0.263 0.128 2.061 0.039 0.245 0.090
reward_EEC_ec1 0.234 0.211 1.109 0.267 0.244 0.088
reward_EEC_ec2 0.151 0.203 0.745 0.456 0.157 0.056
reward_EEC_ec3 -0.060 0.181 -0.331 0.740 -0.062 -0.023
reward_man_EEC 0.109 0.114 0.949 0.343 0.113 0.040
ind_rwrd_EEC_1 0.073 0.082 0.895 0.371 0.076 0.027
ind_rwrd_EEC_2 0.026 0.087 0.303 0.762 0.027 0.009
ind_rwrd_EEC_3 -0.032 0.086 -0.370 0.711 -0.033 -0.012
ind_rw__IM_EEC 0.022 0.049 0.462 0.644 0.023 0.008
tt_rwrd_mn_EEC 0.131 0.123 1.069 0.285 0.136 0.048
eco2_vs_c1_EEF -0.061 0.139 -0.439 0.661 -0.057 -0.021
eco3_vs_c1_EEF -0.198 0.129 -1.540 0.124 -0.184 -0.068
eco1_vs_c2_EEF 0.061 0.139 0.439 0.661 0.057 0.021
eco_main_EEF -0.130 0.113 -1.148 0.251 -0.121 -0.044
eco2_vs_ec1_IM 0.182 0.158 1.149 0.251 0.164 0.062
eco3_vs_ec1_IM -0.138 0.162 -0.855 0.392 -0.125 -0.046
eco1_vs_ec2_IM -0.182 0.158 -1.149 0.251 -0.164 -0.062
in_1__2_IM_EEF -0.093 0.083 -1.130 0.259 -0.087 -0.033
in_2__1_IM_EEF 0.093 0.083 1.130 0.259 0.087 0.033
in_3__1_IM_EEF -0.071 0.086 -0.831 0.406 -0.066 -0.024
ind_c_m_IM_EEF 0.011 0.068 0.164 0.870 0.010 0.004
tt_c1_vs_2_EEF -0.032 0.153 -0.210 0.834 -0.030 -0.012
tt_c2_vs_1_EEF 0.032 0.153 0.210 0.834 0.030 0.012
tt_c3_vs_1_EEF -0.269 0.149 -1.804 0.071 -0.251 -0.092
tot_eco_mn_EEF -0.119 0.127 -0.931 0.352 -0.110 -0.040
eco2_vs_c1_EEC 0.147 0.151 0.974 0.330 0.153 0.058
eco3_vs_c1_EEC -0.047 0.135 -0.345 0.730 -0.048 -0.017
eco_main_EEC 0.050 0.125 0.403 0.687 0.052 0.020
in_2__1_IM_EEC 0.063 0.056 1.131 0.258 0.065 0.025
in_3__1_IM_EEC -0.048 0.060 -0.801 0.423 -0.050 -0.018
ind_c_m_IM_EEC 0.008 0.046 0.165 0.869 0.008 0.003
tt_c2_vs_1_EEC 0.210 0.161 1.305 0.192 0.218 0.082
tt_c3_vs_1_EEC -0.094 0.135 -0.698 0.485 -0.098 -0.035
tot_eco_mn_EEC 0.058 0.128 0.453 0.651 0.060 0.024
eco3_vs_c2_EEF -0.137 0.145 -0.946 0.344 -0.127 -0.047
in_3__2_IM_EEF -0.164 0.099 -1.663 0.096 -0.153 -0.057
tt_c3_vs_2_EEF -0.301 0.163 -1.849 0.065 -0.280 -0.104
eco3_vs_c2_EEC -0.194 0.141 -1.376 0.169 -0.201 -0.074
in_3__2_IM_EEC -0.111 0.071 -1.564 0.118 -0.115 -0.043
tt_c3_vs_2_EEC -0.305 0.152 -1.999 0.046 -0.316 -0.117
reward_IM_eco1 0.211 0.214 0.985 0.325 0.190 0.069
reward_IM_eco2 0.076 0.249 0.305 0.760 0.069 0.023
reward_IM_eco3 -0.092 0.246 -0.374 0.708 -0.083 -0.031
reward_main_IM 0.065 0.137 0.473 0.636 0.059 0.020Moderation
TR
Without control
TR moderation using the dichotomized moderatorlavaan 0.6-21 ended normally after 73 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 63
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 558.354 551.928
Degrees of freedom 222 222
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.012
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3231.681 2839.857
Degrees of freedom 270 270
P-value 0.000 0.000
Scaling correction factor 1.138
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.886 0.872
Tucker-Lewis Index (TLI) 0.862 0.844
Robust Comparative Fit Index (CFI) 0.886
Robust Tucker-Lewis Index (TLI) 0.861
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3882.516 -3882.516
Scaling correction factor 1.619
for the MLR correction
Loglikelihood unrestricted model (H1) -3603.339 -3603.339
Scaling correction factor 1.146
for the MLR correction
Akaike (AIC) 7891.032 7891.032
Bayesian (BIC) 8102.497 8102.497
Sample-size adjusted Bayesian (SABIC) 7902.871 7902.871
Root Mean Square Error of Approximation:
RMSEA 0.085 0.084
90 Percent confidence interval - lower 0.076 0.075
90 Percent confidence interval - upper 0.093 0.092
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.808 0.765
Robust RMSEA 0.084
90 Percent confidence interval - lower 0.075
90 Percent confidence interval - upper 0.093
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.789
Standardized Root Mean Square Residual:
SRMR 0.119 0.119
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EEC =~
EEC1 1.000 0.955 0.732
EEC2 1.287 0.110 11.666 0.000 1.228 0.872
EEC3 1.328 0.093 14.267 0.000 1.268 0.943
EEF =~
EEF1 1.000 1.078 0.911
EEF2 1.041 0.054 19.275 0.000 1.122 0.932
EEF3 0.955 0.056 17.035 0.000 1.030 0.900
ADT =~
ADT1 1.000 0.923 0.882
ADT2 1.029 0.068 15.023 0.000 0.950 0.898
ADT3 1.141 0.076 14.977 0.000 1.053 0.880
TR =~
TR1 1.000 1.317 0.885
TR2 1.090 0.049 22.373 0.000 1.435 0.943
TR3 1.047 0.050 21.004 0.000 1.378 0.919
IM =~
IM1 1.000 1.224 1.001
IM2 0.659 0.111 5.940 0.000 0.806 0.728
IM3 0.624 0.121 5.171 0.000 0.764 0.645
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
reward1_eco1 0.214 0.288 0.743 0.458 0.175 0.063
reward0_eco2 0.379 0.317 1.194 0.232 0.309 0.116
reward1_eco2 0.390 0.330 1.184 0.236 0.319 0.117
reward0_eco3 0.106 0.371 0.285 0.776 0.086 0.032
reward1_eco3 -0.040 0.348 -0.114 0.909 -0.032 -0.012
reward1_ec1_TR -0.299 0.347 -0.861 0.389 -0.244 -0.065
reward0_ec2_TR -0.454 0.433 -1.048 0.295 -0.371 -0.092
reward1_ec2_TR -0.388 0.399 -0.972 0.331 -0.317 -0.079
reward0_ec3_TR -0.491 0.501 -0.982 0.326 -0.402 -0.109
reward1_ec3_TR -0.424 0.428 -0.992 0.321 -0.347 -0.086
TR 0.230 0.107 2.138 0.033 0.247 0.247
ADT 0.386 0.105 3.672 0.000 0.291 0.291
EEF ~
IM 0.536 0.084 6.393 0.000 0.609 0.609
reward1_eco1 0.215 0.181 1.191 0.234 0.200 0.072
reward0_eco2 -0.107 0.206 -0.516 0.606 -0.099 -0.037
reward1_eco2 0.197 0.180 1.091 0.275 0.182 0.067
reward0_eco3 -0.217 0.171 -1.266 0.206 -0.201 -0.076
reward1_eco3 -0.059 0.178 -0.333 0.739 -0.055 -0.021
TR_high_num 0.261 0.218 1.197 0.231 0.242 0.120
TR -0.036 0.094 -0.387 0.699 -0.044 -0.044
ADT 0.196 0.084 2.328 0.020 0.168 0.168
EEC ~
IM 0.359 0.083 4.339 0.000 0.461 0.461
reward1_eco1 0.227 0.209 1.087 0.277 0.238 0.086
reward0_eco2 0.192 0.215 0.893 0.372 0.201 0.075
reward1_eco2 0.328 0.186 1.762 0.078 0.343 0.126
reward0_eco3 0.057 0.175 0.329 0.742 0.060 0.023
reward1_eco3 0.016 0.195 0.080 0.936 0.016 0.006
TR_high_num 0.278 0.224 1.242 0.214 0.291 0.144
TR -0.028 0.098 -0.284 0.776 -0.039 -0.039
ADT 0.207 0.079 2.622 0.009 0.201 0.201
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.399 0.162 2.468 0.014 0.399 0.581
ADT ~~
TR 0.638 0.107 5.963 0.000 0.525 0.525
.EEC ~~
.EEF 0.247 0.075 3.300 0.001 0.412 0.412
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEC1 0.789 0.094 8.430 0.000 0.789 0.464
.EEC2 0.477 0.104 4.569 0.000 0.477 0.240
.EEC3 0.201 0.063 3.202 0.001 0.201 0.111
.EEF1 0.237 0.045 5.302 0.000 0.237 0.170
.EEF2 0.191 0.046 4.138 0.000 0.191 0.132
.EEF3 0.248 0.064 3.885 0.000 0.248 0.189
.ADT1 0.244 0.057 4.278 0.000 0.244 0.223
.ADT2 0.217 0.054 4.030 0.000 0.217 0.194
.ADT3 0.323 0.089 3.621 0.000 0.323 0.226
.TR1 0.479 0.084 5.719 0.000 0.479 0.217
.TR2 0.257 0.067 3.816 0.000 0.257 0.111
.TR3 0.349 0.089 3.943 0.000 0.349 0.155
.IM1 -0.003 0.133 -0.024 0.981 -0.003 -0.002
.IM2 0.575 0.172 3.346 0.001 0.575 0.469
.IM3 0.821 0.229 3.586 0.000 0.821 0.585
.EEC 0.601 0.097 6.200 0.000 0.660 0.660
.EEF 0.599 0.126 4.749 0.000 0.515 0.515
ADT 0.852 0.125 6.808 0.000 1.000 1.000
TR 1.734 0.173 10.028 0.000 1.000 1.000
.IM 1.106 0.173 6.396 0.000 0.738 0.738
R-Square:
Estimate
EEC1 0.536
EEC2 0.760
EEC3 0.889
EEF1 0.830
EEF2 0.868
EEF3 0.811
ADT1 0.777
ADT2 0.806
ADT3 0.774
TR1 0.783
TR2 0.889
TR3 0.845
IM1 NA
IM2 0.531
IM3 0.415
EEC 0.340
EEF 0.485
IM 0.262With PEB control
TR moderation - with control variablelavaan 0.6-21 ended normally after 70 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 66
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 572.694 566.356
Degrees of freedom 234 234
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.011
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3293.815 2909.032
Degrees of freedom 285 285
P-value 0.000 0.000
Scaling correction factor 1.132
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.887 0.873
Tucker-Lewis Index (TLI) 0.863 0.846
Robust Comparative Fit Index (CFI) 0.887
Robust Tucker-Lewis Index (TLI) 0.862
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3858.619 -3858.619
Scaling correction factor 1.597
for the MLR correction
Loglikelihood unrestricted model (H1) -3572.272 -3572.272
Scaling correction factor 1.140
for the MLR correction
Akaike (AIC) 7849.238 7849.238
Bayesian (BIC) 8070.773 8070.773
Sample-size adjusted Bayesian (SABIC) 7861.641 7861.641
Root Mean Square Error of Approximation:
RMSEA 0.083 0.082
90 Percent confidence interval - lower 0.074 0.073
90 Percent confidence interval - upper 0.091 0.090
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.700 0.647
Robust RMSEA 0.082
90 Percent confidence interval - lower 0.074
90 Percent confidence interval - upper 0.091
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.677
Standardized Root Mean Square Residual:
SRMR 0.114 0.114
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EEC =~
EEC1 1.000 0.950 0.731
EEC2 1.285 0.110 11.685 0.000 1.221 0.870
EEC3 1.327 0.093 14.302 0.000 1.261 0.942
EEF =~
EEF1 1.000 1.068 0.910
EEF2 1.040 0.052 19.991 0.000 1.110 0.930
EEF3 0.954 0.056 17.084 0.000 1.019 0.899
ADT =~
ADT1 1.000 0.923 0.882
ADT2 1.028 0.068 15.126 0.000 0.949 0.897
ADT3 1.141 0.076 15.047 0.000 1.054 0.880
TR =~
TR1 1.000 1.317 0.885
TR2 1.090 0.049 22.291 0.000 1.435 0.943
TR3 1.047 0.050 21.072 0.000 1.378 0.919
IM =~
IM1 1.000 1.165 0.972
IM2 0.700 0.104 6.703 0.000 0.815 0.743
IM3 0.667 0.120 5.543 0.000 0.777 0.660
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
reward1_eco1 0.296 0.268 1.103 0.270 0.254 0.092
reward0_eco2 0.435 0.292 1.488 0.137 0.373 0.140
reward1_eco2 0.414 0.316 1.312 0.189 0.356 0.130
reward0_eco3 0.214 0.366 0.585 0.559 0.184 0.069
reward1_eco3 0.171 0.283 0.605 0.545 0.147 0.055
reward1_ec1_TR -0.219 0.324 -0.675 0.500 -0.188 -0.050
reward0_ec2_TR -0.469 0.392 -1.196 0.232 -0.403 -0.100
reward1_ec2_TR -0.190 0.365 -0.521 0.603 -0.163 -0.041
reward0_ec3_TR -0.402 0.460 -0.874 0.382 -0.345 -0.094
reward1_ec3_TR -0.604 0.343 -1.761 0.078 -0.519 -0.129
PEB_yes 1.047 0.173 6.057 0.000 0.899 0.384
TR 0.195 0.092 2.128 0.033 0.221 0.221
ADT 0.367 0.098 3.758 0.000 0.291 0.291
EEF ~
IM 0.511 0.082 6.231 0.000 0.558 0.558
reward1_eco1 0.232 0.183 1.267 0.205 0.217 0.079
reward0_eco2 -0.101 0.197 -0.513 0.608 -0.094 -0.035
reward1_eco2 0.208 0.178 1.165 0.244 0.194 0.071
reward0_eco3 -0.171 0.170 -1.004 0.315 -0.160 -0.060
reward1_eco3 -0.010 0.178 -0.058 0.954 -0.010 -0.004
TR_high_num 0.265 0.210 1.260 0.208 0.248 0.123
PEB_yes 0.377 0.167 2.253 0.024 0.353 0.151
TR -0.045 0.088 -0.516 0.606 -0.056 -0.056
ADT 0.212 0.080 2.649 0.008 0.183 0.183
EEC ~
IM 0.349 0.090 3.870 0.000 0.428 0.428
reward1_eco1 0.234 0.213 1.100 0.272 0.246 0.089
reward0_eco2 0.193 0.218 0.888 0.374 0.204 0.076
reward1_eco2 0.331 0.192 1.722 0.085 0.349 0.128
reward0_eco3 0.083 0.174 0.478 0.633 0.088 0.033
reward1_eco3 0.044 0.196 0.224 0.823 0.046 0.017
TR_high_num 0.280 0.222 1.259 0.208 0.294 0.146
PEB_yes 0.205 0.162 1.267 0.205 0.216 0.092
TR -0.033 0.097 -0.341 0.733 -0.046 -0.046
ADT 0.216 0.082 2.639 0.008 0.210 0.210
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.362 0.159 2.276 0.023 0.362 0.557
ADT ~~
TR 0.638 0.107 5.969 0.000 0.525 0.525
.EEC ~~
.EEF 0.220 0.067 3.281 0.001 0.387 0.387
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEC1 0.787 0.093 8.424 0.000 0.787 0.466
.EEC2 0.478 0.104 4.593 0.000 0.478 0.243
.EEC3 0.202 0.063 3.212 0.001 0.202 0.113
.EEF1 0.235 0.045 5.282 0.000 0.235 0.171
.EEF2 0.193 0.045 4.323 0.000 0.193 0.135
.EEF3 0.248 0.064 3.895 0.000 0.248 0.193
.ADT1 0.243 0.056 4.333 0.000 0.243 0.222
.ADT2 0.218 0.054 4.048 0.000 0.218 0.195
.ADT3 0.323 0.088 3.669 0.000 0.323 0.225
.TR1 0.480 0.084 5.707 0.000 0.480 0.217
.TR2 0.255 0.068 3.764 0.000 0.255 0.110
.TR3 0.351 0.088 3.994 0.000 0.351 0.156
.IM1 0.078 0.102 0.761 0.446 0.078 0.054
.IM2 0.540 0.167 3.223 0.001 0.540 0.448
.IM3 0.782 0.232 3.377 0.001 0.782 0.564
.EEC 0.586 0.094 6.225 0.000 0.649 0.649
.EEF 0.554 0.109 5.065 0.000 0.486 0.486
ADT 0.852 0.125 6.840 0.000 1.000 1.000
TR 1.733 0.173 10.023 0.000 1.000 1.000
.IM 0.840 0.151 5.550 0.000 0.619 0.619
R-Square:
Estimate
EEC1 0.534
EEC2 0.757
EEC3 0.887
EEF1 0.829
EEF2 0.865
EEF3 0.807
ADT1 0.778
ADT2 0.805
ADT3 0.775
TR1 0.783
TR2 0.890
TR3 0.844
IM1 0.946
IM2 0.552
IM3 0.436
EEC 0.351
EEF 0.514
IM 0.381ADT
Without control
ADT moderation using the dichotomized moderatorlavaan 0.6-21 ended normally after 80 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 63
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 513.266 503.036
Degrees of freedom 222 222
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.020
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3186.952 2780.405
Degrees of freedom 270 270
P-value 0.000 0.000
Scaling correction factor 1.146
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.900 0.888
Tucker-Lewis Index (TLI) 0.879 0.864
Robust Comparative Fit Index (CFI) 0.900
Robust Tucker-Lewis Index (TLI) 0.879
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3882.337 -3882.337
Scaling correction factor 1.624
for the MLR correction
Loglikelihood unrestricted model (H1) -3625.704 -3625.704
Scaling correction factor 1.154
for the MLR correction
Akaike (AIC) 7890.674 7890.674
Bayesian (BIC) 8102.139 8102.139
Sample-size adjusted Bayesian (SABIC) 7902.513 7902.513
Root Mean Square Error of Approximation:
RMSEA 0.079 0.077
90 Percent confidence interval - lower 0.070 0.068
90 Percent confidence interval - upper 0.088 0.086
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.411 0.314
Robust RMSEA 0.078
90 Percent confidence interval - lower 0.069
90 Percent confidence interval - upper 0.087
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.370
Standardized Root Mean Square Residual:
SRMR 0.114 0.114
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EEC =~
EEC1 1.000 0.945 0.729
EEC2 1.287 0.111 11.636 0.000 1.217 0.870
EEC3 1.329 0.093 14.331 0.000 1.256 0.942
EEF =~
EEF1 1.000 1.081 0.912
EEF2 1.041 0.054 19.251 0.000 1.125 0.932
EEF3 0.955 0.056 16.967 0.000 1.033 0.901
ADT =~
ADT1 1.000 0.922 0.881
ADT2 1.029 0.069 14.943 0.000 0.949 0.897
ADT3 1.144 0.077 14.853 0.000 1.055 0.881
TR =~
TR1 1.000 1.318 0.886
TR2 1.086 0.048 22.568 0.000 1.431 0.941
TR3 1.048 0.050 20.847 0.000 1.381 0.921
IM =~
IM1 1.000 1.186 0.992
IM2 0.671 0.113 5.926 0.000 0.796 0.727
IM3 0.637 0.124 5.133 0.000 0.755 0.643
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
reward1_eco1 0.028 0.353 0.079 0.937 0.024 0.009
reward0_eco2 0.434 0.388 1.119 0.263 0.366 0.137
reward1_eco2 0.461 0.304 1.513 0.130 0.388 0.142
reward0_eco3 -0.189 0.371 -0.508 0.612 -0.159 -0.060
reward1_eco3 -0.072 0.365 -0.198 0.843 -0.061 -0.023
reward1_c1_ADT 0.079 0.379 0.207 0.836 0.066 0.020
reward0_c2_ADT -0.404 0.446 -0.906 0.365 -0.341 -0.104
reward1_c2_ADT -0.622 0.403 -1.542 0.123 -0.524 -0.126
reward0_c3_ADT 0.138 0.516 0.267 0.789 0.116 0.029
reward1_c3_ADT -0.275 0.380 -0.724 0.469 -0.232 -0.065
TR 0.121 0.062 1.937 0.053 0.134 0.134
ADT 0.464 0.160 2.895 0.004 0.361 0.361
EEF ~
IM 0.540 0.086 6.286 0.000 0.593 0.593
reward1_eco1 0.205 0.180 1.135 0.257 0.189 0.069
reward0_eco2 -0.113 0.202 -0.559 0.576 -0.105 -0.039
reward1_eco2 0.221 0.181 1.217 0.224 0.204 0.075
reward0_eco3 -0.179 0.172 -1.044 0.296 -0.166 -0.062
reward1_eco3 -0.061 0.177 -0.343 0.732 -0.056 -0.021
ADT_high_num 0.125 0.206 0.605 0.545 0.115 0.058
TR 0.058 0.058 0.990 0.322 0.071 0.071
ADT 0.128 0.136 0.948 0.343 0.110 0.110
EEC ~
IM 0.359 0.080 4.495 0.000 0.451 0.451
reward1_eco1 0.209 0.208 1.004 0.315 0.221 0.080
reward0_eco2 0.185 0.213 0.869 0.385 0.196 0.074
reward1_eco2 0.374 0.195 1.922 0.055 0.396 0.145
reward0_eco3 0.115 0.184 0.624 0.532 0.122 0.046
reward1_eco3 0.012 0.194 0.061 0.952 0.012 0.005
ADT_high_num 0.259 0.188 1.379 0.168 0.274 0.137
TR 0.078 0.056 1.388 0.165 0.109 0.109
ADT 0.075 0.118 0.637 0.524 0.073 0.073
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.388 0.166 2.334 0.020 0.388 0.574
ADT ~~
TR 0.639 0.107 5.957 0.000 0.526 0.526
.EEC ~~
.EEF 0.245 0.074 3.314 0.001 0.411 0.411
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEC1 0.789 0.094 8.428 0.000 0.789 0.469
.EEC2 0.477 0.104 4.591 0.000 0.477 0.243
.EEC3 0.201 0.063 3.201 0.001 0.201 0.113
.EEF1 0.238 0.045 5.322 0.000 0.238 0.169
.EEF2 0.191 0.046 4.126 0.000 0.191 0.131
.EEF3 0.247 0.064 3.868 0.000 0.247 0.188
.ADT1 0.245 0.057 4.307 0.000 0.245 0.224
.ADT2 0.219 0.055 4.008 0.000 0.219 0.196
.ADT3 0.320 0.089 3.582 0.000 0.320 0.223
.TR1 0.476 0.083 5.707 0.000 0.476 0.215
.TR2 0.267 0.068 3.935 0.000 0.267 0.115
.TR3 0.342 0.088 3.881 0.000 0.342 0.152
.IM1 0.022 0.133 0.168 0.867 0.022 0.016
.IM2 0.564 0.177 3.196 0.001 0.564 0.471
.IM3 0.810 0.233 3.476 0.001 0.810 0.587
.EEC 0.599 0.097 6.148 0.000 0.671 0.671
.EEF 0.595 0.125 4.743 0.000 0.509 0.509
ADT 0.850 0.126 6.769 0.000 1.000 1.000
TR 1.737 0.173 10.052 0.000 1.000 1.000
.IM 1.076 0.174 6.185 0.000 0.765 0.765
R-Square:
Estimate
EEC1 0.531
EEC2 0.757
EEC3 0.887
EEF1 0.831
EEF2 0.869
EEF3 0.812
ADT1 0.776
ADT2 0.804
ADT3 0.777
TR1 0.785
TR2 0.885
TR3 0.848
IM1 0.984
IM2 0.529
IM3 0.413
EEC 0.329
EEF 0.491
IM 0.235With PEB control
ADT moderation - with control variablelavaan 0.6-21 ended normally after 73 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 66
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 528.340 518.059
Degrees of freedom 234 234
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.020
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3251.533 2847.514
Degrees of freedom 285 285
P-value 0.000 0.000
Scaling correction factor 1.142
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.901 0.889
Tucker-Lewis Index (TLI) 0.879 0.865
Robust Comparative Fit Index (CFI) 0.901
Robust Tucker-Lewis Index (TLI) 0.879
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3857.583 -3857.583
Scaling correction factor 1.608
for the MLR correction
Loglikelihood unrestricted model (H1) -3593.413 -3593.413
Scaling correction factor 1.149
for the MLR correction
Akaike (AIC) 7847.166 7847.166
Bayesian (BIC) 8068.701 8068.701
Sample-size adjusted Bayesian (SABIC) 7859.569 7859.569
Root Mean Square Error of Approximation:
RMSEA 0.077 0.076
90 Percent confidence interval - lower 0.068 0.067
90 Percent confidence interval - upper 0.086 0.084
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.295 0.211
Robust RMSEA 0.076
90 Percent confidence interval - lower 0.068
90 Percent confidence interval - upper 0.085
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.259
Standardized Root Mean Square Residual:
SRMR 0.109 0.109
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
EEC =~
EEC1 1.000 0.938 0.726
EEC2 1.286 0.110 11.665 0.000 1.206 0.868
EEC3 1.328 0.092 14.365 0.000 1.245 0.941
EEF =~
EEF1 1.000 1.061 0.909
EEF2 1.040 0.052 19.992 0.000 1.104 0.929
EEF3 0.955 0.056 17.054 0.000 1.013 0.898
ADT =~
ADT1 1.000 0.922 0.880
ADT2 1.030 0.068 15.087 0.000 0.950 0.898
ADT3 1.144 0.077 14.935 0.000 1.055 0.881
TR =~
TR1 1.000 1.318 0.886
TR2 1.086 0.048 22.519 0.000 1.432 0.941
TR3 1.047 0.050 20.903 0.000 1.380 0.920
IM =~
IM1 1.000 1.110 0.956
IM2 0.721 0.106 6.811 0.000 0.800 0.743
IM3 0.689 0.123 5.582 0.000 0.765 0.659
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
reward1_eco1 0.012 0.352 0.034 0.973 0.011 0.004
reward0_eco2 0.355 0.392 0.905 0.365 0.320 0.120
reward1_eco2 0.568 0.286 1.985 0.047 0.511 0.188
reward0_eco3 -0.142 0.350 -0.406 0.685 -0.128 -0.048
reward1_eco3 0.041 0.304 0.136 0.892 0.037 0.014
reward1_c1_ADT 0.306 0.359 0.851 0.395 0.276 0.084
reward0_c2_ADT -0.173 0.426 -0.406 0.685 -0.156 -0.047
reward1_c2_ADT -0.608 0.353 -1.720 0.085 -0.548 -0.131
reward0_c3_ADT 0.414 0.459 0.902 0.367 0.373 0.093
reward1_c3_ADT -0.227 0.316 -0.718 0.473 -0.205 -0.057
PEB_yes 1.066 0.169 6.303 0.000 0.960 0.411
TR 0.096 0.053 1.809 0.070 0.114 0.114
ADT 0.379 0.145 2.623 0.009 0.315 0.315
EEF ~
IM 0.522 0.086 6.093 0.000 0.546 0.546
reward1_eco1 0.215 0.183 1.174 0.240 0.203 0.073
reward0_eco2 -0.111 0.193 -0.576 0.564 -0.105 -0.039
reward1_eco2 0.227 0.181 1.253 0.210 0.214 0.079
reward0_eco3 -0.134 0.171 -0.785 0.432 -0.126 -0.047
reward1_eco3 -0.013 0.177 -0.075 0.940 -0.013 -0.005
ADT_high_num 0.136 0.199 0.683 0.494 0.128 0.064
PEB_yes 0.355 0.171 2.072 0.038 0.335 0.143
TR 0.050 0.055 0.915 0.360 0.062 0.062
ADT 0.138 0.128 1.084 0.278 0.120 0.120
EEC ~
IM 0.350 0.088 3.972 0.000 0.414 0.414
reward1_eco1 0.212 0.211 1.005 0.315 0.227 0.082
reward0_eco2 0.186 0.216 0.858 0.391 0.198 0.074
reward1_eco2 0.375 0.201 1.867 0.062 0.400 0.147
reward0_eco3 0.140 0.184 0.759 0.448 0.149 0.056
reward1_eco3 0.039 0.195 0.201 0.841 0.042 0.016
ADT_high_num 0.263 0.185 1.422 0.155 0.280 0.140
PEB_yes 0.198 0.162 1.221 0.222 0.211 0.090
TR 0.073 0.056 1.319 0.187 0.103 0.103
ADT 0.083 0.119 0.701 0.483 0.082 0.082
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.342 0.164 2.087 0.037 0.342 0.543
ADT ~~
TR 0.638 0.107 5.958 0.000 0.525 0.525
.EEC ~~
.EEF 0.221 0.067 3.316 0.001 0.388 0.388
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEC1 0.788 0.093 8.429 0.000 0.788 0.473
.EEC2 0.477 0.103 4.619 0.000 0.477 0.247
.EEC3 0.201 0.063 3.207 0.001 0.201 0.115
.EEF1 0.236 0.044 5.303 0.000 0.236 0.173
.EEF2 0.192 0.045 4.310 0.000 0.192 0.136
.EEF3 0.247 0.064 3.877 0.000 0.247 0.194
.ADT1 0.246 0.056 4.362 0.000 0.246 0.225
.ADT2 0.217 0.054 4.000 0.000 0.217 0.194
.ADT3 0.320 0.088 3.625 0.000 0.320 0.224
.TR1 0.476 0.083 5.703 0.000 0.476 0.215
.TR2 0.265 0.068 3.896 0.000 0.265 0.114
.TR3 0.344 0.088 3.926 0.000 0.344 0.153
.IM1 0.116 0.100 1.153 0.249 0.116 0.086
.IM2 0.521 0.172 3.028 0.002 0.521 0.448
.IM3 0.762 0.237 3.210 0.001 0.762 0.566
.EEC 0.586 0.095 6.161 0.000 0.667 0.667
.EEF 0.551 0.108 5.086 0.000 0.490 0.490
ADT 0.849 0.125 6.790 0.000 1.000 1.000
TR 1.737 0.173 10.054 0.000 1.000 1.000
.IM 0.795 0.153 5.196 0.000 0.646 0.646
R-Square:
Estimate
EEC1 0.527
EEC2 0.753
EEC3 0.885
EEF1 0.827
EEF2 0.864
EEF3 0.806
ADT1 0.775
ADT2 0.806
ADT3 0.776
TR1 0.785
TR2 0.886
TR3 0.847
IM1 0.914
IM2 0.552
IM3 0.434
EEC 0.333
EEF 0.510
IM 0.354