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 controls
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 model1
Allowing covariance between IM2 and IM3lavaan 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 0.000Modified measurement model2
Allowing covariance between IM2 ~~ IM3 and EEC1 ~~ EEC2lavaan 0.6-21 ended normally after 37 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 23
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 45.694 39.827
Degrees of freedom 22 22
P-value (Chi-square) 0.002 0.011
Scaling correction factor 1.147
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) 0.985 0.979
Tucker-Lewis Index (TLI) 0.975 0.966
Robust Comparative Fit Index (CFI) 0.986
Robust Tucker-Lewis Index (TLI) 0.978
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2330.232 -2330.232
Scaling correction factor 2.252
for the MLR correction
Loglikelihood unrestricted model (H1) -2307.385 -2307.385
Scaling correction factor 1.712
for the MLR correction
Akaike (AIC) 4706.463 4706.463
Bayesian (BIC) 4783.664 4783.664
Sample-size adjusted Bayesian (SABIC) 4710.785 4710.785
Root Mean Square Error of Approximation:
RMSEA 0.071 0.062
90 Percent confidence interval - lower 0.042 0.032
90 Percent confidence interval - upper 0.100 0.090
P-value H_0: RMSEA <= 0.050 0.109 0.230
P-value H_0: RMSEA >= 0.080 0.335 0.155
Robust RMSEA 0.066
90 Percent confidence interval - lower 0.031
90 Percent confidence interval - upper 0.099
P-value H_0: Robust RMSEA <= 0.050 0.193
P-value H_0: Robust RMSEA >= 0.080 0.263
Standardized Root Mean Square Residual:
SRMR 0.036 0.036
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 1.255 0.103 12.169 0.000 1.053 1.457
EEC3 1.164 0.100 11.602 0.000 0.968 1.361
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.046 0.054 19.429 0.000 0.940 1.151
EEF3 0.957 0.055 17.334 0.000 0.849 1.065
IM =~
IM1 1.000 1.000 1.000
IM2 0.705 0.098 7.217 0.000 0.514 0.896
IM3 0.671 0.108 6.192 0.000 0.459 0.884
Std.lv Std.all
1.049 0.798
1.316 0.923
1.221 0.895
1.084 0.910
1.133 0.935
1.038 0.902
1.128 0.967
0.796 0.736
0.757 0.651
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.358 0.154 2.322 0.020 0.056 0.660
.EEC1 ~~
.EEC2 -0.252 0.073 -3.447 0.001 -0.395 -0.109
EEC ~~
EEF 0.741 0.125 5.913 0.000 0.496 0.987
IM 0.673 0.116 5.810 0.000 0.446 0.900
EEF ~~
IM 0.834 0.131 6.373 0.000 0.578 1.091
Std.lv Std.all
0.358 0.555
-0.252 -0.578
0.652 0.652
0.568 0.568
0.682 0.682
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.629 0.120 5.234 0.000 0.394 0.865
.EEC2 0.302 0.110 2.756 0.006 0.087 0.517
.EEC3 0.371 0.088 4.198 0.000 0.198 0.544
.EEF1 0.243 0.045 5.423 0.000 0.155 0.330
.EEF2 0.186 0.044 4.186 0.000 0.099 0.273
.EEF3 0.248 0.065 3.830 0.000 0.121 0.375
.IM1 0.087 0.086 1.019 0.308 -0.081 0.256
.IM2 0.535 0.165 3.248 0.001 0.212 0.858
.IM3 0.779 0.228 3.419 0.001 0.333 1.226
EEC 1.100 0.168 6.559 0.000 0.772 1.429
EEF 1.175 0.187 6.271 0.000 0.808 1.543
IM 1.273 0.191 6.674 0.000 0.899 1.647
Std.lv Std.all
0.629 0.364
0.302 0.148
0.371 0.199
0.243 0.171
0.186 0.126
0.248 0.187
0.087 0.064
0.535 0.458
0.779 0.576
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.636
EEC2 0.852
EEC3 0.801
EEF1 0.829
EEF2 0.874
EEF3 0.813
IM1 0.936
IM2 0.542
IM3 0.424Cronbach’s Alpha: EEC EEF IM
0.882 0.940 0.874 Omega: EEC EEF IM
0.943 0.940 0.773 Average Variance Extracted (AVE): EEC EEF IM
0.769 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"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.018 0.011 0.000
EEF1 0.055 -0.081 -0.015 0.000
EEF2 0.062 -0.014 0.012 0.002 0.000
EEF3 0.063 -0.032 0.036 0.011 -0.011 0.000
IM1 0.028 -0.014 -0.015 -0.040 0.028 0.004 0.000
IM2 0.093 -0.045 -0.091 -0.102 0.034 0.023 0.001 0.000
IM3 0.247 0.007 0.010 -0.077 0.032 0.076 -0.003 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.547 0.490 0.000
EEF1 0.987 -1.614 -0.434 0.000
EEF2 1.206 -0.350 0.386 0.159 0.000
EEF3 1.138 -0.712 0.873 0.738 -0.956 0.000
IM1 0.484 -0.409 -0.501 -1.576 0.924 0.164 0.000
IM2 1.497 -0.931 -2.112 -2.681 0.955 0.648 0.047 0.000
IM3 2.183 0.083 0.143 -1.494 0.603 1.825 -0.143 0.000 0.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC
IM "1" "0.68 (0)" "0.57 (0)"
EEF "0.68 (0)" "1" "0.65 (0)"
EEC "0.57 (0)" "0.65 (0)" "1" Discriminant validity check lhs op rhs est.std se z pvalue ci.lower ci.upper
1 EEC =~ EEC1 0.798 0.044 18.305 0 0.712 0.883
2 EEC =~ EEC2 0.923 0.030 31.201 0 0.865 0.981
3 EEC =~ EEC3 0.895 0.028 31.695 0 0.840 0.950
4 EEF =~ EEF1 0.910 0.019 47.758 0 0.873 0.948
5 EEF =~ EEF2 0.935 0.017 53.632 0 0.900 0.969
6 EEF =~ EEF3 0.902 0.030 30.046 0 0.843 0.960
7 IM =~ IM1 0.967 0.034 28.828 0 0.902 1.033
8 IM =~ IM2 0.736 0.079 9.309 0 0.581 0.891
9 IM =~ IM3 0.651 0.097 6.726 0 0.461 0.841AVE (IM, EEF, EEC)[1] 0.6339121[1] 0.8384162[1] 0.7628828Square root of AVE (IM, EEF, EEC)[1] 0.796186[1] 0.9156507[1] 0.8734316 lhs rhs est.std
24 EEC EEF 0.652
25 EEC IM 0.568
26 EEF IM 0.682Correlations between square root AVE with correlations (sqrt vs. correlations with the other constructsIM[1] 0.796186[1] 0.6820438[1] 0.5683634EEF[1] 0.9156507[1] 0.6820438[1] 0.6517554EEC[1] 0.8734316[1] 0.5683634[1] 0.6517554With controls
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 $type
[1] "cor.bentler"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.000 0.000
IM3 0.000 0.000 0.000
EEF1 -0.031 -0.059 -0.036 0.000
EEF2 0.020 0.048 0.044 0.001 0.000
EEF3 0.002 0.039 0.077 0.006 -0.006 0.000
EEC1 0.064 0.115 0.206 0.076 0.083 0.083 0.000
EEC2 0.035 0.020 0.049 -0.011 0.031 0.017 -0.040 0.000
EEC3 -0.024 -0.054 0.014 -0.035 -0.018 -0.002 0.005 0.005 0.000
TR1 0.041 0.030 0.042 0.042 0.026 0.046 0.092 0.051 0.076 0.000
TR2 -0.010 -0.053 -0.055 -0.041 -0.050 -0.008 -0.042 -0.062 -0.025 0.001
TR3 -0.012 -0.043 -0.021 0.025 0.003 0.051 0.026 -0.040 0.010 -0.008
ADT1 0.045 -0.059 -0.047 0.064 0.053 0.022 0.060 0.028 0.042 0.052
ADT2 -0.073 -0.150 -0.137 -0.043 -0.072 -0.068 -0.010 -0.052 -0.049 0.017
ADT3 0.047 -0.008 -0.012 0.048 0.021 0.002 0.053 0.031 -0.001 0.035
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 -0.030 -0.018 0.003 0.000
ADT3 -0.040 0.032 -0.014 0.008 0.000
$cov.z
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 0.000
$summary
cov
srmr 0.047
srmr.se 0.009
srmr.exactfit.z 0.589
srmr.exactfit.pvalue 0.278
usrmr 0.020
usrmr.se 0.011
usrmr.ci.lower 0.003
usrmr.ci.upper 0.037
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -2.838
usrmr.closefit.pvalue 0.998 IM EEF EEC TR ADT
IM 1.000
EEF 0.666 1.000
EEC 0.538 0.643 1.000
TR 0.297 0.321 0.316 1.000
ADT 0.381 0.415 0.405 0.526 1.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC TR ADT
IM "1" "0.67 (0)" "0.54 (0)" "0.3 (0)" "0.38 (0)"
EEF "0.67 (0)" "1" "0.64 (0)" "0.32 (0)" "0.42 (0)"
EEC "0.54 (0)" "0.64 (0)" "1" "0.32 (0)" "0.41 (0)"
TR "0.3 (0)" "0.32 (0)" "0.32 (0)" "1" "0.53 (0)"
ADT "0.38 (0)" "0.42 (0)" "0.41 (0)" "0.53 (0)" "1" Details
Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
57 IM =~ ADT2 12.251 -0.137 -0.158 -0.150 -0.150
69 EEF =~ ADT2 10.153 -0.139 -0.151 -0.143 -0.143Residuals[1] lhs op rhs mi epc sepc.lv sepc.all sepc.nox
<0 rows> (or 0-length row.names)$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 0.000Modified 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 control variables
No moderation - without PEB control variablelavaan 0.6-21 ended normally after 66 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 50
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 237.793 223.579
Degrees of freedom 145 145
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.064
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) 0.965 0.963
Tucker-Lewis Index (TLI) 0.957 0.954
Robust Comparative Fit Index (CFI) 0.968
Robust Tucker-Lewis Index (TLI) 0.961
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3910.777 -3910.777
Scaling correction factor 1.776
for the MLR correction
Loglikelihood unrestricted model (H1) -3791.881 -3791.881
Scaling correction factor 1.246
for the MLR correction
Akaike (AIC) 7921.554 7921.554
Bayesian (BIC) 8089.384 8089.384
Sample-size adjusted Bayesian (SABIC) 7930.950 7930.950
Root Mean Square Error of Approximation:
RMSEA 0.055 0.051
90 Percent confidence interval - lower 0.042 0.037
90 Percent confidence interval - upper 0.067 0.063
P-value H_0: RMSEA <= 0.050 0.251 0.458
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.052
90 Percent confidence interval - lower 0.038
90 Percent confidence interval - upper 0.065
P-value H_0: Robust RMSEA <= 0.050 0.384
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.146 0.146
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
TR =~
TR1 1.000 1.315 0.884
TR2 1.090 0.048 22.674 0.000 1.434 0.942
TR3 1.049 0.050 21.146 0.000 1.380 0.920
ADT =~
ADT1 1.000 0.916 0.875
ADT2 1.047 0.069 15.102 0.000 0.960 0.907
ADT3 1.145 0.074 15.390 0.000 1.049 0.876
IM =~
IM1 1.000 1.138 0.975
IM2 0.694 0.104 6.664 0.000 0.789 0.730
IM3 0.660 0.115 5.718 0.000 0.751 0.645
EEF =~
EEF1 1.000 1.085 0.911
EEF2 1.044 0.054 19.440 0.000 1.132 0.934
EEF3 0.957 0.055 17.395 0.000 1.038 0.902
EEC =~
EEC1 1.000 0.970 0.738
EEC2 1.287 0.111 11.618 0.000 1.249 0.875
EEC3 1.328 0.093 14.298 0.000 1.288 0.944
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.163 0.266 0.612 0.540 0.143 0.052
rwrd0_2 (b_02) 0.240 0.265 0.905 0.365 0.211 0.079
rwrd1_2 (b_12) 0.189 0.269 0.705 0.481 0.167 0.061
rwrd0_3 (b_03) -0.159 0.300 -0.532 0.595 -0.140 -0.053
rwrd1_3 (b_13) -0.277 0.267 -1.038 0.299 -0.244 -0.091
EEF ~
rwrd1_1 (c_11) 0.216 0.182 1.192 0.233 0.200 0.072
rwrd0_2 (c_02) -0.122 0.209 -0.583 0.560 -0.112 -0.042
rwrd1_2 (c_12) 0.152 0.187 0.813 0.416 0.140 0.051
rwrd0_3 (c_03) -0.194 0.178 -1.090 0.276 -0.179 -0.067
rwrd1_3 (c_13) -0.058 0.183 -0.317 0.751 -0.053 -0.020
IM (c_IM) 0.635 0.073 8.668 0.000 0.666 0.666
EEC ~
rwrd1_1 (d_11) 0.237 0.210 1.130 0.259 0.244 0.089
rwrd0_2 (d_02) 0.179 0.214 0.837 0.403 0.185 0.069
rwrd1_2 (d_12) 0.287 0.203 1.414 0.157 0.296 0.108
rwrd0_3 (d_03) 0.080 0.183 0.437 0.662 0.082 0.031
rwrd1_3 (d_13) 0.011 0.214 0.052 0.958 0.011 0.004
IM (d_IM) 0.456 0.071 6.444 0.000 0.534 0.534
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.368 0.153 2.404 0.016 0.368 0.561
TR ~~
ADT 0.631 0.106 5.935 0.000 0.523 0.523
.EEF ~~
.EEC 0.280 0.077 3.623 0.000 0.444 0.444
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.483 0.083 5.824 0.000 0.483 0.218
.TR2 0.259 0.067 3.850 0.000 0.259 0.112
.TR3 0.345 0.087 3.940 0.000 0.345 0.153
.ADT1 0.256 0.057 4.456 0.000 0.256 0.234
.ADT2 0.198 0.052 3.837 0.000 0.198 0.177
.ADT3 0.332 0.090 3.696 0.000 0.332 0.232
.IM1 0.066 0.104 0.636 0.525 0.066 0.049
.IM2 0.545 0.164 3.321 0.001 0.545 0.467
.IM3 0.789 0.228 3.458 0.001 0.789 0.584
.EEF1 0.241 0.045 5.326 0.000 0.241 0.170
.EEF2 0.188 0.046 4.130 0.000 0.188 0.128
.EEF3 0.247 0.063 3.893 0.000 0.247 0.187
.EEC1 0.789 0.094 8.393 0.000 0.789 0.456
.EEC2 0.475 0.105 4.543 0.000 0.475 0.234
.EEC3 0.203 0.063 3.229 0.001 0.203 0.109
TR 1.730 0.172 10.045 0.000 1.000 1.000
ADT 0.840 0.124 6.748 0.000 1.000 1.000
.IM 1.258 0.212 5.937 0.000 0.972 0.972
.EEF 0.617 0.128 4.833 0.000 0.524 0.524
.EEC 0.646 0.106 6.105 0.000 0.686 0.686
R-Square:
Estimate
TR1 0.782
TR2 0.888
TR3 0.847
ADT1 0.766
ADT2 0.823
ADT3 0.768
IM1 0.951
IM2 0.533
IM3 0.416
EEF1 0.830
EEF2 0.872
EEF3 0.813
EEC1 0.544
EEC2 0.766
EEC3 0.891
IM 0.028
EEF 0.476
EEC 0.314With control variables
All three (TR, ADT, PEB)
With control all three controlslavaan 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
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
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
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
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
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
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
TR ~~
ADT 0.639 0.107 5.975 0.000 0.525 0.525
.EEF ~~
.EEC 0.222 0.068 3.283 0.001 0.388 0.388
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.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
.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
.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
.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
.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
TR 1.736 0.173 10.049 0.000 1.000 1.000
ADT 0.851 0.125 6.833 0.000 1.000 1.000
.IM 0.837 0.151 5.554 0.000 0.682 0.682
.EEF 0.554 0.109 5.098 0.000 0.480 0.480
.EEC 0.590 0.094 6.242 0.000 0.637 0.637
R-Square:
Estimate
TR1 0.785
TR2 0.886
TR3 0.847
ADT1 0.777
ADT2 0.806
ADT3 0.775
IM1 0.923
IM2 0.541
IM3 0.425
EEF1 0.831
EEF2 0.867
EEF3 0.809
EEC1 0.540
EEC2 0.760
EEC3 0.893
IM 0.318
EEF 0.520
EEC 0.363
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
eco_main_IM 0.022 0.133 0.163 0.870 0.020 0.008
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 0.020
r_3_EEF___1_EE -0.243 0.196 -1.238 0.216 -0.226 -0.082
r_2_EEF___1_EE -0.016 0.197 -0.081 0.936 -0.015 -0.004
r_2_EEC___1_EE 0.106 0.203 0.521 0.602 0.110 0.041
r_3_EEC___2_EE -0.300 0.199 -1.506 0.132 -0.311 -0.114
r_3_EEC___1_EE -0.194 0.211 -0.916 0.360 -0.201 -0.072
rw_2_IM___1_IM 0.114 0.212 0.540 0.589 0.103 0.039
rw_3_IM___1_IM -0.290 0.207 -1.398 0.162 -0.261 -0.096
i__2_EEC___1_E 0.040 0.072 0.549 0.583 0.041 0.015
i__3_EEC___1_E -0.100 0.084 -1.190 0.234 -0.104 -0.038
i__3_EEC___2_E -0.140 0.090 -1.555 0.120 -0.145 -0.054
t__2_EEC___1_E 0.145 0.214 0.680 0.497 0.151 0.057
t__3_EEC___1_E -0.294 0.212 -1.385 0.166 -0.306 -0.111
t__3_EEC___2_E -0.439 0.209 -2.103 0.036 -0.457 -0.167Mediation analysis with bootstrapping=5000 lhs op
93 reward_main_EEF :=
97 ind_reward_main_IM_EEF :=
98 tot_reward_main_EEF :=
102 reward_main_EEC :=
106 ind_reward_main_IM_EEC :=
107 tot_reward_main_EEC :=
109 eco3_vs_eco1_EEF :=
110 eco1_vs_eco2_EEF :=
111 eco_main_EEF :=
112 eco2_vs_eco1_IM :=
113 eco3_vs_eco1_IM :=
114 eco1_vs_eco2_IM :=
115 ind_eco1_vs_eco2_IM_EEF :=
117 ind_eco3_vs_eco1_IM_EEF :=
118 ind_eco_main_IM_EEF :=
119 tot_eco1_vs_eco2_EEF :=
121 tot_eco3_vs_eco1_EEF :=
122 tot_eco_main_EEF :=
123 eco2_vs_eco1_EEC :=
124 eco3_vs_eco1_EEC :=
125 eco_main_EEC :=
126 ind_eco2_vs_eco1_IM_EEC :=
127 ind_eco3_vs_eco1_IM_EEC :=
128 ind_eco_main_IM_EEC :=
129 tot_eco2_vs_eco1_EEC :=
130 tot_eco3_vs_eco1_EEC :=
131 tot_eco_main_EEC :=
132 eco_main_IM :=
136 eco3_vs_eco2_EEC :=
137 ind_eco3_vs_eco2_IM_EEC :=
138 tot_eco3_vs_eco2_EEC :=
142 reward_main_IM :=
143 reward_eco3_EEF_vs_reward_eco1_EEF :=
144 reward_eco2_EEF_vs_reward_eco1_EEF :=
145 reward_eco2_EEC_vs_reward_eco1_EEC :=
146 reward_eco3_EEC_vs_reward_eco2_EEC :=
148 reward_eco2_IM_vs_reward_eco1_IM :=
149 reward_eco3_IM_vs_reward_eco1_IM :=
150 ind_reward_eco2_EEC_vs_reward_eco1_EEC :=
151 ind_reward_eco3_EEC_vs_reward_eco1_EEC :=
152 ind_reward_eco3_EEC_vs_reward_eco2_EEC :=
153 tot_reward_eco2_EEC_vs_reward_eco1_EEC :=
154 tot_reward_eco3_EEC_vs_reward_eco1_EEC :=
155 tot_reward_eco3_EEC_vs_reward_eco2_EEC :=
rhs
93 ((c_r1e1-0)+(c_r1e2-c_r0e2)+(c_r1e3-c_r0e3))/3
97 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3*c_IM
98 reward_main_EEF+ind_reward_main_IM_EEF
102 ((d_r1e1-0)+(d_r1e2-d_r0e2)+(d_r1e3-d_r0e3))/3
106 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3*d_IM
107 reward_main_EEC+ind_reward_main_IM_EEC
109 ((c_r0e3-0)+(c_r1e3-c_r1e1))/2
110 ((0-c_r0e2)+(c_r1e1-c_r1e2))/2
111 (eco2_vs_eco1_EEF+eco3_vs_eco1_EEF)/2
112 ((b_r0e2-0)+(b_r1e2-b_r1e1))/2
113 ((b_r0e3-0)+(b_r1e3-b_r1e1))/2
114 ((0-b_r0e2)+(b_r1e1-b_r1e2))/2
115 eco1_vs_eco2_IM*c_IM
117 eco3_vs_eco1_IM*c_IM
118 (ind_eco2_vs_eco1_IM_EEF+ind_eco3_vs_eco1_IM_EEF)/2
119 eco1_vs_eco2_EEF+ind_eco1_vs_eco2_IM_EEF
121 eco3_vs_eco1_EEF+ind_eco3_vs_eco1_IM_EEF
122 eco_main_EEF+ind_eco_main_IM_EEF
123 ((d_r0e2-0)+(d_r1e2-d_r1e1))/2
124 ((d_r0e3-0)+(d_r1e3-d_r1e1))/2
125 (eco2_vs_eco1_EEC+eco3_vs_eco1_EEC)/2
126 eco2_vs_eco1_IM*d_IM
127 eco3_vs_eco1_IM*d_IM
128 (ind_eco2_vs_eco1_IM_EEC+ind_eco3_vs_eco1_IM_EEC)/2
129 eco2_vs_eco1_EEC+ind_eco2_vs_eco1_IM_EEC
130 eco3_vs_eco1_EEC+ind_eco3_vs_eco1_IM_EEC
131 eco_main_EEC+ind_eco_main_IM_EEC
132 (eco2_vs_eco1_IM+eco3_vs_eco1_IM)/2
136 eco3_vs_eco1_EEC-eco2_vs_eco1_EEC
137 ind_eco3_vs_eco1_IM_EEC-ind_eco2_vs_eco1_IM_EEC
138 tot_eco3_vs_eco1_EEC-tot_eco2_vs_eco1_EEC
142 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3
143 c_r1e3-c_r1e1
144 c_r1e2-c_r1e1
145 d_r1e2-d_r1e1
146 d_r1e3-d_r1e2
148 b_r1e2-b_r1e1
149 b_r1e3-b_r1e1
150 (b_r1e2-b_r1e1)*d_IM
151 (b_r1e3-b_r1e1)*d_IM
152 (b_r1e3-b_r1e2)*d_IM
153 (d_r1e2-d_r1e1)+ind_reward_eco2_EEC_vs_reward_eco1_EEC
154 (d_r1e3-d_r1e1)+ind_reward_eco3_EEC_vs_reward_eco1_EEC
155 (d_r1e3-d_r1e2)+ind_reward_eco3_EEC_vs_reward_eco2_EEC
label est se z pvalue ci.lower
93 reward_main_EEF 0.230 0.123 1.873 0.061 -0.007
97 ind_reward_main_IM_EEF 0.033 0.069 0.481 0.630 -0.098
98 tot_reward_main_EEF 0.263 0.137 1.916 0.055 -0.005
102 reward_main_EEC 0.109 0.120 0.906 0.365 -0.124
106 ind_reward_main_IM_EEC 0.022 0.049 0.461 0.645 -0.064
107 tot_reward_main_EEC 0.131 0.126 1.038 0.299 -0.116
109 eco3_vs_eco1_EEF -0.198 0.138 -1.440 0.150 -0.478
110 eco1_vs_eco2_EEF 0.061 0.142 0.431 0.667 -0.214
111 eco_main_EEF -0.130 0.116 -1.117 0.264 -0.359
112 eco2_vs_eco1_IM 0.182 0.163 1.116 0.264 -0.164
113 eco3_vs_eco1_IM -0.138 0.166 -0.835 0.404 -0.486
114 eco1_vs_eco2_IM -0.182 0.163 -1.116 0.264 -0.469
115 ind_eco1_vs_eco2_IM_EEF -0.093 0.085 -1.092 0.275 -0.258
117 ind_eco3_vs_eco1_IM_EEF -0.071 0.092 -0.769 0.442 -0.282
118 ind_eco_main_IM_EEF 0.011 0.073 0.154 0.878 -0.145
119 tot_eco1_vs_eco2_EEF -0.032 0.157 -0.205 0.838 -0.350
121 tot_eco3_vs_eco1_EEF -0.269 0.157 -1.717 0.086 -0.585
122 tot_eco_main_EEF -0.119 0.128 -0.924 0.356 -0.381
123 eco2_vs_eco1_EEC 0.147 0.150 0.984 0.325 -0.139
124 eco3_vs_eco1_EEC -0.047 0.137 -0.341 0.733 -0.314
125 eco_main_EEC 0.050 0.125 0.403 0.687 -0.186
126 ind_eco2_vs_eco1_IM_EEC 0.063 0.058 1.083 0.279 -0.068
127 ind_eco3_vs_eco1_IM_EEC -0.048 0.068 -0.707 0.480 -0.206
128 ind_eco_main_IM_EEC 0.008 0.050 0.150 0.881 -0.114
129 tot_eco2_vs_eco1_EEC 0.210 0.163 1.286 0.198 -0.099
130 tot_eco3_vs_eco1_EEC -0.094 0.139 -0.678 0.498 -0.398
131 tot_eco_main_EEC 0.058 0.131 0.442 0.658 -0.199
132 eco_main_IM 0.022 0.137 0.158 0.874 -0.254
136 eco3_vs_eco2_EEC -0.194 0.141 -1.378 0.168 -0.458
137 ind_eco3_vs_eco2_IM_EEC -0.111 0.077 -1.443 0.149 -0.286
138 tot_eco3_vs_eco2_EEC -0.305 0.154 -1.972 0.049 -0.605
142 reward_main_IM 0.065 0.135 0.482 0.630 -0.203
143 reward_eco3_EEF_vs_reward_eco1_EEF -0.243 0.205 -1.188 0.235 -0.658
144 reward_eco2_EEF_vs_reward_eco1_EEF -0.016 0.204 -0.078 0.938 -0.419
145 reward_eco2_EEC_vs_reward_eco1_EEC 0.106 0.206 0.513 0.608 -0.259
146 reward_eco3_EEC_vs_reward_eco2_EEC -0.300 0.202 -1.486 0.137 -0.697
148 reward_eco2_IM_vs_reward_eco1_IM 0.114 0.218 0.523 0.601 -0.335
149 reward_eco3_IM_vs_reward_eco1_IM -0.290 0.211 -1.373 0.170 -0.698
150 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.040 0.076 0.522 0.602 -0.131
151 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.100 0.092 -1.084 0.278 -0.307
152 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.140 0.098 -1.426 0.154 -0.370
153 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.145 0.221 0.659 0.510 -0.283
154 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.294 0.210 -1.400 0.162 -0.719
155 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.439 0.210 -2.088 0.037 -0.858
ci.upper std.lv std.all std.nox
93 0.477 0.214 0.079 0.214
97 0.165 0.031 0.011 0.031
98 0.576 0.245 0.090 0.245
102 0.335 0.113 0.040 0.113
106 0.137 0.023 0.008 0.023
107 0.379 0.136 0.048 0.136
109 0.066 -0.184 -0.068 -0.184
110 0.338 0.057 0.021 0.057
111 0.098 -0.121 -0.044 -0.121
112 0.469 0.164 0.062 0.164
113 0.181 -0.125 -0.046 -0.125
114 0.164 -0.164 -0.062 -0.164
115 0.082 -0.087 -0.033 -0.087
117 0.087 -0.066 -0.024 -0.066
118 0.147 0.010 0.004 0.010
119 0.264 -0.030 -0.012 -0.030
121 0.015 -0.251 -0.092 -0.251
122 0.119 -0.110 -0.040 -0.110
123 0.449 0.153 0.058 0.153
124 0.238 -0.048 -0.017 -0.048
125 0.300 0.052 0.020 0.052
126 0.178 0.065 0.025 0.065
127 0.063 -0.050 -0.018 -0.050
128 0.097 0.008 0.003 0.008
129 0.540 0.218 0.082 0.218
130 0.168 -0.098 -0.035 -0.098
131 0.319 0.060 0.024 0.060
132 0.269 0.020 0.008 0.020
136 0.096 -0.201 -0.074 -0.201
137 0.022 -0.115 -0.043 -0.115
138 -0.020 -0.316 -0.117 -0.316
142 0.329 0.059 0.020 0.059
143 0.145 -0.226 -0.082 -0.226
144 0.397 -0.015 -0.004 -0.015
145 0.535 0.110 0.041 0.110
146 0.121 -0.311 -0.114 -0.311
148 0.550 0.103 0.039 0.103
149 0.105 -0.261 -0.096 -0.261
150 0.193 0.041 0.015 0.041
151 0.027 -0.104 -0.038 -0.104
152 0.039 -0.145 -0.054 -0.145
153 0.607 0.151 0.057 0.151
154 0.090 -0.306 -0.111 -0.306
155 -0.024 -0.457 -0.167 -0.457ADT, PEB
With control variableslavaan 0.6-21 ended normally after 57 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 49
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 146.437 135.187
Degrees of freedom 101 101
P-value (Chi-square) 0.002 0.013
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2226.453 1731.411
Degrees of freedom 138 138
P-value 0.000 0.000
Scaling correction factor 1.286
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.970 0.971
Robust Comparative Fit Index (CFI) 0.982
Robust Tucker-Lewis Index (TLI) 0.975
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3017.623 -3017.623
Scaling correction factor 1.752
for the MLR correction
Loglikelihood unrestricted model (H1) -2944.404 -2944.404
Scaling correction factor 1.302
for the MLR correction
Akaike (AIC) 6133.245 6133.245
Bayesian (BIC) 6297.718 6297.718
Sample-size adjusted Bayesian (SABIC) 6142.453 6142.453
Root Mean Square Error of Approximation:
RMSEA 0.046 0.040
90 Percent confidence interval - lower 0.028 0.020
90 Percent confidence interval - upper 0.062 0.056
P-value H_0: RMSEA <= 0.050 0.641 0.838
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.020
90 Percent confidence interval - upper 0.059
P-value H_0: Robust RMSEA <= 0.050 0.772
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
ADT =~
ADT1 1.000 0.920 0.879
ADT2 1.033 0.068 15.123 0.000 0.951 0.899
ADT3 1.146 0.077 14.877 0.000 1.055 0.881
IM =~
IM1 1.000 1.111 0.961
IM2 0.712 0.104 6.836 0.000 0.791 0.736
IM3 0.680 0.121 5.617 0.000 0.755 0.652
EEF =~
EEF1 1.000 1.077 0.912
EEF2 1.040 0.052 20.006 0.000 1.121 0.932
EEF3 0.954 0.056 17.092 0.000 1.028 0.900
EEC =~
EEC1 1.000 0.964 0.736
EEC2 1.285 0.110 11.673 0.000 1.238 0.873
EEC3 1.327 0.092 14.352 0.000 1.279 0.944
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.215 0.216 0.993 0.321 0.193 0.070
rwrd0_2 (b_02) 0.227 0.241 0.945 0.345 0.205 0.077
rwrd1_2 (b_12) 0.306 0.238 1.283 0.200 0.275 0.101
rwrd0_3 (b_03) 0.006 0.254 0.023 0.982 0.005 0.002
rwrd1_3 (b_13) -0.079 0.198 -0.401 0.689 -0.072 -0.027
ADT (b_AD) 0.426 0.100 4.261 0.000 0.353 0.353
PEB_yes (b_PE) 1.057 0.167 6.326 0.000 0.951 0.406
EEF ~
rwrd1_1 (c_11) 0.231 0.182 1.266 0.205 0.215 0.078
rwrd0_2 (c_02) -0.118 0.197 -0.600 0.549 -0.110 -0.041
rwrd1_2 (c_12) 0.204 0.180 1.130 0.258 0.189 0.069
rwrd0_3 (c_03) -0.157 0.169 -0.925 0.355 -0.145 -0.055
rwrd1_3 (c_13) -0.013 0.179 -0.071 0.943 -0.012 -0.004
IM (c_IM) 0.520 0.084 6.172 0.000 0.536 0.536
ADT (c_AD) 0.237 0.067 3.541 0.000 0.203 0.203
PEB_yes (c_PE) 0.365 0.168 2.169 0.030 0.339 0.145
EEC ~
rwrd1_1 (d_11) 0.236 0.214 1.104 0.270 0.245 0.089
rwrd0_2 (d_02) 0.174 0.218 0.801 0.423 0.181 0.068
rwrd1_2 (d_12) 0.327 0.197 1.666 0.096 0.340 0.125
rwrd0_3 (d_03) 0.098 0.176 0.556 0.578 0.101 0.038
rwrd1_3 (d_13) 0.041 0.202 0.201 0.841 0.042 0.016
IM (d_IM) 0.356 0.089 4.006 0.000 0.410 0.410
ADT (d_AD) 0.254 0.078 3.245 0.001 0.242 0.242
PEB_yes (d_PE) 0.199 0.165 1.203 0.229 0.206 0.088
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.351 0.161 2.184 0.029 0.351 0.549
.EEF ~~
.EEC 0.226 0.069 3.271 0.001 0.392 0.392
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.ADT1 0.248 0.057 4.396 0.000 0.248 0.227
.ADT2 0.215 0.054 4.007 0.000 0.215 0.192
.ADT3 0.320 0.087 3.682 0.000 0.320 0.224
.IM1 0.101 0.099 1.021 0.307 0.101 0.076
.IM2 0.529 0.169 3.136 0.002 0.529 0.458
.IM3 0.771 0.236 3.263 0.001 0.771 0.575
.EEF1 0.235 0.044 5.295 0.000 0.235 0.169
.EEF2 0.191 0.044 4.316 0.000 0.191 0.132
.EEF3 0.249 0.063 3.920 0.000 0.249 0.191
.EEC1 0.787 0.094 8.401 0.000 0.787 0.459
.EEC2 0.478 0.103 4.634 0.000 0.478 0.238
.EEC3 0.201 0.063 3.204 0.001 0.201 0.110
ADT 0.847 0.125 6.797 0.000 1.000 1.000
.IM 0.850 0.154 5.532 0.000 0.689 0.689
.EEF 0.557 0.111 5.008 0.000 0.480 0.480
.EEC 0.594 0.096 6.211 0.000 0.640 0.640
R-Square:
Estimate
ADT1 0.773
ADT2 0.808
ADT3 0.776
IM1 0.924
IM2 0.542
IM3 0.425
EEF1 0.831
EEF2 0.868
EEF3 0.809
EEC1 0.541
EEC2 0.762
EEC3 0.890
IM 0.311
EEF 0.520
EEC 0.360
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.215 0.216 0.993 0.321 0.193 0.070
reward2_IM 0.078 0.255 0.307 0.759 0.071 0.024
reward3_IM -0.085 0.244 -0.350 0.727 -0.077 -0.029
reward_vrgd_IM 0.069 0.138 0.503 0.615 0.062 0.022
reward_EEF_ec1 0.231 0.182 1.266 0.205 0.215 0.078
reward_EEF_ec2 0.322 0.212 1.519 0.129 0.299 0.110
reward_EEF_ec3 0.144 0.188 0.767 0.443 0.133 0.050
reward_man_EEF 0.232 0.113 2.048 0.041 0.215 0.079
ind_rwrd_EEF_1 0.112 0.117 0.954 0.340 0.104 0.038
ind_rwrd_EEF_2 0.041 0.132 0.310 0.757 0.038 0.013
ind_rwrd_EEF_3 -0.044 0.128 -0.347 0.729 -0.041 -0.015
ind_rw__IM_EEF 0.036 0.072 0.504 0.614 0.033 0.012
tt_rwrd_mn_EEF 0.268 0.129 2.084 0.037 0.249 0.091
reward_EEC_ec1 0.236 0.214 1.104 0.270 0.245 0.089
reward_EEC_ec2 0.153 0.202 0.756 0.450 0.159 0.057
reward_EEC_ec3 -0.057 0.182 -0.314 0.754 -0.059 -0.022
reward_man_EEC 0.111 0.115 0.963 0.336 0.115 0.041
ind_rwrd_EEC_1 0.076 0.085 0.904 0.366 0.079 0.029
ind_rwrd_EEC_2 0.028 0.091 0.305 0.760 0.029 0.010
ind_rwrd_EEC_3 -0.030 0.088 -0.346 0.729 -0.031 -0.012
ind_rw__IM_EEC 0.025 0.050 0.491 0.624 0.026 0.009
tt_rwrd_mn_EEC 0.135 0.123 1.097 0.273 0.141 0.050
eco2_vs_c1_EEF -0.073 0.141 -0.517 0.605 -0.068 -0.025
eco3_vs_c1_EEF -0.200 0.129 -1.551 0.121 -0.186 -0.068
eco1_vs_c2_EEF 0.073 0.141 0.517 0.605 0.068 0.025
eco_main_EEF -0.136 0.114 -1.202 0.229 -0.127 -0.047
eco2_vs_ec1_IM 0.159 0.163 0.978 0.328 0.143 0.054
eco3_vs_ec1_IM -0.144 0.162 -0.891 0.373 -0.130 -0.048
eco1_vs_ec2_IM -0.159 0.163 -0.978 0.328 -0.143 -0.054
in_1__2_IM_EEF -0.083 0.086 -0.967 0.334 -0.077 -0.029
in_2__1_IM_EEF 0.083 0.086 0.967 0.334 0.077 0.029
in_3__1_IM_EEF -0.075 0.087 -0.863 0.388 -0.070 -0.025
ind_c_m_IM_EEF 0.004 0.070 0.055 0.956 0.004 0.002
tt_c1_vs_2_EEF -0.010 0.157 -0.064 0.949 -0.009 -0.004
tt_c2_vs_1_EEF 0.010 0.157 0.064 0.949 0.009 0.004
tt_c3_vs_1_EEF -0.275 0.150 -1.830 0.067 -0.255 -0.094
tot_eco_mn_EEF -0.133 0.130 -1.022 0.307 -0.123 -0.045
eco2_vs_c1_EEC 0.133 0.150 0.884 0.377 0.138 0.052
eco3_vs_c1_EEC -0.049 0.136 -0.359 0.720 -0.051 -0.017
eco_main_EEC 0.042 0.125 0.335 0.737 0.043 0.017
in_2__1_IM_EEC 0.057 0.058 0.975 0.330 0.059 0.022
in_3__1_IM_EEC -0.051 0.062 -0.834 0.404 -0.053 -0.019
ind_c_m_IM_EEC 0.003 0.048 0.055 0.956 0.003 0.001
tt_c2_vs_1_EEC 0.189 0.163 1.165 0.244 0.197 0.074
tt_c3_vs_1_EEC -0.100 0.137 -0.731 0.465 -0.104 -0.037
tot_eco_mn_EEC 0.045 0.129 0.345 0.730 0.046 0.018
eco_main_IM 0.007 0.135 0.055 0.956 0.007 0.003
eco3_vs_c2_EEF -0.127 0.146 -0.873 0.383 -0.118 -0.044
in_3__2_IM_EEF -0.158 0.101 -1.563 0.118 -0.147 -0.054
tt_c3_vs_2_EEF -0.285 0.165 -1.726 0.084 -0.265 -0.098
eco3_vs_c2_EEC -0.182 0.141 -1.286 0.198 -0.189 -0.069
in_3__2_IM_EEC -0.108 0.072 -1.497 0.134 -0.112 -0.042
tt_c3_vs_2_EEC -0.290 0.154 -1.877 0.060 -0.301 -0.111
reward_IM_eco1 0.215 0.216 0.993 0.321 0.193 0.070
reward_IM_eco2 0.078 0.255 0.307 0.759 0.071 0.024
reward_IM_eco3 -0.085 0.244 -0.350 0.727 -0.077 -0.029
reward_main_IM 0.069 0.138 0.503 0.615 0.062 0.022
r_3_EEF___1_EE -0.244 0.197 -1.236 0.216 -0.226 -0.082
r_2_EEF___1_EE -0.027 0.197 -0.140 0.889 -0.026 -0.008
r_2_EEC___1_EE 0.091 0.203 0.450 0.653 0.095 0.036
r_3_EEC___2_EE -0.287 0.202 -1.419 0.156 -0.298 -0.109
r_3_EEC___1_EE -0.196 0.214 -0.912 0.362 -0.203 -0.073
rw_2_IM___1_IM 0.091 0.220 0.414 0.679 0.082 0.031
rw_3_IM___1_IM -0.294 0.207 -1.424 0.154 -0.265 -0.097
i__2_EEC___1_E 0.032 0.077 0.420 0.674 0.034 0.013
i__3_EEC___1_E -0.105 0.086 -1.213 0.225 -0.109 -0.040
i__3_EEC___2_E -0.137 0.092 -1.485 0.138 -0.142 -0.052
t__2_EEC___1_E 0.124 0.217 0.571 0.568 0.128 0.048
t__3_EEC___1_E -0.300 0.216 -1.390 0.165 -0.312 -0.113
t__3_EEC___2_E -0.424 0.215 -1.969 0.049 -0.440 -0.161Mediation analysis with bootstrapping=5000 lhs op
82 reward_main_EEF :=
86 ind_reward_main_IM_EEF :=
87 tot_reward_main_EEF :=
91 reward_main_EEC :=
95 ind_reward_main_IM_EEC :=
96 tot_reward_main_EEC :=
98 eco3_vs_eco1_EEF :=
99 eco1_vs_eco2_EEF :=
100 eco_main_EEF :=
101 eco2_vs_eco1_IM :=
102 eco3_vs_eco1_IM :=
103 eco1_vs_eco2_IM :=
104 ind_eco1_vs_eco2_IM_EEF :=
106 ind_eco3_vs_eco1_IM_EEF :=
107 ind_eco_main_IM_EEF :=
108 tot_eco1_vs_eco2_EEF :=
110 tot_eco3_vs_eco1_EEF :=
111 tot_eco_main_EEF :=
112 eco2_vs_eco1_EEC :=
113 eco3_vs_eco1_EEC :=
114 eco_main_EEC :=
115 ind_eco2_vs_eco1_IM_EEC :=
116 ind_eco3_vs_eco1_IM_EEC :=
117 ind_eco_main_IM_EEC :=
118 tot_eco2_vs_eco1_EEC :=
119 tot_eco3_vs_eco1_EEC :=
120 tot_eco_main_EEC :=
121 eco_main_IM :=
125 eco3_vs_eco2_EEC :=
126 ind_eco3_vs_eco2_IM_EEC :=
127 tot_eco3_vs_eco2_EEC :=
131 reward_main_IM :=
132 reward_eco3_EEF_vs_reward_eco1_EEF :=
133 reward_eco2_EEF_vs_reward_eco1_EEF :=
134 reward_eco2_EEC_vs_reward_eco1_EEC :=
135 reward_eco3_EEC_vs_reward_eco2_EEC :=
137 reward_eco2_IM_vs_reward_eco1_IM :=
138 reward_eco3_IM_vs_reward_eco1_IM :=
139 ind_reward_eco2_EEC_vs_reward_eco1_EEC :=
140 ind_reward_eco3_EEC_vs_reward_eco1_EEC :=
141 ind_reward_eco3_EEC_vs_reward_eco2_EEC :=
142 tot_reward_eco2_EEC_vs_reward_eco1_EEC :=
143 tot_reward_eco3_EEC_vs_reward_eco1_EEC :=
144 tot_reward_eco3_EEC_vs_reward_eco2_EEC :=
rhs
82 ((c_r1e1-0)+(c_r1e2-c_r0e2)+(c_r1e3-c_r0e3))/3
86 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3*c_IM
87 reward_main_EEF+ind_reward_main_IM_EEF
91 ((d_r1e1-0)+(d_r1e2-d_r0e2)+(d_r1e3-d_r0e3))/3
95 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3*d_IM
96 reward_main_EEC+ind_reward_main_IM_EEC
98 ((c_r0e3-0)+(c_r1e3-c_r1e1))/2
99 ((0-c_r0e2)+(c_r1e1-c_r1e2))/2
100 (eco2_vs_eco1_EEF+eco3_vs_eco1_EEF)/2
101 ((b_r0e2-0)+(b_r1e2-b_r1e1))/2
102 ((b_r0e3-0)+(b_r1e3-b_r1e1))/2
103 ((0-b_r0e2)+(b_r1e1-b_r1e2))/2
104 eco1_vs_eco2_IM*c_IM
106 eco3_vs_eco1_IM*c_IM
107 (ind_eco2_vs_eco1_IM_EEF+ind_eco3_vs_eco1_IM_EEF)/2
108 eco1_vs_eco2_EEF+ind_eco1_vs_eco2_IM_EEF
110 eco3_vs_eco1_EEF+ind_eco3_vs_eco1_IM_EEF
111 eco_main_EEF+ind_eco_main_IM_EEF
112 ((d_r0e2-0)+(d_r1e2-d_r1e1))/2
113 ((d_r0e3-0)+(d_r1e3-d_r1e1))/2
114 (eco2_vs_eco1_EEC+eco3_vs_eco1_EEC)/2
115 eco2_vs_eco1_IM*d_IM
116 eco3_vs_eco1_IM*d_IM
117 (ind_eco2_vs_eco1_IM_EEC+ind_eco3_vs_eco1_IM_EEC)/2
118 eco2_vs_eco1_EEC+ind_eco2_vs_eco1_IM_EEC
119 eco3_vs_eco1_EEC+ind_eco3_vs_eco1_IM_EEC
120 eco_main_EEC+ind_eco_main_IM_EEC
121 (eco2_vs_eco1_IM+eco3_vs_eco1_IM)/2
125 eco3_vs_eco1_EEC-eco2_vs_eco1_EEC
126 ind_eco3_vs_eco1_IM_EEC-ind_eco2_vs_eco1_IM_EEC
127 tot_eco3_vs_eco1_EEC-tot_eco2_vs_eco1_EEC
131 ((b_r1e1-0)+(b_r1e2-b_r0e2)+(b_r1e3-b_r0e3))/3
132 c_r1e3-c_r1e1
133 c_r1e2-c_r1e1
134 d_r1e2-d_r1e1
135 d_r1e3-d_r1e2
137 b_r1e2-b_r1e1
138 b_r1e3-b_r1e1
139 (b_r1e2-b_r1e1)*d_IM
140 (b_r1e3-b_r1e1)*d_IM
141 (b_r1e3-b_r1e2)*d_IM
142 (d_r1e2-d_r1e1)+ind_reward_eco2_EEC_vs_reward_eco1_EEC
143 (d_r1e3-d_r1e1)+ind_reward_eco3_EEC_vs_reward_eco1_EEC
144 (d_r1e3-d_r1e2)+ind_reward_eco3_EEC_vs_reward_eco2_EEC
label est se z pvalue ci.lower
82 reward_main_EEF 0.232 0.124 1.878 0.060 -0.052
86 ind_reward_main_IM_EEF 0.036 0.072 0.501 0.616 -0.089
87 tot_reward_main_EEF 0.268 0.125 2.149 0.032 -0.003
91 reward_main_EEC 0.111 0.115 0.966 0.334 -0.219
95 ind_reward_main_IM_EEC 0.025 0.055 0.447 0.655 -0.058
96 tot_reward_main_EEC 0.135 0.125 1.085 0.278 -0.237
98 eco3_vs_eco1_EEF -0.200 0.137 -1.459 0.144 -0.620
99 eco1_vs_eco2_EEF 0.073 0.131 0.557 0.577 -0.178
100 eco_main_EEF -0.136 0.116 -1.174 0.240 -0.431
101 eco2_vs_eco1_IM 0.159 0.164 0.971 0.332 -0.216
102 eco3_vs_eco1_IM -0.144 0.155 -0.933 0.351 -0.527
103 eco1_vs_eco2_IM -0.159 0.164 -0.971 0.332 -0.423
104 ind_eco1_vs_eco2_IM_EEF -0.083 0.089 -0.929 0.353 -0.266
106 ind_eco3_vs_eco1_IM_EEF -0.075 0.082 -0.919 0.358 -0.289
107 ind_eco_main_IM_EEF 0.004 0.071 0.054 0.957 -0.152
108 tot_eco1_vs_eco2_EEF -0.010 0.149 -0.067 0.946 -0.348
110 tot_eco3_vs_eco1_EEF -0.275 0.134 -2.049 0.040 -0.613
111 tot_eco_main_EEF -0.133 0.127 -1.044 0.296 -0.423
112 eco2_vs_eco1_EEC 0.133 0.139 0.952 0.341 -0.121
113 eco3_vs_eco1_EEC -0.049 0.141 -0.347 0.729 -0.318
114 eco_main_EEC 0.042 0.123 0.341 0.733 -0.194
115 ind_eco2_vs_eco1_IM_EEC 0.057 0.060 0.936 0.349 -0.069
116 ind_eco3_vs_eco1_IM_EEC -0.051 0.059 -0.876 0.381 -0.213
117 ind_eco_main_IM_EEC 0.003 0.048 0.055 0.956 -0.126
118 tot_eco2_vs_eco1_EEC 0.189 0.147 1.291 0.197 -0.057
119 tot_eco3_vs_eco1_EEC -0.100 0.135 -0.744 0.457 -0.379
120 tot_eco_main_EEC 0.045 0.123 0.363 0.717 -0.187
121 eco_main_IM 0.007 0.139 0.053 0.957 -0.324
125 eco3_vs_eco2_EEC -0.182 0.135 -1.346 0.178 -0.486
126 ind_eco3_vs_eco2_IM_EEC -0.108 0.069 -1.557 0.119 -0.269
127 tot_eco3_vs_eco2_EEC -0.290 0.138 -2.092 0.036 -0.650
131 reward_main_IM 0.069 0.139 0.498 0.619 -0.159
132 reward_eco3_EEF_vs_reward_eco1_EEF -0.244 0.187 -1.305 0.192 -0.785
133 reward_eco2_EEF_vs_reward_eco1_EEF -0.027 0.191 -0.144 0.885 -0.461
134 reward_eco2_EEC_vs_reward_eco1_EEC 0.091 0.211 0.431 0.666 -0.302
135 reward_eco3_EEC_vs_reward_eco2_EEC -0.287 0.207 -1.382 0.167 -0.735
137 reward_eco2_IM_vs_reward_eco1_IM 0.091 0.211 0.432 0.666 -0.376
138 reward_eco3_IM_vs_reward_eco1_IM -0.294 0.197 -1.495 0.135 -0.733
139 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.032 0.077 0.421 0.674 -0.153
140 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.105 0.089 -1.171 0.242 -0.322
141 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.137 0.099 -1.387 0.165 -0.449
142 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.124 0.215 0.574 0.566 -0.249
143 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.300 0.228 -1.315 0.188 -0.750
144 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.424 0.215 -1.969 0.049 -0.895
ci.upper std.lv std.all std.nox
82 0.469 0.215 0.079 0.215
86 0.202 0.033 0.012 0.033
87 0.515 0.249 0.091 0.249
91 0.295 0.115 0.041 0.115
95 0.164 0.026 0.009 0.026
96 0.404 0.141 0.050 0.141
98 0.051 -0.186 -0.068 -0.186
99 0.386 0.068 0.025 0.068
100 0.114 -0.127 -0.047 -0.127
101 0.423 0.143 0.054 0.143
102 0.139 -0.130 -0.048 -0.130
103 0.216 -0.143 -0.054 -0.143
104 0.101 -0.077 -0.029 -0.077
106 0.075 -0.070 -0.025 -0.070
107 0.140 0.004 0.002 0.004
108 0.311 -0.009 -0.004 -0.009
110 -0.007 -0.255 -0.094 -0.255
111 0.104 -0.123 -0.045 -0.123
112 0.494 0.138 0.052 0.138
113 0.326 -0.051 -0.017 -0.051
114 0.323 0.043 0.017 0.043
115 0.206 0.059 0.022 0.059
116 0.049 -0.053 -0.019 -0.053
117 0.075 0.003 0.001 0.003
118 0.639 0.197 0.074 0.197
119 0.232 -0.104 -0.037 -0.104
120 0.326 0.046 0.018 0.046
121 0.238 0.007 0.003 0.007
125 0.090 -0.189 -0.069 -0.189
126 0.012 -0.112 -0.042 -0.112
127 -0.093 -0.301 -0.111 -0.301
131 0.352 0.062 0.022 0.062
132 0.103 -0.226 -0.082 -0.226
133 0.310 -0.026 -0.008 -0.026
134 0.601 0.095 0.036 0.095
135 0.217 -0.298 -0.109 -0.298
137 0.568 0.082 0.031 0.082
138 0.114 -0.265 -0.097 -0.265
139 0.239 0.034 0.013 0.034
140 0.036 -0.109 -0.040 -0.109
141 0.009 -0.142 -0.052 -0.142
142 0.675 0.128 0.048 0.128
143 0.334 -0.312 -0.113 -0.312
144 0.051 -0.440 -0.161 -0.440Only PEB)
With control variableslavaan 0.6-21 ended normally after 63 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 53
Number of observations 212
Model Test User Model:
Standard Scaled
Test Statistic 254.566 240.491
Degrees of freedom 157 157
P-value (Chi-square) 0.000 0.000
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) 0.964 0.962
Tucker-Lewis Index (TLI) 0.955 0.952
Robust Comparative Fit Index (CFI) 0.967
Robust Tucker-Lewis Index (TLI) 0.959
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3888.666 -3888.666
Scaling correction factor 1.747
for the MLR correction
Loglikelihood unrestricted model (H1) -3761.384 -3761.384
Scaling correction factor 1.232
for the MLR correction
Akaike (AIC) 7883.333 7883.333
Bayesian (BIC) 8061.232 8061.232
Sample-size adjusted Bayesian (SABIC) 7893.293 7893.293
Root Mean Square Error of Approximation:
RMSEA 0.054 0.050
90 Percent confidence interval - lower 0.042 0.037
90 Percent confidence interval - upper 0.066 0.062
P-value H_0: RMSEA <= 0.050 0.279 0.483
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.052
90 Percent confidence interval - lower 0.038
90 Percent confidence interval - upper 0.064
P-value H_0: Robust RMSEA <= 0.050 0.410
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.140 0.140
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
TR =~
TR1 1.000 1.315 0.884
TR2 1.090 0.048 22.674 0.000 1.434 0.942
TR3 1.049 0.050 21.146 0.000 1.380 0.920
ADT =~
ADT1 1.000 0.916 0.875
ADT2 1.047 0.069 15.102 0.000 0.960 0.907
ADT3 1.145 0.074 15.390 0.000 1.049 0.876
IM =~
IM1 1.000 1.106 0.948
IM2 0.732 0.099 7.417 0.000 0.810 0.750
IM3 0.702 0.116 6.048 0.000 0.776 0.667
EEF =~
EEF1 1.000 1.085 0.912
EEF2 1.043 0.052 20.112 0.000 1.132 0.933
EEF3 0.957 0.055 17.485 0.000 1.038 0.902
EEC =~
EEC1 1.000 0.971 0.738
EEC2 1.287 0.111 11.622 0.000 1.249 0.875
EEC3 1.327 0.093 14.320 0.000 1.288 0.944
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.281 0.249 1.129 0.259 0.254 0.092
rwrd0_2 (b_02) 0.292 0.242 1.204 0.229 0.264 0.099
rwrd1_2 (b_12) 0.305 0.242 1.262 0.207 0.276 0.101
rwrd0_3 (b_03) 0.005 0.279 0.019 0.985 0.005 0.002
rwrd1_3 (b_13) -0.120 0.218 -0.548 0.584 -0.108 -0.041
PEB_yes (b_PE) 1.109 0.175 6.328 0.000 1.002 0.428
EEF ~
rwrd1_1 (c_11) 0.222 0.185 1.203 0.229 0.205 0.074
rwrd0_2 (c_02) -0.120 0.201 -0.598 0.550 -0.110 -0.041
rwrd1_2 (c_12) 0.153 0.188 0.811 0.417 0.141 0.052
rwrd0_3 (c_03) -0.161 0.178 -0.903 0.366 -0.148 -0.056
rwrd1_3 (c_13) -0.022 0.186 -0.119 0.905 -0.020 -0.008
IM (c_IM) 0.623 0.078 7.974 0.000 0.635 0.635
PEB_yes (c_PE) 0.271 0.176 1.538 0.124 0.249 0.107
EEC ~
rwrd1_1 (d_11) 0.232 0.215 1.079 0.281 0.239 0.087
rwrd0_2 (d_02) 0.175 0.217 0.805 0.421 0.180 0.068
rwrd1_2 (d_12) 0.279 0.208 1.336 0.181 0.287 0.105
rwrd0_3 (d_03) 0.094 0.185 0.507 0.612 0.097 0.036
rwrd1_3 (d_13) 0.028 0.216 0.132 0.895 0.029 0.011
IM (d_IM) 0.460 0.079 5.793 0.000 0.524 0.524
PEB_yes (d_PE) 0.109 0.170 0.639 0.523 0.112 0.048
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.332 0.152 2.176 0.030 0.332 0.536
TR ~~
ADT 0.631 0.106 5.935 0.000 0.523 0.523
.EEF ~~
.EEC 0.263 0.072 3.672 0.000 0.430 0.430
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.483 0.083 5.824 0.000 0.483 0.218
.TR2 0.259 0.067 3.850 0.000 0.259 0.112
.TR3 0.345 0.087 3.940 0.000 0.345 0.153
.ADT1 0.256 0.057 4.456 0.000 0.256 0.234
.ADT2 0.198 0.052 3.837 0.000 0.198 0.177
.ADT3 0.332 0.090 3.696 0.000 0.332 0.232
.IM1 0.137 0.081 1.692 0.091 0.137 0.101
.IM2 0.511 0.162 3.163 0.002 0.511 0.438
.IM3 0.750 0.232 3.228 0.001 0.750 0.555
.EEF1 0.240 0.045 5.314 0.000 0.240 0.169
.EEF2 0.189 0.044 4.298 0.000 0.189 0.129
.EEF3 0.247 0.063 3.898 0.000 0.247 0.186
.EEC1 0.788 0.094 8.384 0.000 0.788 0.455
.EEC2 0.475 0.104 4.551 0.000 0.475 0.234
.EEC3 0.204 0.063 3.234 0.001 0.204 0.109
TR 1.730 0.172 10.045 0.000 1.000 1.000
ADT 0.840 0.124 6.748 0.000 1.000 1.000
.IM 0.962 0.185 5.199 0.000 0.786 0.786
.EEF 0.586 0.115 5.110 0.000 0.498 0.498
.EEC 0.636 0.105 6.078 0.000 0.675 0.675
R-Square:
Estimate
TR1 0.782
TR2 0.888
TR3 0.847
ADT1 0.766
ADT2 0.823
ADT3 0.768
IM1 0.899
IM2 0.562
IM3 0.445
EEF1 0.831
EEF2 0.871
EEF3 0.814
EEC1 0.545
EEC2 0.766
EEC3 0.891
IM 0.214
EEF 0.502
EEC 0.325###Comparing difference between model fits