KMO
KMOKaiser-Meyer-Olkin factor adequacy
Call: KMO(r = efa_data_good)
Overall MSA = 0.84
MSA for each item =
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2 TR3
0.90 0.84 0.83 0.86 0.89 0.89 0.90 0.83 0.81 0.87 0.78 0.81 0.86 0.76 0.81 R was not square, finding R from data$chisq
[1] 2681.929
$p.value
[1] 0
$df
[1] 105 IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1
IM1 1.0000000 0.64326152 0.61979636 0.4982582 0.5173121 0.5129724 0.4126565
IM2 0.6432615 1.00000000 0.67070298 0.4139217 0.4676608 0.4573846 0.3136449
IM3 0.6197964 0.67070298 1.00000000 0.3426372 0.3894868 0.4338694 0.4159567
EEF1 0.4982582 0.41392173 0.34263720 1.0000000 0.8316756 0.8168640 0.4793843
EEF2 0.5173121 0.46766080 0.38948681 0.8316756 1.0000000 0.8129749 0.4721765
EEF3 0.5129724 0.45738460 0.43386936 0.8168640 0.8129749 1.0000000 0.4628790
EEC1 0.4126565 0.31364493 0.41595667 0.4793843 0.4721765 0.4628790 1.0000000
EEC2 0.4778518 0.32807817 0.32931552 0.4957168 0.5272198 0.5120467 0.5904316
EEC3 0.4663014 0.26966554 0.32382237 0.5245412 0.5114065 0.5316961 0.6909718
ADT1 0.2794156 0.13501374 0.15510711 0.3255508 0.3312074 0.3248718 0.2420757
ADT2 0.1436737 0.03888524 0.06903489 0.2462682 0.2235847 0.2436994 0.1993086
ADT3 0.1812815 0.09549328 0.10554165 0.3094569 0.2692572 0.2543317 0.2038638
TR1 0.2269993 0.12679426 0.16844263 0.2506951 0.1945171 0.2174108 0.2457840
TR2 0.2192631 0.08673667 0.12332224 0.1852857 0.1486312 0.2032614 0.1481077
TR3 0.2101082 0.12041224 0.15370525 0.2512533 0.1947803 0.2523888 0.1981541
EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2
IM1 0.4778518 0.4663014 0.2794156 0.14367369 0.18128154 0.2269993 0.21926306
IM2 0.3280782 0.2696655 0.1350137 0.03888524 0.09549328 0.1267943 0.08673667
IM3 0.3293155 0.3238224 0.1551071 0.06903489 0.10554165 0.1684426 0.12332224
EEF1 0.4957168 0.5245412 0.3255508 0.24626818 0.30945689 0.2506951 0.18528567
EEF2 0.5272198 0.5114065 0.3312074 0.22358466 0.26925724 0.1945171 0.14863117
EEF3 0.5120467 0.5316961 0.3248718 0.24369938 0.25433169 0.2174108 0.20326143
EEC1 0.5904316 0.6909718 0.2420757 0.19930861 0.20386383 0.2457840 0.14810773
EEC2 1.0000000 0.8270083 0.3072727 0.25024427 0.28481147 0.2606290 0.17748546
EEC3 0.8270083 1.0000000 0.3282466 0.25511178 0.25512328 0.3272256 0.26011965
ADT1 0.3072727 0.3282466 1.0000000 0.76093033 0.71536627 0.3396706 0.33413205
ADT2 0.2502443 0.2551118 0.7609303 1.00000000 0.78053629 0.3168064 0.30260667
ADT3 0.2848115 0.2551233 0.7153663 0.78053629 1.00000000 0.3343923 0.29317572
TR1 0.2606290 0.3272256 0.3396706 0.31680643 0.33439226 1.0000000 0.83406679
TR2 0.1774855 0.2601197 0.3341320 0.30260667 0.29317572 0.8340668 1.00000000
TR3 0.1903847 0.2780288 0.3570132 0.31129561 0.36508970 0.8148168 0.86483216
TR3
IM1 0.2101082
IM2 0.1204122
IM3 0.1537052
EEF1 0.2512533
EEF2 0.1947803
EEF3 0.2523888
EEC1 0.1981541
EEC2 0.1903847
EEC3 0.2780288
ADT1 0.3570132
ADT2 0.3112956
ADT3 0.3650897
TR1 0.8148168
TR2 0.8648322
TR3 1.0000000
Loading required namespace: GPArotationThreshold = 0.35
Loadings:
MR1 MR2 MR3 MR4 MR5
IM1 NA NA NA NA 0.650
IM2 NA NA NA NA 0.832
IM3 NA NA NA NA 0.838
EEF1 0.943 NA NA NA NA
EEF2 0.894 NA NA NA NA
EEF3 0.837 NA NA NA NA
EEC1 NA NA NA 0.589 NA
EEC2 NA NA NA 0.761 NA
EEC3 NA NA NA 1.019 NA
ADT1 NA NA 0.800 NA NA
ADT2 NA NA 0.942 NA NA
ADT3 NA NA 0.846 NA NA
TR1 NA 0.862 NA NA NA
TR2 NA 0.961 NA NA NA
TR3 NA 0.911 NA NA NA
MR1 MR2 MR3 MR4 MR5
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 0.238 0.340 0.589 0.563
2 0.238 1.000 0.396 0.287 0.174
3 0.340 0.396 1.000 0.322 0.143
4 0.589 0.287 0.322 1.000 0.425
5 0.563 0.174 0.143 0.425 1.000
1 2 3 4 5
1 1.000 0.239 0.339 0.592 0.564
2 0.239 1.000 0.396 0.288 0.174
3 0.339 0.396 1.000 0.322 0.143
4 0.592 0.288 0.322 1.000 0.427
5 0.564 0.174 0.143 0.427 1.000lavaan 0.6-21 ended normally after 32 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 21
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 65.304 49.602
Degrees of freedom 24 24
P-value (Chi-square) 0.000 0.002
Scaling correction factor 1.317
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1540.967 832.018
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.852
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.973 0.968
Tucker-Lewis Index (TLI) 0.959 0.952
Robust Comparative Fit Index (CFI) 0.977
Robust Tucker-Lewis Index (TLI) 0.966
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2528.324 -2528.324
Scaling correction factor 2.238
for the MLR correction
Loglikelihood unrestricted model (H1) -2495.672 -2495.672
Scaling correction factor 1.747
for the MLR correction
Akaike (AIC) 5098.647 5098.647
Bayesian (BIC) 5171.209 5171.209
Sample-size adjusted Bayesian (SABIC) 5104.648 5104.648
Root Mean Square Error of Approximation:
RMSEA 0.086 0.068
90 Percent confidence interval - lower 0.061 0.044
90 Percent confidence interval - upper 0.111 0.091
P-value H_0: RMSEA <= 0.050 0.010 0.103
P-value H_0: RMSEA >= 0.080 0.671 0.199
Robust RMSEA 0.077
90 Percent confidence interval - lower 0.046
90 Percent confidence interval - upper 0.108
P-value H_0: Robust RMSEA <= 0.050 0.070
P-value H_0: Robust RMSEA >= 0.080 0.474
Standardized Root Mean Square Residual:
SRMR 0.049 0.049
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 1.272 0.104 12.248 0.000 1.069 1.476
EEC3 1.353 0.091 14.867 0.000 1.175 1.531
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.985 0.050 19.776 0.000 0.887 1.082
EEF3 0.953 0.044 21.627 0.000 0.866 1.039
IM =~
IM1 1.000 1.000 1.000
IM2 0.801 0.095 8.436 0.000 0.615 0.987
IM3 0.885 0.117 7.573 0.000 0.656 1.114
Std.lv Std.all
0.966 0.724
1.229 0.870
1.308 0.946
1.055 0.908
1.039 0.911
1.005 0.899
0.851 0.816
0.682 0.809
0.754 0.780
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC ~~
EEF 0.641 0.105 6.085 0.000 0.434 0.847
IM 0.415 0.093 4.475 0.000 0.233 0.597
EEF ~~
IM 0.557 0.091 6.136 0.000 0.379 0.735
Std.lv Std.all
0.629 0.629
0.504 0.504
0.620 0.620
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.849 0.095 8.926 0.000 0.663 1.036
.EEC2 0.484 0.097 4.996 0.000 0.294 0.674
.EEC3 0.202 0.061 3.287 0.001 0.081 0.322
.EEF1 0.236 0.050 4.713 0.000 0.138 0.334
.EEF2 0.222 0.043 5.217 0.000 0.139 0.305
.EEF3 0.240 0.057 4.203 0.000 0.128 0.352
.IM1 0.363 0.072 5.067 0.000 0.223 0.504
.IM2 0.245 0.063 3.879 0.000 0.121 0.369
.IM3 0.365 0.189 1.930 0.054 -0.006 0.735
EEC 0.934 0.143 6.554 0.000 0.655 1.213
EEF 1.113 0.168 6.611 0.000 0.783 1.443
IM 0.725 0.110 6.614 0.000 0.510 0.940
Std.lv Std.all
0.849 0.476
0.484 0.243
0.202 0.105
0.236 0.175
0.222 0.171
0.240 0.192
0.363 0.334
0.245 0.345
0.365 0.391
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.524
EEC2 0.757
EEC3 0.895
EEF1 0.825
EEF2 0.829
EEF3 0.808
IM1 0.666
IM2 0.655
IM3 0.609Cronbach’s Alpha: EEC EEF IM
0.877 0.932 0.840 Omega: EEC EEF IM
0.896 0.932 0.843 Average Variance Extracted (AVE): EEC EEF IM
0.730 0.821 0.644 Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
28 EEC =~ IM1 16.694 0.276 0.267 0.256 0.256
29 EEC =~ IM2 10.937 -0.180 -0.174 -0.207 -0.207
39 IM =~ EEC3 10.377 -0.278 -0.236 -0.171 -0.171
50 EEC1 ~~ IM3 10.568 0.139 0.139 0.251 0.251
78 IM2 ~~ IM3 13.696 0.164 0.164 0.549 0.549Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
50 EEC1 ~~ IM3 10.568 0.139 0.139 0.251 0.251
78 IM2 ~~ IM3 13.696 0.164 0.164 0.549 0.549$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.074 0.000
EEC3 0.012 0.008 0.000
EEF1 0.103 -0.002 -0.025 0.000
EEF2 0.088 0.047 -0.047 0.006 0.000
EEF3 0.081 0.032 -0.004 0.001 -0.007 0.000
IM1 0.160 0.176 0.111 0.046 0.067 0.067 0.000
IM2 0.021 -0.032 -0.135 -0.041 0.010 0.006 -0.015 0.000
IM3 0.169 -0.018 -0.064 -0.109 -0.057 -0.001 -0.017 0.032 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -1.657 0.000
EEC3 0.296 0.106 0.000
EEF1 1.439 -0.028 -0.396 0.000
EEF2 1.443 0.760 -0.839 0.197 0.000
EEF3 1.210 0.552 -0.073 0.023 -0.303 0.000
IM1 2.243 2.603 1.832 0.778 1.206 1.180 0.000
IM2 0.379 -0.726 -2.701 -0.720 0.287 0.136 -0.991 0.000
IM3 1.832 -0.323 -1.299 -2.232 -1.388 -0.034 -0.812 1.479 0.000Allowing covariance between IM2 and IM3lavaan 0.6-21 ended normally after 33 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 22
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 51.906 40.807
Degrees of freedom 23 23
P-value (Chi-square) 0.001 0.012
Scaling correction factor 1.272
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1540.967 832.018
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.852
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.981 0.978
Tucker-Lewis Index (TLI) 0.970 0.965
Robust Comparative Fit Index (CFI) 0.985
Robust Tucker-Lewis Index (TLI) 0.976
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2521.625 -2521.625
Scaling correction factor 2.243
for the MLR correction
Loglikelihood unrestricted model (H1) -2495.672 -2495.672
Scaling correction factor 1.747
for the MLR correction
Akaike (AIC) 5087.250 5087.250
Bayesian (BIC) 5163.267 5163.267
Sample-size adjusted Bayesian (SABIC) 5093.537 5093.537
Root Mean Square Error of Approximation:
RMSEA 0.073 0.058
90 Percent confidence interval - lower 0.047 0.031
90 Percent confidence interval - upper 0.100 0.083
P-value H_0: RMSEA <= 0.050 0.072 0.292
P-value H_0: RMSEA >= 0.080 0.363 0.073
Robust RMSEA 0.065
90 Percent confidence interval - lower 0.030
90 Percent confidence interval - upper 0.097
P-value H_0: Robust RMSEA <= 0.050 0.209
P-value H_0: Robust RMSEA >= 0.080 0.237
Standardized Root Mean Square Residual:
SRMR 0.038 0.038
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 1.274 0.105 12.173 0.000 1.069 1.479
EEC3 1.353 0.091 14.854 0.000 1.175 1.532
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.983 0.051 19.403 0.000 0.883 1.082
EEF3 0.949 0.044 21.584 0.000 0.863 1.036
IM =~
IM1 1.000 1.000 1.000
IM2 0.633 0.104 6.091 0.000 0.429 0.837
IM3 0.697 0.101 6.895 0.000 0.499 0.895
Std.lv Std.all
0.966 0.723
1.230 0.871
1.307 0.945
1.057 0.910
1.038 0.910
1.003 0.898
0.946 0.907
0.598 0.710
0.659 0.683
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.151 0.064 2.354 0.019 0.025 0.277
EEC ~~
EEF 0.642 0.105 6.097 0.000 0.435 0.848
IM 0.502 0.095 5.288 0.000 0.316 0.688
EEF ~~
IM 0.629 0.093 6.763 0.000 0.447 0.812
Std.lv Std.all
0.151 0.361
0.629 0.629
0.549 0.549
0.630 0.630
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.851 0.096 8.879 0.000 0.663 1.038
.EEC2 0.482 0.097 4.955 0.000 0.292 0.673
.EEC3 0.203 0.062 3.262 0.001 0.081 0.325
.EEF1 0.232 0.051 4.553 0.000 0.132 0.332
.EEF2 0.223 0.043 5.213 0.000 0.139 0.306
.EEF3 0.243 0.057 4.252 0.000 0.131 0.355
.IM1 0.194 0.078 2.479 0.013 0.041 0.347
.IM2 0.352 0.079 4.436 0.000 0.196 0.507
.IM3 0.498 0.168 2.955 0.003 0.168 0.828
EEC 0.933 0.143 6.546 0.000 0.654 1.212
EEF 1.117 0.169 6.608 0.000 0.785 1.448
IM 0.894 0.143 6.248 0.000 0.614 1.175
Std.lv Std.all
0.851 0.477
0.482 0.242
0.203 0.106
0.232 0.172
0.223 0.171
0.243 0.194
0.194 0.178
0.352 0.496
0.498 0.534
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.523
EEC2 0.758
EEC3 0.894
EEF1 0.828
EEF2 0.829
EEF3 0.806
IM1 0.822
IM2 0.504
IM3 0.466Cronbach’s Alpha: EEC EEF IM
0.877 0.932 0.840 Omega: EEC EEF IM
0.896 0.932 0.783 Average Variance Extracted (AVE): EEC EEF IM
0.730 0.821 0.618 Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 10.531 0.137 0.137 0.211 0.211Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 10.531 0.137 0.137 0.211 0.211$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.074 0.000
EEC3 0.013 0.007 0.000
EEF1 0.102 -0.004 -0.026 0.000
EEF2 0.089 0.047 -0.047 0.004 0.000
EEF3 0.082 0.033 -0.003 0.000 -0.005 0.000
IM1 0.073 0.065 -0.007 -0.026 -0.003 0.001 0.000
IM2 0.035 -0.014 -0.116 0.007 0.058 0.053 -0.001 0.000
IM3 0.187 0.004 -0.041 -0.055 -0.002 0.052 0.001 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -2.685 0.000
EEC3 0.522 0.423 0.000
EEF1 1.613 -0.083 -0.745 0.000
EEF2 1.492 1.009 -1.342 0.223 0.000
EEF3 1.319 0.763 -0.070 0.021 -0.328 0.000
IM1 1.160 1.674 -0.370 -0.994 -0.104 0.018 0.000
IM2 0.613 -0.357 -2.498 0.151 1.552 1.438 -0.043 0.000
IM3 1.907 0.061 -0.743 -1.423 -0.052 1.568 0.047 0.000 0.000Allowing 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 234
Model Test User Model:
Standard Scaled
Test Statistic 41.159 31.684
Degrees of freedom 22 22
P-value (Chi-square) 0.008 0.083
Scaling correction factor 1.299
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1540.967 832.018
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.852
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.987 0.988
Tucker-Lewis Index (TLI) 0.979 0.980
Robust Comparative Fit Index (CFI) 0.991
Robust Tucker-Lewis Index (TLI) 0.986
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2516.251 -2516.251
Scaling correction factor 2.175
for the MLR correction
Loglikelihood unrestricted model (H1) -2495.672 -2495.672
Scaling correction factor 1.747
for the MLR correction
Akaike (AIC) 5078.502 5078.502
Bayesian (BIC) 5157.975 5157.975
Sample-size adjusted Bayesian (SABIC) 5085.075 5085.075
Root Mean Square Error of Approximation:
RMSEA 0.061 0.043
90 Percent confidence interval - lower 0.031 0.000
90 Percent confidence interval - upper 0.090 0.071
P-value H_0: RMSEA <= 0.050 0.243 0.620
P-value H_0: RMSEA >= 0.080 0.146 0.012
Robust RMSEA 0.049
90 Percent confidence interval - lower 0.000
90 Percent confidence interval - upper 0.085
P-value H_0: Robust RMSEA <= 0.050 0.474
P-value H_0: Robust RMSEA >= 0.080 0.085
Standardized Root Mean Square Residual:
SRMR 0.030 0.030
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 1.247 0.099 12.639 0.000 1.054 1.441
EEC3 1.189 0.104 11.413 0.000 0.985 1.393
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.985 0.051 19.442 0.000 0.886 1.084
EEF3 0.949 0.044 21.618 0.000 0.863 1.036
IM =~
IM1 1.000 1.000 1.000
IM2 0.643 0.100 6.440 0.000 0.448 0.839
IM3 0.709 0.098 7.231 0.000 0.517 0.901
Std.lv Std.all
1.041 0.780
1.299 0.919
1.238 0.895
1.056 0.909
1.040 0.912
1.002 0.897
0.938 0.899
0.603 0.716
0.665 0.689
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.144 0.063 2.285 0.022 0.021 0.268
.EEC1 ~~
.EEC2 -0.239 0.074 -3.243 0.001 -0.383 -0.094
EEC ~~
EEF 0.696 0.107 6.508 0.000 0.487 0.906
IM 0.555 0.095 5.859 0.000 0.370 0.741
EEF ~~
IM 0.627 0.093 6.742 0.000 0.445 0.810
Std.lv Std.all
0.144 0.351
-0.239 -0.514
0.633 0.633
0.569 0.569
0.633 0.633
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.699 0.117 5.963 0.000 0.469 0.929
.EEC2 0.309 0.110 2.809 0.005 0.093 0.524
.EEC3 0.379 0.090 4.221 0.000 0.203 0.555
.EEF1 0.234 0.051 4.586 0.000 0.134 0.334
.EEF2 0.219 0.042 5.263 0.000 0.138 0.301
.EEF3 0.245 0.058 4.221 0.000 0.131 0.358
.IM1 0.209 0.074 2.829 0.005 0.064 0.353
.IM2 0.346 0.078 4.450 0.000 0.194 0.498
.IM3 0.490 0.167 2.938 0.003 0.163 0.817
EEC 1.084 0.163 6.657 0.000 0.765 1.404
EEF 1.115 0.169 6.599 0.000 0.784 1.446
IM 0.879 0.136 6.484 0.000 0.614 1.145
Std.lv Std.all
0.699 0.392
0.309 0.155
0.379 0.198
0.234 0.174
0.219 0.169
0.245 0.196
0.209 0.192
0.346 0.487
0.490 0.526
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.608
EEC2 0.845
EEC3 0.802
EEF1 0.826
EEF2 0.831
EEF3 0.804
IM1 0.808
IM2 0.513
IM3 0.474Cronbach’s Alpha: EEC EEF IM
0.877 0.932 0.840 Omega: EEC EEF IM
0.935 0.932 0.785 Average Variance Extracted (AVE): EEC EEF IM
0.756 0.821 0.617 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"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.013 0.007 0.000
EEF1 0.047 -0.055 0.014 0.000
EEF2 0.033 -0.006 -0.009 0.004 0.000
EEF3 0.030 -0.016 0.036 0.002 -0.006 0.000
IM1 0.020 0.012 0.012 -0.024 -0.002 0.003 0.000
IM2 -0.004 -0.055 -0.111 0.002 0.052 0.048 0.000 0.000
IM3 0.143 -0.042 -0.036 -0.061 -0.009 0.046 0.001 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.519 0.394 0.000
EEF1 0.917 -1.218 0.398 0.000
EEF2 0.681 -0.144 -0.270 0.242 0.000
EEF3 0.582 -0.393 0.924 0.172 -0.587 0.000
IM1 0.347 0.405 0.388 -1.001 -0.076 0.103 0.000
IM2 -0.075 -1.546 -2.566 0.035 1.361 1.304 -0.053 0.000
IM3 1.425 -0.705 -0.703 -1.536 -0.210 1.386 0.047 0.000 0.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC
IM "1" "0.63 (0)" "0.57 (0)"
EEF "0.63 (0)" "1" "0.63 (0)"
EEC "0.57 (0)" "0.63 (0)" "1" Discriminant validity check lhs op rhs est.std se z pvalue ci.lower ci.upper
1 EEC =~ EEC1 0.780 0.042 18.777 0 0.698 0.861
2 EEC =~ EEC2 0.919 0.030 30.328 0 0.860 0.979
3 EEC =~ EEC3 0.895 0.028 31.680 0 0.840 0.951
4 EEF =~ EEF1 0.909 0.022 42.056 0 0.867 0.951
5 EEF =~ EEF2 0.912 0.019 48.876 0 0.875 0.948
6 EEF =~ EEF3 0.897 0.029 30.821 0 0.840 0.954
7 IM =~ IM1 0.899 0.039 22.883 0 0.822 0.976
8 IM =~ IM2 0.716 0.071 10.021 0 0.576 0.856
9 IM =~ IM3 0.689 0.093 7.426 0 0.507 0.871AVE (IM, EEF, EEC)[1] 0.5984496[1] 0.8206829[1] 0.7517229Square root of AVE (IM, EEF, EEC)[1] 0.7735952[1] 0.9059155[1] 0.8670195 lhs rhs est.std
24 EEC EEF 0.633
25 EEC IM 0.569
26 EEF IM 0.633Correlations between square root AVE with correlations (sqrt vs. correlations with the other constructsIM[1] 0.7735952[1] 0.6334666[1] 0.5686249EEF[1] 0.9059155[1] 0.6334666[1] 0.6333929EEC[1] 0.8670195[1] 0.5686249[1] 0.6333929lavaan 0.6-21 ended normally after 49 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 124.000 106.249
Degrees of freedom 79 79
P-value (Chi-square) 0.001 0.022
Scaling correction factor 1.167
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2762.603 1876.548
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.472
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.983 0.985
Tucker-Lewis Index (TLI) 0.977 0.980
Robust Comparative Fit Index (CFI) 0.988
Robust Tucker-Lewis Index (TLI) 0.984
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4230.781 -4230.781
Scaling correction factor 1.920
for the MLR correction
Loglikelihood unrestricted model (H1) -4168.781 -4168.781
Scaling correction factor 1.424
for the MLR correction
Akaike (AIC) 8543.562 8543.562
Bayesian (BIC) 8685.230 8685.230
Sample-size adjusted Bayesian (SABIC) 8555.278 8555.278
Root Mean Square Error of Approximation:
RMSEA 0.049 0.038
90 Percent confidence interval - lower 0.032 0.018
90 Percent confidence interval - upper 0.065 0.055
P-value H_0: RMSEA <= 0.050 0.508 0.869
P-value H_0: RMSEA >= 0.080 0.001 0.000
Robust RMSEA 0.041
90 Percent confidence interval - lower 0.017
90 Percent confidence interval - upper 0.061
P-value H_0: Robust RMSEA <= 0.050 0.749
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.039 0.039
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 0.631 0.108 5.870 0.000 0.421 0.842
IM3 0.696 0.104 6.716 0.000 0.493 0.899
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.981 0.051 19.164 0.000 0.881 1.082
EEF3 0.949 0.044 21.508 0.000 0.862 1.035
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.272 0.104 12.229 0.000 1.068 1.476
EEC3 1.360 0.092 14.772 0.000 1.179 1.540
TR =~
TR1 1.000 1.000 1.000
TR2 1.081 0.046 23.301 0.000 0.990 1.172
TR3 1.044 0.047 22.200 0.000 0.952 1.136
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.081 0.081 13.352 0.000 0.923 1.240
ADT3 1.103 0.078 14.070 0.000 0.950 1.257
Std.lv Std.all
0.947 0.908
0.598 0.709
0.659 0.682
1.058 0.910
1.038 0.910
1.003 0.897
0.964 0.722
1.227 0.868
1.311 0.948
1.316 0.889
1.423 0.937
1.374 0.921
0.829 0.845
0.896 0.899
0.914 0.861
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.152 0.066 2.313 0.021 0.023 0.281
IM ~~
EEF 0.630 0.093 6.738 0.000 0.447 0.813
EEC 0.500 0.096 5.231 0.000 0.312 0.687
TR 0.306 0.111 2.751 0.006 0.088 0.524
ADT 0.173 0.071 2.428 0.015 0.033 0.313
EEF ~~
EEC 0.639 0.105 6.073 0.000 0.433 0.846
TR 0.345 0.113 3.055 0.002 0.123 0.566
ADT 0.304 0.078 3.903 0.000 0.151 0.456
EEC ~~
TR 0.385 0.102 3.792 0.000 0.186 0.584
ADT 0.272 0.069 3.957 0.000 0.137 0.406
TR ~~
ADT 0.440 0.089 4.919 0.000 0.264 0.615
Std.lv Std.all
0.152 0.362
0.629 0.629
0.547 0.547
0.246 0.246
0.221 0.221
0.627 0.627
0.248 0.248
0.347 0.347
0.303 0.303
0.340 0.340
0.403 0.403
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.192 0.084 2.282 0.023 0.027 0.357
.IM2 0.353 0.080 4.398 0.000 0.196 0.510
.IM3 0.498 0.167 2.982 0.003 0.171 0.826
.EEF1 0.231 0.051 4.482 0.000 0.130 0.332
.EEF2 0.224 0.043 5.196 0.000 0.139 0.308
.EEF3 0.243 0.057 4.272 0.000 0.132 0.355
.EEC1 0.853 0.095 8.944 0.000 0.666 1.040
.EEC2 0.490 0.098 5.010 0.000 0.299 0.682
.EEC3 0.192 0.063 3.060 0.002 0.069 0.315
.TR1 0.458 0.077 5.980 0.000 0.308 0.608
.TR2 0.283 0.068 4.180 0.000 0.150 0.416
.TR3 0.336 0.083 4.053 0.000 0.174 0.499
.ADT1 0.275 0.062 4.453 0.000 0.154 0.396
.ADT2 0.190 0.049 3.853 0.000 0.094 0.287
.ADT3 0.292 0.078 3.729 0.000 0.139 0.446
IM 0.896 0.149 6.014 0.000 0.604 1.188
EEF 1.118 0.169 6.600 0.000 0.786 1.450
EEC 0.930 0.142 6.551 0.000 0.652 1.208
TR 1.732 0.166 10.422 0.000 1.407 2.058
ADT 0.687 0.091 7.570 0.000 0.509 0.864
Std.lv Std.all
0.192 0.176
0.353 0.497
0.498 0.534
0.231 0.171
0.224 0.172
0.243 0.195
0.853 0.478
0.490 0.246
0.192 0.100
0.458 0.209
0.283 0.123
0.336 0.151
0.275 0.286
0.190 0.192
0.292 0.259
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.824
IM2 0.503
IM3 0.466
EEF1 0.829
EEF2 0.828
EEF3 0.805
EEC1 0.522
EEC2 0.754
EEC3 0.900
TR1 0.791
TR2 0.877
TR3 0.849
ADT1 0.714
ADT2 0.808
ADT3 0.741Cronbach’s Alpha: IM EEF EEC TR ADT
0.840 0.932 0.877 0.939 0.900 Omega: IM EEF EEC TR ADT
0.783 0.932 0.895 0.941 0.903 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.618 0.821 0.730 0.840 0.754 $type
[1] "cor.bentler"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.000 0.000
IM3 0.001 0.000 0.000
EEF1 -0.022 0.008 -0.048 0.000
EEF2 -0.002 0.062 -0.001 0.003 0.000
EEF3 0.000 0.057 0.049 0.000 -0.004 0.000
EEC1 0.054 0.033 0.146 0.067 0.060 0.057 0.000
EEC2 0.047 -0.009 0.005 0.000 0.032 0.024 -0.037 0.000
EEC3 -0.005 -0.098 -0.030 -0.017 -0.030 -0.002 0.006 0.003 0.000
TR1 0.029 -0.028 0.019 0.050 -0.006 0.020 0.051 0.026 0.071 0.000
TR2 0.011 -0.076 -0.034 -0.026 -0.062 -0.005 -0.057 -0.069 -0.009 0.001
TR3 0.005 -0.040 -0.001 0.044 -0.013 0.048 -0.004 -0.052 0.013 -0.005
ADT1 0.110 0.003 0.028 0.059 0.065 0.062 0.035 0.058 0.056 0.037
ADT2 -0.037 -0.102 -0.067 -0.038 -0.060 -0.036 -0.021 -0.015 -0.035 -0.005
ADT3 0.009 -0.039 -0.024 0.038 -0.002 -0.013 -0.007 0.031 -0.022 0.026
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.002 0.000
ADT1 0.015 0.043 0.000
ADT2 -0.037 -0.023 0.001 0.000
ADT3 -0.032 0.046 -0.012 0.007 0.000
$cov.z
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.014 0.000
IM3 0.017 0.000 0.000
EEF1 -0.670 0.159 -1.150 0.000
EEF2 -0.075 1.311 -0.027 0.112 0.000
EEF3 0.013 1.233 1.361 -0.006 -0.146 0.000
EEC1 1.104 0.612 1.803 1.474 1.434 1.276 0.000
EEC2 1.520 -0.240 0.095 0.000 1.020 0.713 -1.291 0.000
EEC3 -0.188 -2.336 -0.590 -0.592 -1.013 -0.058 0.224 0.125 0.000
TR1 0.806 -0.706 0.292 1.399 -0.194 0.535 1.016 0.683 2.160 0.000
TR2 0.349 -1.768 -0.672 -0.761 -2.212 -0.146 -1.157 -1.892 -0.427 0.046
TR3 0.147 -0.924 -0.010 1.387 -0.393 1.348 -0.075 -1.374 0.512 -0.188
ADT1 2.789 0.055 0.593 1.466 1.617 1.647 0.707 1.360 1.932 0.776
ADT2 -1.192 -2.071 -1.339 -1.173 -1.766 -1.131 -0.473 -0.423 -1.529 -0.158
ADT3 0.258 -0.929 -0.423 1.032 -0.058 -0.367 -0.169 0.802 -0.786 0.707
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.067 0.000
ADT1 0.391 1.004 0.000
ADT2 -1.377 -0.688 0.077 0.000
ADT3 -0.923 1.306 -0.658 0.389 0.000
$summary
cov
srmr 0.039
srmr.se 0.007
srmr.exactfit.z 0.178
srmr.exactfit.pvalue 0.430
usrmr 0.007
usrmr.se 0.008
usrmr.ci.lower -0.007
usrmr.ci.upper 0.021
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -5.206
usrmr.closefit.pvalue 1.000 IM EEF EEC TR ADT
IM 1.000
EEF 0.629 1.000
EEC 0.547 0.627 1.000
TR 0.246 0.248 0.303 1.000
ADT 0.221 0.347 0.340 0.403 1.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC TR ADT
IM "1" "0.63 (0)" "0.55 (0)" "0.25 (0.002)" "0.22 (0.004)"
EEF "0.63 (0)" "1" "0.63 (0)" "0.25 (0)" "0.35 (0)"
EEC "0.55 (0)" "0.63 (0)" "1" "0.3 (0)" "0.34 (0)"
TR "0.25 (0.002)" "0.25 (0)" "0.3 (0)" "1" "0.4 (0)"
ADT "0.22 (0.004)" "0.35 (0)" "0.34 (0)" "0.4 (0)" "1" Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
56 IM =~ ADT1 10.291 0.150 0.142 0.145 0.145
136 IM3 ~~ EEC1 10.508 0.137 0.137 0.210 0.210Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 10.508 0.137 0.137 0.21 0.21$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.000 0.000
IM3 0.001 0.000 0.000
EEF1 -0.026 0.007 -0.054 0.000
EEF2 -0.003 0.059 -0.001 0.004 0.000
EEF3 0.001 0.054 0.052 0.000 -0.004 0.000
EEC1 0.075 0.038 0.189 0.104 0.092 0.085 0.000
EEC2 0.069 -0.011 0.007 0.000 0.051 0.037 -0.069 0.000
EEC3 -0.007 -0.115 -0.040 -0.027 -0.047 -0.003 0.011 0.006 0.000
TR1 0.044 -0.035 0.028 0.086 -0.010 0.033 0.101 0.055 0.146 0.000
TR2 0.017 -0.098 -0.049 -0.046 -0.108 -0.008 -0.116 -0.148 -0.019 0.002
TR3 0.007 -0.050 -0.001 0.075 -0.022 0.080 -0.007 -0.110 0.027 -0.010
ADT1 0.112 0.002 0.026 0.067 0.072 0.068 0.045 0.080 0.076 0.053
ADT2 -0.038 -0.086 -0.064 -0.043 -0.068 -0.040 -0.028 -0.021 -0.048 -0.008
ADT3 0.010 -0.035 -0.025 0.047 -0.003 -0.016 -0.011 0.046 -0.033 0.041
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.004 0.000
ADT1 0.023 0.063 0.000
ADT2 -0.056 -0.033 0.001 0.000
ADT3 -0.051 0.072 -0.013 0.007 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.014 0.000
IM3 0.017 0.000 0.000
EEF1 -0.670 0.159 -1.150 0.000
EEF2 -0.075 1.311 -0.027 0.112 0.000
EEF3 0.013 1.233 1.361 -0.006 -0.146 0.000
EEC1 1.104 0.612 1.803 1.474 1.434 1.276 0.000
EEC2 1.520 -0.240 0.095 0.002 1.020 0.713 -1.291 0.000
EEC3 -0.188 -2.336 -0.590 -0.592 -1.013 -0.058 0.224 0.125 0.000
TR1 0.806 -0.706 0.292 1.399 -0.194 0.535 1.016 0.683 2.160 0.000
TR2 0.349 -1.768 -0.672 -0.761 -2.212 -0.146 -1.157 -1.892 -0.427 0.046
TR3 0.147 -0.924 -0.010 1.387 -0.393 1.348 -0.075 -1.374 0.512 -0.188
ADT1 2.789 0.055 0.593 1.466 1.617 1.647 0.707 1.360 1.932 0.776
ADT2 -1.192 -2.071 -1.339 -1.173 -1.766 -1.131 -0.473 -0.423 -1.529 -0.158
ADT3 0.258 -0.929 -0.423 1.032 -0.058 -0.367 -0.169 0.802 -0.786 0.707
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.067 0.000
ADT1 0.391 1.004 0.000
ADT2 -1.377 -0.688 0.077 0.000
ADT3 -0.923 1.306 -0.658 0.389 0.000lavaan 0.6-21 ended normally after 49 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 124.000 106.249
Degrees of freedom 79 79
P-value (Chi-square) 0.001 0.022
Scaling correction factor 1.167
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2762.603 1876.548
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.472
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.983 0.985
Tucker-Lewis Index (TLI) 0.977 0.980
Robust Comparative Fit Index (CFI) 0.988
Robust Tucker-Lewis Index (TLI) 0.984
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4230.781 -4230.781
Scaling correction factor 1.920
for the MLR correction
Loglikelihood unrestricted model (H1) -4168.781 -4168.781
Scaling correction factor 1.424
for the MLR correction
Akaike (AIC) 8543.562 8543.562
Bayesian (BIC) 8685.230 8685.230
Sample-size adjusted Bayesian (SABIC) 8555.278 8555.278
Root Mean Square Error of Approximation:
RMSEA 0.049 0.038
90 Percent confidence interval - lower 0.032 0.018
90 Percent confidence interval - upper 0.065 0.055
P-value H_0: RMSEA <= 0.050 0.508 0.869
P-value H_0: RMSEA >= 0.080 0.001 0.000
Robust RMSEA 0.041
90 Percent confidence interval - lower 0.017
90 Percent confidence interval - upper 0.061
P-value H_0: Robust RMSEA <= 0.050 0.749
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.039 0.039
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 0.631 0.108 5.870 0.000 0.421 0.842
IM3 0.696 0.104 6.716 0.000 0.493 0.899
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.981 0.051 19.164 0.000 0.881 1.082
EEF3 0.949 0.044 21.508 0.000 0.862 1.035
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.272 0.104 12.229 0.000 1.068 1.476
EEC3 1.360 0.092 14.772 0.000 1.179 1.540
TR =~
TR1 1.000 1.000 1.000
TR2 1.081 0.046 23.301 0.000 0.990 1.172
TR3 1.044 0.047 22.200 0.000 0.952 1.136
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.081 0.081 13.352 0.000 0.923 1.240
ADT3 1.103 0.078 14.070 0.000 0.950 1.257
Std.lv Std.all
0.947 0.908
0.598 0.709
0.659 0.682
1.058 0.910
1.038 0.910
1.003 0.897
0.964 0.722
1.227 0.868
1.311 0.948
1.316 0.889
1.423 0.937
1.374 0.921
0.829 0.845
0.896 0.899
0.914 0.861
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.152 0.066 2.313 0.021 0.023 0.281
IM ~~
EEF 0.630 0.093 6.738 0.000 0.447 0.813
EEC 0.500 0.096 5.231 0.000 0.312 0.687
TR 0.306 0.111 2.751 0.006 0.088 0.524
ADT 0.173 0.071 2.428 0.015 0.033 0.313
EEF ~~
EEC 0.639 0.105 6.073 0.000 0.433 0.846
TR 0.345 0.113 3.055 0.002 0.123 0.566
ADT 0.304 0.078 3.903 0.000 0.151 0.456
EEC ~~
TR 0.385 0.102 3.792 0.000 0.186 0.584
ADT 0.272 0.069 3.957 0.000 0.137 0.406
TR ~~
ADT 0.440 0.089 4.919 0.000 0.264 0.615
Std.lv Std.all
0.152 0.362
0.629 0.629
0.547 0.547
0.246 0.246
0.221 0.221
0.627 0.627
0.248 0.248
0.347 0.347
0.303 0.303
0.340 0.340
0.403 0.403
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.192 0.084 2.282 0.023 0.027 0.357
.IM2 0.353 0.080 4.398 0.000 0.196 0.510
.IM3 0.498 0.167 2.982 0.003 0.171 0.826
.EEF1 0.231 0.051 4.482 0.000 0.130 0.332
.EEF2 0.224 0.043 5.196 0.000 0.139 0.308
.EEF3 0.243 0.057 4.272 0.000 0.132 0.355
.EEC1 0.853 0.095 8.944 0.000 0.666 1.040
.EEC2 0.490 0.098 5.010 0.000 0.299 0.682
.EEC3 0.192 0.063 3.060 0.002 0.069 0.315
.TR1 0.458 0.077 5.980 0.000 0.308 0.608
.TR2 0.283 0.068 4.180 0.000 0.150 0.416
.TR3 0.336 0.083 4.053 0.000 0.174 0.499
.ADT1 0.275 0.062 4.453 0.000 0.154 0.396
.ADT2 0.190 0.049 3.853 0.000 0.094 0.287
.ADT3 0.292 0.078 3.729 0.000 0.139 0.446
IM 0.896 0.149 6.014 0.000 0.604 1.188
EEF 1.118 0.169 6.600 0.000 0.786 1.450
EEC 0.930 0.142 6.551 0.000 0.652 1.208
TR 1.732 0.166 10.422 0.000 1.407 2.058
ADT 0.687 0.091 7.570 0.000 0.509 0.864
Std.lv Std.all
0.192 0.176
0.353 0.497
0.498 0.534
0.231 0.171
0.224 0.172
0.243 0.195
0.853 0.478
0.490 0.246
0.192 0.100
0.458 0.209
0.283 0.123
0.336 0.151
0.275 0.286
0.190 0.192
0.292 0.259
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.824
IM2 0.503
IM3 0.466
EEF1 0.829
EEF2 0.828
EEF3 0.805
EEC1 0.522
EEC2 0.754
EEC3 0.900
TR1 0.791
TR2 0.877
TR3 0.849
ADT1 0.714
ADT2 0.808
ADT3 0.741Cronbach’s Alpha: IM EEF EEC TR ADT
0.840 0.932 0.877 0.939 0.900 Omega: IM EEF EEC TR ADT
0.783 0.932 0.895 0.941 0.903 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.618 0.821 0.730 0.840 0.754 Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
56 IM =~ ADT1 10.291 0.150 0.142 0.145 0.145
136 IM3 ~~ EEC1 10.508 0.137 0.137 0.210 0.210Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 10.508 0.137 0.137 0.21 0.21$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.000 0.000
IM3 0.001 0.000 0.000
EEF1 -0.026 0.007 -0.054 0.000
EEF2 -0.003 0.059 -0.001 0.004 0.000
EEF3 0.001 0.054 0.052 0.000 -0.004 0.000
EEC1 0.075 0.038 0.189 0.104 0.092 0.085 0.000
EEC2 0.069 -0.011 0.007 0.000 0.051 0.037 -0.069 0.000
EEC3 -0.007 -0.115 -0.040 -0.027 -0.047 -0.003 0.011 0.006 0.000
TR1 0.044 -0.035 0.028 0.086 -0.010 0.033 0.101 0.055 0.146 0.000
TR2 0.017 -0.098 -0.049 -0.046 -0.108 -0.008 -0.116 -0.148 -0.019 0.002
TR3 0.007 -0.050 -0.001 0.075 -0.022 0.080 -0.007 -0.110 0.027 -0.010
ADT1 0.112 0.002 0.026 0.067 0.072 0.068 0.045 0.080 0.076 0.053
ADT2 -0.038 -0.086 -0.064 -0.043 -0.068 -0.040 -0.028 -0.021 -0.048 -0.008
ADT3 0.010 -0.035 -0.025 0.047 -0.003 -0.016 -0.011 0.046 -0.033 0.041
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.004 0.000
ADT1 0.023 0.063 0.000
ADT2 -0.056 -0.033 0.001 0.000
ADT3 -0.051 0.072 -0.013 0.007 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.014 0.000
IM3 0.017 0.000 0.000
EEF1 -0.670 0.159 -1.150 0.000
EEF2 -0.075 1.311 -0.027 0.112 0.000
EEF3 0.013 1.233 1.361 -0.006 -0.146 0.000
EEC1 1.104 0.612 1.803 1.474 1.434 1.276 0.000
EEC2 1.520 -0.240 0.095 0.002 1.020 0.713 -1.291 0.000
EEC3 -0.188 -2.336 -0.590 -0.592 -1.013 -0.058 0.224 0.125 0.000
TR1 0.806 -0.706 0.292 1.399 -0.194 0.535 1.016 0.683 2.160 0.000
TR2 0.349 -1.768 -0.672 -0.761 -2.212 -0.146 -1.157 -1.892 -0.427 0.046
TR3 0.147 -0.924 -0.010 1.387 -0.393 1.348 -0.075 -1.374 0.512 -0.188
ADT1 2.789 0.055 0.593 1.466 1.617 1.647 0.707 1.360 1.932 0.776
ADT2 -1.192 -2.071 -1.339 -1.173 -1.766 -1.131 -0.473 -0.423 -1.529 -0.158
ADT3 0.258 -0.929 -0.423 1.032 -0.058 -0.367 -0.169 0.802 -0.786 0.707
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.067 0.000
ADT1 0.391 1.004 0.000
ADT2 -1.377 -0.688 0.077 0.000
ADT3 -0.923 1.306 -0.658 0.389 0.000lavaan 0.6-21 ended normally after 69 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 126
0 108
Model Test User Model:
Standard Scaled
Test Statistic 231.988 221.046
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.050
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 106.383 106.383
0 114.663 114.663
Model Test Baseline Model:
Test statistic 2453.821 1892.728
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.296
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.967 0.963
Tucker-Lewis Index (TLI) 0.956 0.950
Robust Comparative Fit Index (CFI) 0.970
Robust Tucker-Lewis Index (TLI) 0.960
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4046.771 -4046.771
Scaling correction factor 1.521
for the MLR correction
Loglikelihood unrestricted model (H1) -3930.777 -3930.777
Scaling correction factor 1.245
for the MLR correction
Akaike (AIC) 8317.543 8317.543
Bayesian (BIC) 8704.538 8704.538
Sample-size adjusted Bayesian (SABIC) 8349.550 8349.550
Root Mean Square Error of Approximation:
RMSEA 0.063 0.058
90 Percent confidence interval - lower 0.045 0.039
90 Percent confidence interval - upper 0.080 0.075
P-value H_0: RMSEA <= 0.050 0.110 0.216
P-value H_0: RMSEA >= 0.080 0.052 0.017
Robust RMSEA 0.060
90 Percent confidence interval - lower 0.040
90 Percent confidence interval - upper 0.078
P-value H_0: Robust RMSEA <= 0.050 0.193
P-value H_0: Robust RMSEA >= 0.080 0.030
Standardized Root Mean Square Residual:
SRMR 0.057 0.057
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 0.857 0.847
IM2 0.773 0.137 5.632 0.000 0.662 0.778
IM3 0.771 0.118 6.513 0.000 0.661 0.639
EEF =~
EEF1 1.000 0.893 0.886
EEF2 1.006 0.073 13.804 0.000 0.898 0.900
EEF3 0.916 0.072 12.674 0.000 0.817 0.859
EEC =~
EEC1 1.000 1.041 0.743
EEC2 1.111 0.106 10.463 0.000 1.156 0.864
EEC3 1.210 0.106 11.397 0.000 1.259 0.934
TR =~
TR1 1.000 1.346 0.890
TR2 1.033 0.069 14.987 0.000 1.390 0.919
TR3 1.026 0.068 15.045 0.000 1.381 0.907
ADT =~
ADT1 1.000 0.382 0.613
ADT2 1.397 0.326 4.280 0.000 0.533 0.898
ADT3 1.048 0.271 3.865 0.000 0.400 0.635
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.089 0.056 1.577 0.115 0.089 0.209
IM ~~
EEF 0.496 0.082 6.034 0.000 0.649 0.649
EEC 0.483 0.117 4.136 0.000 0.542 0.542
TR 0.264 0.132 1.992 0.046 0.228 0.228
ADT 0.026 0.041 0.635 0.526 0.080 0.080
EEF ~~
EEC 0.584 0.116 5.047 0.000 0.629 0.629
TR 0.280 0.127 2.207 0.027 0.233 0.233
ADT 0.077 0.045 1.717 0.086 0.225 0.225
EEC ~~
TR 0.410 0.134 3.059 0.002 0.293 0.293
ADT 0.096 0.048 2.000 0.045 0.243 0.243
TR ~~
ADT 0.185 0.081 2.291 0.022 0.359 0.359
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.437 0.090 60.313 0.000 5.437 5.373
.IM2 5.881 0.076 77.587 0.000 5.881 6.912
.IM3 5.690 0.092 61.726 0.000 5.690 5.499
.EEF1 5.611 0.090 62.504 0.000 5.611 5.568
.EEF2 5.754 0.089 64.749 0.000 5.754 5.768
.EEF3 5.802 0.085 68.453 0.000 5.802 6.098
.EEC1 4.556 0.125 36.515 0.000 4.556 3.253
.EEC2 4.683 0.119 39.307 0.000 4.683 3.502
.EEC3 4.730 0.120 39.400 0.000 4.730 3.510
.TR1 4.175 0.135 30.986 0.000 4.175 2.760
.TR2 4.135 0.135 30.663 0.000 4.135 2.732
.TR3 3.873 0.136 28.560 0.000 3.873 2.544
.ADT1 6.095 0.055 109.875 0.000 6.095 9.788
.ADT2 6.071 0.053 114.863 0.000 6.071 10.233
.ADT3 6.087 0.056 108.427 0.000 6.087 9.659
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.290 0.101 2.866 0.004 0.290 0.283
.IM2 0.285 0.092 3.111 0.002 0.285 0.394
.IM3 0.634 0.302 2.101 0.036 0.634 0.592
.EEF1 0.219 0.074 2.959 0.003 0.219 0.215
.EEF2 0.189 0.058 3.255 0.001 0.189 0.190
.EEF3 0.237 0.066 3.578 0.000 0.237 0.262
.EEC1 0.878 0.148 5.934 0.000 0.878 0.448
.EEC2 0.452 0.126 3.588 0.000 0.452 0.253
.EEC3 0.230 0.091 2.537 0.011 0.230 0.127
.TR1 0.474 0.119 4.002 0.000 0.474 0.207
.TR2 0.358 0.113 3.168 0.002 0.358 0.156
.TR3 0.410 0.144 2.841 0.004 0.410 0.177
.ADT1 0.242 0.070 3.438 0.001 0.242 0.625
.ADT2 0.068 0.064 1.058 0.290 0.068 0.194
.ADT3 0.237 0.046 5.208 0.000 0.237 0.597
IM 0.734 0.133 5.499 0.000 1.000 1.000
EEF 0.797 0.147 5.409 0.000 1.000 1.000
EEC 1.083 0.200 5.412 0.000 1.000 1.000
TR 1.813 0.241 7.523 0.000 1.000 1.000
ADT 0.146 0.052 2.788 0.005 1.000 1.000
Group 2 [0]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM =~
IM1 1.000 0.946 0.910
IM2 0.583 0.169 3.446 0.001 0.551 0.671
IM3 0.703 0.188 3.745 0.000 0.665 0.768
EEF =~
EEF1 1.000 1.135 0.915
EEF2 0.969 0.072 13.524 0.000 1.099 0.906
EEF3 0.968 0.067 14.411 0.000 1.099 0.913
EEC =~
EEC1 1.000 0.805 0.670
EEC2 1.446 0.229 6.315 0.000 1.163 0.842
EEC3 1.617 0.201 8.046 0.000 1.301 0.972
TR =~
TR1 1.000 1.157 0.866
TR2 1.195 0.082 14.504 0.000 1.382 0.963
TR3 1.065 0.072 14.839 0.000 1.231 0.923
ADT =~
ADT1 1.000 0.452 0.656
ADT2 0.858 0.501 1.712 0.087 0.388 0.555
ADT3 0.962 0.641 1.502 0.133 0.435 0.589
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.181 0.112 1.613 0.107 0.181 0.537
IM ~~
EEF 0.666 0.152 4.375 0.000 0.620 0.620
EEC 0.389 0.138 2.827 0.005 0.511 0.511
TR 0.196 0.164 1.193 0.233 0.179 0.179
ADT 0.066 0.109 0.610 0.542 0.155 0.155
EEF ~~
EEC 0.507 0.154 3.291 0.001 0.555 0.555
TR 0.163 0.155 1.054 0.292 0.124 0.124
ADT 0.096 0.100 0.957 0.339 0.187 0.187
EEC ~~
TR 0.180 0.116 1.554 0.120 0.194 0.194
ADT 0.086 0.084 1.028 0.304 0.238 0.238
TR ~~
ADT 0.136 0.117 1.167 0.243 0.261 0.261
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.046 0.100 50.435 0.000 5.046 4.853
.IM2 5.694 0.079 72.021 0.000 5.694 6.930
.IM3 5.491 0.083 65.893 0.000 5.491 6.341
.EEF1 5.000 0.119 41.912 0.000 5.000 4.033
.EEF2 5.167 0.117 44.252 0.000 5.167 4.258
.EEF3 5.185 0.116 44.793 0.000 5.185 4.310
.EEC1 4.056 0.116 35.106 0.000 4.056 3.378
.EEC2 3.898 0.133 29.341 0.000 3.898 2.823
.EEC3 4.074 0.129 31.639 0.000 4.074 3.044
.TR1 3.435 0.128 26.737 0.000 3.435 2.573
.TR2 3.435 0.138 24.869 0.000 3.435 2.393
.TR3 3.083 0.128 24.017 0.000 3.083 2.311
.ADT1 4.630 0.066 69.887 0.000 4.630 6.725
.ADT2 4.546 0.067 67.592 0.000 4.546 6.504
.ADT3 4.454 0.071 62.744 0.000 4.454 6.038
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.186 0.136 1.373 0.170 0.186 0.172
.IM2 0.371 0.117 3.185 0.001 0.371 0.550
.IM3 0.308 0.122 2.530 0.011 0.308 0.410
.EEF1 0.250 0.065 3.826 0.000 0.250 0.162
.EEF2 0.264 0.062 4.238 0.000 0.264 0.180
.EEF3 0.240 0.102 2.363 0.018 0.240 0.166
.EEC1 0.794 0.101 7.830 0.000 0.794 0.551
.EEC2 0.554 0.156 3.541 0.000 0.554 0.291
.EEC3 0.099 0.094 1.055 0.291 0.099 0.055
.TR1 0.445 0.089 5.021 0.000 0.445 0.250
.TR2 0.150 0.060 2.482 0.013 0.150 0.073
.TR3 0.264 0.075 3.529 0.000 0.264 0.148
.ADT1 0.270 0.138 1.948 0.051 0.270 0.569
.ADT2 0.338 0.102 3.309 0.001 0.338 0.692
.ADT3 0.355 0.189 1.878 0.060 0.355 0.653
IM 0.895 0.256 3.492 0.000 1.000 1.000
EEF 1.287 0.277 4.647 0.000 1.000 1.000
EEC 0.647 0.191 3.386 0.001 1.000 1.000
TR 1.338 0.210 6.366 0.000 1.000 1.000
ADT 0.204 0.136 1.501 0.133 1.000 1.000lavaan 0.6-21 ended normally after 60 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 104
0 130
Model Test User Model:
Standard Scaled
Test Statistic 254.817 254.464
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.001
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 146.383 146.383
0 108.081 108.081
Model Test Baseline Model:
Test statistic 2401.542 1857.299
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.293
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.956 0.941
Tucker-Lewis Index (TLI) 0.941 0.922
Robust Comparative Fit Index (CFI) 0.955
Robust Tucker-Lewis Index (TLI) 0.940
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4004.732 -4004.732
Scaling correction factor 1.589
for the MLR correction
Loglikelihood unrestricted model (H1) -3877.323 -3877.323
Scaling correction factor 1.245
for the MLR correction
Akaike (AIC) 8233.463 8233.463
Bayesian (BIC) 8620.459 8620.459
Sample-size adjusted Bayesian (SABIC) 8265.471 8265.471
Root Mean Square Error of Approximation:
RMSEA 0.072 0.072
90 Percent confidence interval - lower 0.056 0.055
90 Percent confidence interval - upper 0.088 0.088
P-value H_0: RMSEA <= 0.050 0.016 0.017
P-value H_0: RMSEA >= 0.080 0.226 0.222
Robust RMSEA 0.072
90 Percent confidence interval - lower 0.055
90 Percent confidence interval - upper 0.088
P-value H_0: Robust RMSEA <= 0.050 0.017
P-value H_0: Robust RMSEA >= 0.080 0.224
Standardized Root Mean Square Residual:
SRMR 0.058 0.058
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 0.838 0.903
IM2 0.834 0.127 6.572 0.000 0.700 0.854
IM3 0.807 0.143 5.645 0.000 0.677 0.714
EEF =~
EEF1 1.000 0.891 0.912
EEF2 1.042 0.072 14.415 0.000 0.929 0.882
EEF3 0.901 0.092 9.786 0.000 0.803 0.840
EEC =~
EEC1 1.000 0.856 0.740
EEC2 1.213 0.167 7.253 0.000 1.038 0.814
EEC3 1.297 0.148 8.767 0.000 1.110 0.898
TR =~
TR1 1.000 0.301 0.392
TR2 1.318 0.393 3.355 0.001 0.397 0.711
TR3 1.853 0.713 2.598 0.009 0.558 0.804
ADT =~
ADT1 1.000 0.902 0.925
ADT2 0.957 0.080 11.934 0.000 0.863 0.917
ADT3 0.950 0.066 14.423 0.000 0.857 0.830
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.077 0.070 1.099 0.272 0.077 0.272
IM ~~
EEF 0.510 0.087 5.866 0.000 0.683 0.683
EEC 0.310 0.109 2.852 0.004 0.431 0.431
TR 0.005 0.045 0.116 0.908 0.021 0.021
ADT 0.151 0.102 1.479 0.139 0.200 0.200
EEF ~~
EEC 0.440 0.108 4.088 0.000 0.577 0.577
TR 0.041 0.038 1.075 0.282 0.154 0.154
ADT 0.257 0.102 2.523 0.012 0.319 0.319
EEC ~~
TR 0.046 0.048 0.957 0.339 0.176 0.176
ADT 0.259 0.095 2.728 0.006 0.336 0.336
TR ~~
ADT 0.105 0.056 1.886 0.059 0.385 0.385
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.442 0.091 59.777 0.000 5.442 5.862
.IM2 5.894 0.080 73.353 0.000 5.894 7.193
.IM3 5.750 0.093 61.844 0.000 5.750 6.064
.EEF1 5.577 0.096 58.179 0.000 5.577 5.705
.EEF2 5.663 0.103 54.872 0.000 5.663 5.381
.EEF3 5.760 0.094 61.459 0.000 5.760 6.027
.EEC1 4.587 0.113 40.426 0.000 4.587 3.964
.EEC2 4.663 0.125 37.283 0.000 4.663 3.656
.EEC3 4.827 0.121 39.826 0.000 4.827 3.905
.TR1 5.125 0.075 68.035 0.000 5.125 6.671
.TR2 5.231 0.055 95.480 0.000 5.231 9.363
.TR3 4.808 0.068 70.602 0.000 4.808 6.923
.ADT1 5.721 0.096 59.826 0.000 5.721 5.866
.ADT2 5.692 0.092 61.669 0.000 5.692 6.047
.ADT3 5.673 0.101 56.029 0.000 5.673 5.494
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.159 0.090 1.758 0.079 0.159 0.184
.IM2 0.182 0.067 2.705 0.007 0.182 0.271
.IM3 0.441 0.190 2.322 0.020 0.441 0.491
.EEF1 0.161 0.063 2.571 0.010 0.161 0.169
.EEF2 0.245 0.067 3.642 0.000 0.245 0.221
.EEF3 0.268 0.082 3.260 0.001 0.268 0.294
.EEC1 0.606 0.111 5.444 0.000 0.606 0.453
.EEC2 0.549 0.146 3.751 0.000 0.549 0.338
.EEC3 0.295 0.117 2.517 0.012 0.295 0.193
.TR1 0.499 0.120 4.169 0.000 0.499 0.846
.TR2 0.154 0.041 3.751 0.000 0.154 0.495
.TR3 0.171 0.101 1.688 0.091 0.171 0.354
.ADT1 0.137 0.053 2.589 0.010 0.137 0.144
.ADT2 0.141 0.054 2.628 0.009 0.141 0.159
.ADT3 0.332 0.154 2.161 0.031 0.332 0.312
IM 0.703 0.135 5.217 0.000 1.000 1.000
EEF 0.794 0.159 5.004 0.000 1.000 1.000
EEC 0.733 0.155 4.739 0.000 1.000 1.000
TR 0.091 0.063 1.434 0.152 1.000 1.000
ADT 0.814 0.135 6.029 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 0.978 0.885
IM2 0.543 0.134 4.036 0.000 0.530 0.622
IM3 0.658 0.135 4.873 0.000 0.644 0.669
EEF =~
EEF1 1.000 1.130 0.901
EEF2 0.979 0.062 15.799 0.000 1.106 0.932
EEF3 0.977 0.050 19.480 0.000 1.104 0.922
EEC =~
EEC1 1.000 1.000 0.700
EEC2 1.294 0.150 8.608 0.000 1.294 0.889
EEC3 1.367 0.124 10.997 0.000 1.367 0.970
TR =~
TR1 1.000 0.810 0.784
TR2 0.977 0.102 9.582 0.000 0.791 0.790
TR3 1.076 0.113 9.525 0.000 0.871 0.799
ADT =~
ADT1 1.000 0.684 0.747
ADT2 1.221 0.167 7.325 0.000 0.835 0.867
ADT3 1.272 0.173 7.343 0.000 0.870 0.865
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.179 0.092 1.937 0.053 0.179 0.375
IM ~~
EEF 0.650 0.140 4.647 0.000 0.588 0.588
EEC 0.591 0.142 4.149 0.000 0.604 0.604
TR 0.202 0.108 1.879 0.060 0.256 0.256
ADT 0.098 0.081 1.209 0.227 0.147 0.147
EEF ~~
EEC 0.704 0.160 4.408 0.000 0.623 0.623
TR 0.151 0.097 1.555 0.120 0.165 0.165
ADT 0.230 0.095 2.419 0.016 0.297 0.297
EEC ~~
TR 0.104 0.093 1.127 0.260 0.129 0.129
ADT 0.166 0.084 1.970 0.049 0.242 0.242
TR ~~
ADT 0.104 0.066 1.576 0.115 0.187 0.187
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.108 0.097 52.743 0.000 5.108 4.626
.IM2 5.715 0.075 76.444 0.000 5.715 6.705
.IM3 5.477 0.084 64.880 0.000 5.477 5.690
.EEF1 5.131 0.110 46.611 0.000 5.131 4.088
.EEF2 5.338 0.104 51.287 0.000 5.338 4.498
.EEF3 5.323 0.105 50.681 0.000 5.323 4.445
.EEC1 4.115 0.125 32.848 0.000 4.115 2.881
.EEC2 4.046 0.128 31.677 0.000 4.046 2.778
.EEC3 4.108 0.124 33.214 0.000 4.108 2.913
.TR1 2.800 0.091 30.896 0.000 2.800 2.710
.TR2 2.677 0.088 30.471 0.000 2.677 2.672
.TR3 2.469 0.096 25.835 0.000 2.469 2.266
.ADT1 5.177 0.080 64.482 0.000 5.177 5.655
.ADT2 5.108 0.084 60.491 0.000 5.108 5.305
.ADT3 5.062 0.088 57.379 0.000 5.062 5.032
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.264 0.116 2.268 0.023 0.264 0.216
.IM2 0.445 0.113 3.936 0.000 0.445 0.613
.IM3 0.512 0.244 2.101 0.036 0.512 0.553
.EEF1 0.297 0.077 3.851 0.000 0.297 0.189
.EEF2 0.185 0.045 4.069 0.000 0.185 0.131
.EEF3 0.215 0.075 2.874 0.004 0.215 0.150
.EEC1 1.040 0.147 7.098 0.000 1.040 0.510
.EEC2 0.446 0.138 3.236 0.001 0.446 0.210
.EEC3 0.119 0.058 2.047 0.041 0.119 0.060
.TR1 0.412 0.092 4.492 0.000 0.412 0.386
.TR2 0.378 0.104 3.642 0.000 0.378 0.376
.TR3 0.429 0.138 3.112 0.002 0.429 0.361
.ADT1 0.370 0.093 4.001 0.000 0.370 0.442
.ADT2 0.230 0.079 2.897 0.004 0.230 0.248
.ADT3 0.255 0.070 3.649 0.000 0.255 0.252
IM 0.956 0.210 4.542 0.000 1.000 1.000
EEF 1.278 0.248 5.144 0.000 1.000 1.000
EEC 1.000 0.223 4.475 0.000 1.000 1.000
TR 0.656 0.113 5.822 0.000 1.000 1.000
ADT 0.468 0.114 4.117 0.000 1.000 1.000
Chi-Squared Difference Test
Df AIC BIC Chisq Chisq diff RMSEA Df diff Pr(>Chisq)
fit_config 158 8233.5 8620.5 254.82
fit_metric 168 8229.3 8581.8 270.67 15.8519 0.070722 10 0.1040
fit_scalar 178 8217.7 8535.6 279.09 8.4233 0.000000 10 0.5876 config metric scalar
chisq 254.81674376 270.66863870 279.09196400
df 158.00000000 168.00000000 178.00000000
cfi 0.95582255 0.95315233 0.95387177
rmsea 0.07236920 0.07227221 0.06967154
srmr 0.05844121 0.06163038 0.06414048<NA>
NA <NA>
NA <NA>
NA <NA>
NA lhs op rhs block group level mi epc sepc.lv sepc.all sepc.nox
238 IM3 ~~ ADT1 1 1 1 10.339 0.100 0.100 0.359 0.359
179 TR =~ IM1 1 1 1 10.311 0.641 0.261 0.279 0.279
470 ADT2 ~~ ADT3 2 2 1 10.078 0.215 0.215 0.822 0.822No moderation - without PEB control variablelavaan 0.6-21 ended normally after 61 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 50
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 218.907 202.910
Degrees of freedom 145 145
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.079
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2823.399 2235.176
Degrees of freedom 180 180
P-value 0.000 0.000
Scaling correction factor 1.263
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.972 0.972
Tucker-Lewis Index (TLI) 0.965 0.965
Robust Comparative Fit Index (CFI) 0.976
Robust Tucker-Lewis Index (TLI) 0.970
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4247.837 -4247.837
Scaling correction factor 1.746
for the MLR correction
Loglikelihood unrestricted model (H1) -4138.383 -4138.383
Scaling correction factor 1.250
for the MLR correction
Akaike (AIC) 8595.673 8595.673
Bayesian (BIC) 8768.439 8768.439
Sample-size adjusted Bayesian (SABIC) 8609.962 8609.962
Root Mean Square Error of Approximation:
RMSEA 0.047 0.041
90 Percent confidence interval - lower 0.033 0.027
90 Percent confidence interval - upper 0.059 0.054
P-value H_0: RMSEA <= 0.050 0.658 0.870
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.043
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.056
P-value H_0: Robust RMSEA <= 0.050 0.798
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.117 0.117
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 1.314 0.888
TR2 1.084 0.046 23.470 0.000 1.424 0.938
TR3 1.046 0.047 22.442 0.000 1.374 0.921
ADT =~
ADT1 1.000 0.823 0.840
ADT2 1.095 0.081 13.478 0.000 0.902 0.905
ADT3 1.109 0.077 14.353 0.000 0.913 0.860
IM =~
IM1 1.000 0.948 0.909
IM2 0.629 0.109 5.746 0.000 0.596 0.708
IM3 0.694 0.108 6.412 0.000 0.658 0.682
EEF =~
EEF1 1.000 1.057 0.910
EEF2 0.983 0.051 19.417 0.000 1.039 0.911
EEF3 0.948 0.044 21.605 0.000 1.002 0.897
EEC =~
EEC1 1.000 0.967 0.724
EEC2 1.275 0.105 12.092 0.000 1.233 0.873
EEC3 1.348 0.091 14.867 0.000 1.303 0.943
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) -0.027 0.242 -0.110 0.912 -0.028 -0.011
rwrd0_2 (b_02) -0.071 0.237 -0.298 0.766 -0.074 -0.029
rwrd1_2 (b_12) 0.093 0.211 0.439 0.661 0.098 0.038
rwrd0_3 (b_03) 0.049 0.250 0.197 0.844 0.052 0.018
rwrd1_3 (b_13) -0.249 0.225 -1.106 0.269 -0.262 -0.090
EEF ~
rwrd1_1 (c_11) 0.053 0.205 0.259 0.796 0.050 0.019
rwrd0_2 (c_02) -0.016 0.192 -0.083 0.934 -0.015 -0.006
rwrd1_2 (c_12) 0.031 0.171 0.184 0.854 0.030 0.012
rwrd0_3 (c_03) -0.235 0.179 -1.308 0.191 -0.222 -0.075
rwrd1_3 (c_13) 0.059 0.186 0.316 0.752 0.056 0.019
IM (c_IM) 0.704 0.094 7.488 0.000 0.632 0.632
EEC ~
rwrd1_1 (d_11) 0.191 0.201 0.950 0.342 0.198 0.076
rwrd0_2 (d_02) 0.233 0.196 1.191 0.234 0.241 0.094
rwrd1_2 (d_12) 0.256 0.187 1.369 0.171 0.265 0.103
rwrd0_3 (d_03) 0.097 0.189 0.513 0.608 0.100 0.034
rwrd1_3 (d_13) 0.124 0.222 0.561 0.575 0.129 0.044
IM (d_IM) 0.560 0.079 7.072 0.000 0.550 0.550
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.153 0.065 2.357 0.018 0.153 0.364
TR ~~
ADT 0.434 0.089 4.892 0.000 0.401 0.401
.EEF ~~
.EEC 0.288 0.075 3.822 0.000 0.439 0.439
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.464 0.076 6.098 0.000 0.464 0.212
.TR2 0.278 0.067 4.143 0.000 0.278 0.120
.TR3 0.336 0.082 4.089 0.000 0.336 0.151
.ADT1 0.283 0.061 4.659 0.000 0.283 0.295
.ADT2 0.180 0.048 3.735 0.000 0.180 0.181
.ADT3 0.295 0.080 3.662 0.000 0.295 0.261
.IM1 0.189 0.086 2.192 0.028 0.189 0.173
.IM2 0.355 0.081 4.402 0.000 0.355 0.499
.IM3 0.499 0.171 2.919 0.004 0.499 0.535
.EEF1 0.231 0.051 4.498 0.000 0.231 0.171
.EEF2 0.222 0.043 5.181 0.000 0.222 0.170
.EEF3 0.245 0.057 4.273 0.000 0.245 0.196
.EEC1 0.848 0.096 8.865 0.000 0.848 0.476
.EEC2 0.475 0.097 4.902 0.000 0.475 0.238
.EEC3 0.212 0.063 3.389 0.001 0.212 0.111
TR 1.726 0.166 10.407 0.000 1.000 1.000
ADT 0.678 0.090 7.547 0.000 1.000 1.000
.IM 0.889 0.155 5.746 0.000 0.988 0.988
.EEF 0.668 0.129 5.182 0.000 0.598 0.598
.EEC 0.643 0.107 6.018 0.000 0.688 0.688
R-Square:
Estimate
TR1 0.788
TR2 0.880
TR3 0.849
ADT1 0.705
ADT2 0.819
ADT3 0.739
IM1 0.827
IM2 0.501
IM3 0.465
EEF1 0.829
EEF2 0.830
EEF3 0.804
EEC1 0.524
EEC2 0.762
EEC3 0.889
IM 0.012
EEF 0.402
EEC 0.312With control all three controlslavaan 0.6-21 ended normally after 62 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 59
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 187.229 174.523
Degrees of freedom 151 151
P-value (Chi-square) 0.024 0.092
Scaling correction factor 1.073
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2881.080 2318.492
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.243
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.987 0.989
Tucker-Lewis Index (TLI) 0.983 0.986
Robust Comparative Fit Index (CFI) 0.990
Robust Tucker-Lewis Index (TLI) 0.988
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4203.157 -4203.157
Scaling correction factor 1.638
for the MLR correction
Loglikelihood unrestricted model (H1) -4109.543 -4109.543
Scaling correction factor 1.232
for the MLR correction
Akaike (AIC) 8524.314 8524.314
Bayesian (BIC) 8728.178 8728.178
Sample-size adjusted Bayesian (SABIC) 8541.175 8541.175
Root Mean Square Error of Approximation:
RMSEA 0.032 0.026
90 Percent confidence interval - lower 0.012 0.000
90 Percent confidence interval - upper 0.046 0.041
P-value H_0: RMSEA <= 0.050 0.985 0.998
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.027
90 Percent confidence interval - lower 0.000
90 Percent confidence interval - upper 0.043
P-value H_0: Robust RMSEA <= 0.050 0.994
P-value H_0: Robust RMSEA >= 0.080 0.000
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|) Std.lv Std.all
TR =~
TR1 1.000 1.316 0.889
TR2 1.081 0.047 23.244 0.000 1.423 0.937
TR3 1.044 0.047 22.266 0.000 1.374 0.921
ADT =~
ADT1 1.000 0.830 0.846
ADT2 1.078 0.080 13.411 0.000 0.895 0.898
ADT3 1.103 0.078 14.122 0.000 0.915 0.861
IM =~
IM1 1.000 0.909 0.874
IM2 0.679 0.107 6.376 0.000 0.617 0.734
IM3 0.751 0.106 7.063 0.000 0.683 0.708
EEF =~
EEF1 1.000 1.058 0.911
EEF2 0.980 0.049 19.817 0.000 1.037 0.910
EEF3 0.947 0.043 21.866 0.000 1.002 0.896
EEC =~
EEC1 1.000 0.965 0.723
EEC2 1.272 0.104 12.181 0.000 1.228 0.870
EEC3 1.354 0.091 14.811 0.000 1.307 0.946
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.167 0.197 0.848 0.397 0.184 0.071
rwrd0_2 (b_02) 0.042 0.214 0.195 0.845 0.046 0.018
rwrd1_2 (b_12) 0.246 0.183 1.344 0.179 0.270 0.106
rwrd0_3 (b_03) 0.216 0.224 0.965 0.335 0.238 0.081
rwrd1_3 (b_13) -0.091 0.189 -0.480 0.631 -0.100 -0.034
TR (b_TR) 0.103 0.054 1.928 0.054 0.150 0.150
ADT (b_AD) 0.175 0.085 2.052 0.040 0.160 0.160
PEB_yes (b_PE) 0.905 0.129 7.026 0.000 0.996 0.411
EEF ~
rwrd1_1 (c_11) 0.087 0.202 0.432 0.666 0.082 0.032
rwrd0_2 (c_02) -0.041 0.180 -0.226 0.822 -0.038 -0.015
rwrd1_2 (c_12) 0.071 0.163 0.433 0.665 0.067 0.026
rwrd0_3 (c_03) -0.198 0.175 -1.129 0.259 -0.187 -0.063
rwrd1_3 (c_13) 0.075 0.188 0.397 0.691 0.071 0.024
IM (c_IM) 0.618 0.097 6.364 0.000 0.531 0.531
TR (c_TR) 0.013 0.049 0.275 0.783 0.017 0.017
ADT (c_AD) 0.294 0.085 3.450 0.001 0.231 0.231
PEB_yes (c_PE) 0.345 0.175 1.974 0.048 0.326 0.135
EEC ~
rwrd1_1 (d_11) 0.196 0.200 0.982 0.326 0.203 0.078
rwrd0_2 (d_02) 0.212 0.198 1.070 0.284 0.220 0.086
rwrd1_2 (d_12) 0.284 0.176 1.615 0.106 0.295 0.115
rwrd0_3 (d_03) 0.091 0.185 0.495 0.620 0.095 0.032
rwrd1_3 (d_13) 0.125 0.203 0.617 0.538 0.130 0.045
IM (d_IM) 0.494 0.096 5.175 0.000 0.465 0.465
TR (d_TR) 0.085 0.050 1.706 0.088 0.116 0.116
ADT (d_AD) 0.227 0.082 2.778 0.005 0.195 0.195
PEB_yes (d_PE) 0.046 0.163 0.280 0.779 0.047 0.020
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.121 0.060 2.031 0.042 0.121 0.312
TR ~~
ADT 0.440 0.089 4.928 0.000 0.403 0.403
.EEF ~~
.EEC 0.226 0.065 3.482 0.000 0.387 0.387
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.458 0.077 5.983 0.000 0.458 0.209
.TR2 0.282 0.068 4.144 0.000 0.282 0.122
.TR3 0.337 0.082 4.093 0.000 0.337 0.152
.ADT1 0.273 0.061 4.463 0.000 0.273 0.284
.ADT2 0.193 0.049 3.899 0.000 0.193 0.194
.ADT3 0.291 0.078 3.750 0.000 0.291 0.258
.IM1 0.256 0.075 3.409 0.001 0.256 0.237
.IM2 0.326 0.077 4.257 0.000 0.326 0.462
.IM3 0.463 0.169 2.742 0.006 0.463 0.499
.EEF1 0.229 0.051 4.440 0.000 0.229 0.170
.EEF2 0.224 0.042 5.297 0.000 0.224 0.172
.EEF3 0.245 0.057 4.302 0.000 0.245 0.196
.EEC1 0.850 0.095 8.935 0.000 0.850 0.477
.EEC2 0.485 0.097 4.991 0.000 0.485 0.243
.EEC3 0.200 0.063 3.198 0.001 0.200 0.105
TR 1.732 0.166 10.421 0.000 1.000 1.000
ADT 0.688 0.090 7.613 0.000 1.000 1.000
.IM 0.621 0.118 5.279 0.000 0.752 0.752
.EEF 0.582 0.108 5.388 0.000 0.520 0.520
.EEC 0.586 0.098 5.952 0.000 0.629 0.629
R-Square:
Estimate
TR1 0.791
TR2 0.878
TR3 0.848
ADT1 0.716
ADT2 0.806
ADT3 0.742
IM1 0.763
IM2 0.538
IM3 0.501
EEF1 0.830
EEF2 0.828
EEF3 0.804
EEC1 0.523
EEC2 0.757
EEC3 0.895
IM 0.248
EEF 0.480
EEC 0.371
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.167 0.197 0.848 0.397 0.184 0.071
reward2_IM 0.204 0.205 0.994 0.320 0.224 0.088
reward3_IM -0.307 0.230 -1.335 0.182 -0.338 -0.115
reward_vrgd_IM 0.021 0.124 0.171 0.864 0.023 0.014
reward_EEF_ec1 0.087 0.202 0.432 0.666 0.082 0.032
reward_EEF_ec2 0.111 0.186 0.597 0.550 0.105 0.041
reward_EEF_ec3 0.273 0.201 1.356 0.175 0.258 0.088
reward_man_EEF 0.157 0.112 1.403 0.161 0.148 0.053
ind_rwrd_EEF_1 0.103 0.128 0.810 0.418 0.098 0.037
ind_rwrd_EEF_2 0.126 0.124 1.014 0.311 0.119 0.047
ind_rwrd_EEF_3 -0.190 0.145 -1.311 0.190 -0.180 -0.061
ind_rw__IM_EEF 0.013 0.077 0.171 0.864 0.012 0.008
tt_rwrd_mn_EEF 0.170 0.124 1.377 0.169 0.161 0.061
reward_EEC_ec1 0.196 0.200 0.982 0.326 0.203 0.078
reward_EEC_ec2 0.072 0.180 0.402 0.688 0.075 0.029
reward_EEC_ec3 0.034 0.202 0.168 0.867 0.035 0.013
reward_man_EEC 0.101 0.112 0.903 0.367 0.104 0.040
ind_rwrd_EEC_1 0.083 0.100 0.828 0.407 0.086 0.033
ind_rwrd_EEC_2 0.101 0.103 0.977 0.328 0.104 0.041
ind_rwrd_EEC_3 -0.152 0.118 -1.285 0.199 -0.157 -0.054
ind_rw__IM_EEC 0.011 0.061 0.171 0.864 0.011 0.007
tt_rwrd_mn_EEC 0.111 0.117 0.953 0.340 0.115 0.047
eco2_vs_c1_EEF -0.029 0.131 -0.218 0.827 -0.027 -0.010
eco3_vs_c1_EEF -0.105 0.139 -0.759 0.448 -0.100 -0.035
eco1_vs_c2_EEF 0.029 0.131 0.218 0.827 0.027 0.010
eco_main_EEF -0.067 0.116 -0.579 0.563 -0.063 -0.023
eco2_vs_ec1_IM 0.060 0.136 0.441 0.659 0.066 0.026
eco3_vs_ec1_IM -0.021 0.146 -0.142 0.887 -0.023 -0.012
eco1_vs_ec2_IM -0.060 0.136 -0.441 0.659 -0.066 -0.026
in_1__2_IM_EEF -0.037 0.085 -0.436 0.663 -0.035 -0.014
in_2__1_IM_EEF 0.037 0.085 0.436 0.663 0.035 0.014
in_3__1_IM_EEF -0.013 0.091 -0.142 0.887 -0.012 -0.006
ind_c_m_IM_EEF 0.012 0.074 0.165 0.869 0.011 0.004
tt_c1_vs_2_EEF -0.009 0.145 -0.059 0.953 -0.008 -0.004
tt_c2_vs_1_EEF 0.009 0.145 0.059 0.953 0.008 0.004
tt_c3_vs_1_EEF -0.118 0.155 -0.761 0.447 -0.112 -0.042
tot_eco_mn_EEF -0.055 0.128 -0.427 0.669 -0.052 -0.019
eco2_vs_c1_EEC 0.150 0.136 1.103 0.270 0.155 0.061
eco3_vs_c1_EEC 0.010 0.138 0.073 0.941 0.011 -0.001
eco_main_EEC 0.080 0.120 0.668 0.504 0.083 0.030
in_2__1_IM_EEC 0.030 0.068 0.437 0.662 0.031 0.012
in_3__1_IM_EEC -0.010 0.072 -0.142 0.887 -0.011 -0.006
ind_c_m_IM_EEC 0.010 0.059 0.165 0.869 0.010 0.003
tt_c2_vs_1_EEC 0.180 0.149 1.205 0.228 0.186 0.074
tt_c3_vs_1_EEC -0.000 0.135 -0.001 0.999 -0.000 -0.006
tot_eco_mn_EEC 0.090 0.124 0.724 0.469 0.093 0.034
eco_main_IM 0.020 0.119 0.166 0.868 0.022 0.007
eco3_vs_c2_EEF -0.077 0.139 -0.553 0.580 -0.073 -0.025
in_3__2_IM_EEF -0.050 0.096 -0.520 0.603 -0.047 -0.020
tt_c3_vs_2_EEF -0.127 0.157 -0.807 0.420 -0.120 -0.046
eco3_vs_c2_EEC -0.140 0.133 -1.048 0.295 -0.145 -0.062
in_3__2_IM_EEC -0.040 0.077 -0.521 0.602 -0.041 -0.018
tt_c3_vs_2_EEC -0.180 0.140 -1.283 0.200 -0.186 -0.080
reward_IM_eco1 0.167 0.197 0.848 0.397 0.184 0.071
reward_IM_eco2 0.204 0.205 0.994 0.320 0.224 0.088
reward_IM_eco3 -0.307 0.230 -1.335 0.182 -0.338 -0.115
reward_main_IM 0.021 0.124 0.171 0.864 0.023 0.014
r_3_EEF___1_EE -0.013 0.222 -0.057 0.955 -0.012 -0.007
r_2_EEF___1_EE -0.017 0.199 -0.083 0.934 -0.016 -0.006
r_2_EEC___1_EE 0.088 0.184 0.478 0.633 0.091 0.037
r_3_EEC___2_EE -0.159 0.193 -0.824 0.410 -0.165 -0.070
r_3_EEC___1_EE -0.071 0.212 -0.335 0.737 -0.074 -0.033
rw_2_IM___1_IM 0.078 0.176 0.447 0.655 0.086 0.035
rw_3_IM___1_IM -0.258 0.193 -1.338 0.181 -0.284 -0.105
i__2_EEC___1_E 0.039 0.087 0.445 0.657 0.040 0.016
i__3_EEC___1_E -0.128 0.099 -1.282 0.200 -0.132 -0.049
i__3_EEC___2_E -0.166 0.098 -1.705 0.088 -0.172 -0.065
t__2_EEC___1_E 0.127 0.204 0.621 0.535 0.131 0.053
t__3_EEC___1_E -0.199 0.216 -0.917 0.359 -0.206 -0.082
t__3_EEC___2_E -0.325 0.198 -1.646 0.100 -0.337 -0.136
rwrd_c3_dr_EEF 0.273 0.201 1.356 0.175 0.258 0.088
rwrd_3__IM_EEF -0.190 0.145 -1.311 0.190 -0.180 -0.061
rwrd_c3_tt_EEF 0.083 0.230 0.359 0.720 0.078 0.027
rwrd_c3_dr_EEC 0.034 0.202 0.168 0.867 0.035 0.013
rwrd_3__IM_EEC -0.152 0.118 -1.285 0.199 -0.157 -0.054
rwrd_c3_tt_EEC -0.118 0.192 -0.616 0.538 -0.122 -0.041Mediation 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 :=
156 reward_eco3_direct_EEF :=
157 reward_eco3_ind_IM_EEF :=
158 reward_eco3_total_EEF :=
159 reward_eco3_direct_EEC :=
160 reward_eco3_ind_IM_EEC :=
161 reward_eco3_total_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
156 (c_r1e3-c_r0e3)
157 (b_r1e3-b_r0e3)*c_IM
158 reward_eco3_direct_EEF+reward_eco3_ind_IM_EEF
159 (d_r1e3-d_r0e3)
160 (b_r1e3-b_r0e3)*d_IM
161 reward_eco3_direct_EEC+reward_eco3_ind_IM_EEC
label est se z pvalue ci.lower
93 reward_main_EEF 0.157 0.110 1.424 0.154 -0.048
97 ind_reward_main_IM_EEF 0.013 0.079 0.167 0.867 -0.140
98 tot_reward_main_EEF 0.170 0.127 1.345 0.179 -0.088
102 reward_main_EEC 0.101 0.111 0.909 0.363 -0.117
106 ind_reward_main_IM_EEC 0.011 0.063 0.167 0.867 -0.117
107 tot_reward_main_EEC 0.111 0.118 0.941 0.347 -0.112
109 eco3_vs_eco1_EEF -0.105 0.147 -0.719 0.472 -0.409
110 eco1_vs_eco2_EEF 0.029 0.140 0.204 0.838 -0.257
111 eco_main_EEF -0.067 0.124 -0.541 0.588 -0.314
112 eco2_vs_eco1_IM 0.060 0.143 0.421 0.674 -0.257
113 eco3_vs_eco1_IM -0.021 0.147 -0.141 0.888 -0.309
114 eco1_vs_eco2_IM -0.060 0.143 -0.421 0.674 -0.288
115 ind_eco1_vs_eco2_IM_EEF -0.037 0.088 -0.420 0.674 -0.192
117 ind_eco3_vs_eco1_IM_EEF -0.013 0.092 -0.139 0.889 -0.203
118 ind_eco_main_IM_EEF 0.012 0.076 0.161 0.872 -0.147
119 tot_eco1_vs_eco2_EEF -0.009 0.148 -0.058 0.954 -0.316
121 tot_eco3_vs_eco1_EEF -0.118 0.157 -0.754 0.451 -0.419
122 tot_eco_main_EEF -0.055 0.130 -0.421 0.674 -0.323
123 eco2_vs_eco1_EEC 0.150 0.136 1.104 0.270 -0.136
124 eco3_vs_eco1_EEC 0.010 0.141 0.072 0.942 -0.273
125 eco_main_EEC 0.080 0.121 0.662 0.508 -0.172
126 ind_eco2_vs_eco1_IM_EEC 0.030 0.071 0.419 0.675 -0.126
127 ind_eco3_vs_eco1_IM_EEC -0.010 0.073 -0.140 0.889 -0.154
128 ind_eco_main_IM_EEC 0.010 0.061 0.161 0.872 -0.118
129 tot_eco2_vs_eco1_EEC 0.180 0.151 1.191 0.234 -0.141
130 tot_eco3_vs_eco1_EEC 0.000 0.137 -0.001 0.999 -0.295
131 tot_eco_main_EEC 0.090 0.125 0.719 0.472 -0.164
132 eco_main_IM 0.020 0.123 0.160 0.873 -0.244
136 eco3_vs_eco2_EEC -0.140 0.134 -1.043 0.297 -0.387
137 ind_eco3_vs_eco2_IM_EEC -0.040 0.078 -0.512 0.609 -0.199
138 tot_eco3_vs_eco2_EEC -0.180 0.144 -1.245 0.213 -0.455
142 reward_main_IM 0.021 0.127 0.168 0.867 -0.239
143 reward_eco3_EEF_vs_reward_eco1_EEF -0.013 0.230 -0.055 0.956 -0.454
144 reward_eco2_EEF_vs_reward_eco1_EEF -0.017 0.203 -0.082 0.935 -0.412
145 reward_eco2_EEC_vs_reward_eco1_EEC 0.088 0.185 0.477 0.634 -0.250
146 reward_eco3_EEC_vs_reward_eco2_EEC -0.159 0.196 -0.810 0.418 -0.548
148 reward_eco2_IM_vs_reward_eco1_IM 0.078 0.184 0.426 0.670 -0.291
149 reward_eco3_IM_vs_reward_eco1_IM -0.258 0.207 -1.249 0.212 -0.640
150 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.039 0.091 0.425 0.671 -0.148
151 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.128 0.108 -1.184 0.236 -0.352
152 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.166 0.110 -1.516 0.130 -0.391
153 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.127 0.201 0.630 0.529 -0.277
154 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.199 0.222 -0.893 0.372 -0.648
155 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.325 0.203 -1.602 0.109 -0.739
156 reward_eco3_direct_EEF 0.273 0.214 1.275 0.202 -0.166
157 reward_eco3_ind_IM_EEF -0.190 0.149 -1.272 0.203 -0.492
158 reward_eco3_total_EEF 0.083 0.246 0.335 0.737 -0.427
159 reward_eco3_direct_EEC 0.034 0.208 0.163 0.871 -0.388
160 reward_eco3_ind_IM_EEC -0.152 0.127 -1.198 0.231 -0.430
161 reward_eco3_total_EEC -0.118 0.199 -0.594 0.553 -0.491
ci.upper std.lv std.all std.nox
93 0.373 0.148 0.053 0.148
97 0.157 0.012 0.008 0.012
98 0.439 0.161 0.061 0.161
102 0.334 0.104 0.040 0.104
106 0.134 0.011 0.007 0.011
107 0.357 0.115 0.047 0.115
109 0.194 -0.100 -0.035 -0.100
110 0.296 0.027 0.010 0.027
111 0.182 -0.063 -0.023 -0.063
112 0.288 0.066 0.026 0.066
113 0.236 -0.023 -0.012 -0.023
114 0.257 -0.066 -0.026 -0.066
115 0.148 -0.035 -0.014 -0.035
117 0.158 -0.012 -0.006 -0.012
118 0.149 0.011 0.004 0.011
119 0.288 -0.008 -0.004 -0.008
121 0.188 -0.112 -0.042 -0.112
122 0.201 -0.052 -0.019 -0.052
123 0.419 0.155 0.061 0.155
124 0.308 0.011 -0.001 0.011
125 0.325 0.083 0.030 0.083
126 0.158 0.031 0.012 0.031
127 0.132 -0.011 -0.006 -0.011
128 0.123 0.010 0.003 0.010
129 0.467 0.186 0.074 0.186
130 0.283 0.000 -0.006 0.000
131 0.341 0.093 0.034 0.093
132 0.238 0.022 0.007 0.022
136 0.142 -0.145 -0.062 -0.145
137 0.115 -0.041 -0.018 -0.041
138 0.098 -0.186 -0.080 -0.186
142 0.266 0.023 0.014 0.023
143 0.434 -0.012 -0.007 -0.012
144 0.401 -0.016 -0.006 -0.016
145 0.431 0.091 0.037 0.091
146 0.202 -0.165 -0.070 -0.165
148 0.453 0.086 0.035 0.086
149 0.158 -0.284 -0.105 -0.284
150 0.224 0.040 0.016 0.040
151 0.083 -0.132 -0.049 -0.132
152 0.054 -0.172 -0.065 -0.172
153 0.496 0.131 0.053 0.131
154 0.253 -0.206 -0.082 -0.206
155 0.070 -0.337 -0.136 -0.337
156 0.688 0.258 0.088 0.258
157 0.097 -0.180 -0.061 -0.180
158 0.560 0.078 0.027 0.078
159 0.457 0.035 0.013 0.035
160 0.075 -0.157 -0.054 -0.157
161 0.284 -0.122 -0.041 -0.122With control variableslavaan 0.6-21 ended normally after 56 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 49
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 135.213 124.275
Degrees of freedom 101 101
P-value (Chi-square) 0.013 0.058
Scaling correction factor 1.088
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2155.873 1664.643
Degrees of freedom 138 138
P-value 0.000 0.000
Scaling correction factor 1.295
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.983 0.985
Tucker-Lewis Index (TLI) 0.977 0.979
Robust Comparative Fit Index (CFI) 0.987
Robust Tucker-Lewis Index (TLI) 0.982
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3260.616 -3260.616
Scaling correction factor 1.706
for the MLR correction
Loglikelihood unrestricted model (H1) -3193.010 -3193.010
Scaling correction factor 1.290
for the MLR correction
Akaike (AIC) 6619.233 6619.233
Bayesian (BIC) 6788.544 6788.544
Sample-size adjusted Bayesian (SABIC) 6633.236 6633.236
Root Mean Square Error of Approximation:
RMSEA 0.038 0.031
90 Percent confidence interval - lower 0.018 0.000
90 Percent confidence interval - upper 0.054 0.048
P-value H_0: RMSEA <= 0.050 0.887 0.970
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.033
90 Percent confidence interval - lower 0.000
90 Percent confidence interval - upper 0.051
P-value H_0: Robust RMSEA <= 0.050 0.943
P-value H_0: Robust RMSEA >= 0.080 0.000
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|) Std.lv Std.all
ADT =~
ADT1 1.000 0.828 0.844
ADT2 1.085 0.082 13.218 0.000 0.898 0.901
ADT3 1.104 0.079 13.967 0.000 0.914 0.860
IM =~
IM1 1.000 0.911 0.873
IM2 0.683 0.106 6.465 0.000 0.622 0.737
IM3 0.754 0.106 7.093 0.000 0.687 0.711
EEF =~
EEF1 1.000 1.061 0.912
EEF2 0.981 0.049 19.881 0.000 1.040 0.910
EEF3 0.947 0.043 21.872 0.000 1.005 0.897
EEC =~
EEC1 1.000 0.968 0.725
EEC2 1.276 0.106 12.067 0.000 1.236 0.874
EEC3 1.347 0.090 14.953 0.000 1.304 0.942
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.160 0.202 0.793 0.428 0.176 0.067
rwrd0_2 (b_02) 0.011 0.219 0.050 0.960 0.012 0.005
rwrd1_2 (b_12) 0.227 0.187 1.216 0.224 0.249 0.097
rwrd0_3 (b_03) 0.205 0.223 0.920 0.358 0.225 0.076
rwrd1_3 (b_13) -0.108 0.191 -0.564 0.573 -0.118 -0.041
ADT (b_AD) 0.239 0.087 2.736 0.006 0.217 0.217
PEB_yes (b_PE) 0.929 0.127 7.292 0.000 1.020 0.421
EEF ~
rwrd1_1 (c_11) 0.083 0.201 0.414 0.679 0.078 0.030
rwrd0_2 (c_02) -0.048 0.181 -0.266 0.790 -0.045 -0.018
rwrd1_2 (c_12) 0.064 0.164 0.393 0.694 0.061 0.024
rwrd0_3 (c_03) -0.202 0.175 -1.154 0.248 -0.190 -0.065
rwrd1_3 (c_13) 0.071 0.190 0.376 0.707 0.067 0.023
IM (c_IM) 0.624 0.096 6.504 0.000 0.536 0.536
ADT (c_AD) 0.302 0.077 3.927 0.000 0.236 0.236
PEB_yes (c_PE) 0.344 0.175 1.965 0.049 0.324 0.134
EEC ~
rwrd1_1 (d_11) 0.185 0.203 0.909 0.364 0.191 0.073
rwrd0_2 (d_02) 0.186 0.200 0.931 0.352 0.192 0.075
rwrd1_2 (d_12) 0.264 0.180 1.466 0.143 0.272 0.106
rwrd0_3 (d_03) 0.083 0.187 0.443 0.658 0.085 0.029
rwrd1_3 (d_13) 0.110 0.212 0.520 0.603 0.114 0.039
IM (d_IM) 0.519 0.094 5.538 0.000 0.488 0.488
ADT (d_AD) 0.279 0.081 3.455 0.001 0.239 0.239
PEB_yes (d_PE) 0.046 0.169 0.275 0.783 0.048 0.020
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.120 0.060 2.005 0.045 0.120 0.309
.EEF ~~
.EEC 0.228 0.066 3.458 0.001 0.388 0.388
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.ADT1 0.277 0.063 4.416 0.000 0.277 0.288
.ADT2 0.188 0.049 3.812 0.000 0.188 0.189
.ADT3 0.293 0.077 3.832 0.000 0.293 0.260
.IM1 0.260 0.074 3.525 0.000 0.260 0.239
.IM2 0.324 0.077 4.235 0.000 0.324 0.456
.IM3 0.462 0.171 2.707 0.007 0.462 0.495
.EEF1 0.229 0.051 4.445 0.000 0.229 0.169
.EEF2 0.224 0.042 5.322 0.000 0.224 0.171
.EEF3 0.245 0.057 4.306 0.000 0.245 0.195
.EEC1 0.848 0.096 8.861 0.000 0.848 0.475
.EEC2 0.472 0.097 4.871 0.000 0.472 0.236
.EEC3 0.215 0.063 3.416 0.001 0.215 0.112
ADT 0.685 0.091 7.520 0.000 1.000 1.000
.IM 0.633 0.121 5.235 0.000 0.763 0.763
.EEF 0.582 0.108 5.375 0.000 0.517 0.517
.EEC 0.594 0.101 5.898 0.000 0.634 0.634
R-Square:
Estimate
ADT1 0.712
ADT2 0.811
ADT3 0.740
IM1 0.761
IM2 0.544
IM3 0.505
EEF1 0.831
EEF2 0.829
EEF3 0.805
EEC1 0.525
EEC2 0.764
EEC3 0.888
IM 0.237
EEF 0.483
EEC 0.366
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.160 0.202 0.793 0.428 0.176 0.067
reward2_IM 0.216 0.207 1.045 0.296 0.237 0.093
reward3_IM -0.313 0.229 -1.370 0.171 -0.344 -0.117
reward_vrgd_IM 0.021 0.125 0.168 0.867 0.023 0.014
reward_EEF_ec1 0.083 0.201 0.414 0.679 0.078 0.030
reward_EEF_ec2 0.113 0.187 0.602 0.547 0.106 0.041
reward_EEF_ec3 0.273 0.201 1.359 0.174 0.258 0.088
reward_man_EEF 0.156 0.112 1.396 0.163 0.147 0.053
ind_rwrd_EEF_1 0.100 0.132 0.759 0.448 0.094 0.036
ind_rwrd_EEF_2 0.135 0.126 1.069 0.285 0.127 0.050
ind_rwrd_EEF_3 -0.196 0.146 -1.343 0.179 -0.184 -0.063
ind_rw__IM_EEF 0.013 0.078 0.168 0.867 0.012 0.008
tt_rwrd_mn_EEF 0.169 0.124 1.367 0.172 0.160 0.061
reward_EEC_ec1 0.185 0.203 0.909 0.364 0.191 0.073
reward_EEC_ec2 0.078 0.180 0.430 0.667 0.080 0.031
reward_EEC_ec3 0.028 0.207 0.133 0.894 0.028 0.010
reward_man_EEC 0.097 0.113 0.852 0.394 0.100 0.038
ind_rwrd_EEC_1 0.083 0.107 0.778 0.436 0.086 0.033
ind_rwrd_EEC_2 0.112 0.109 1.029 0.304 0.116 0.045
ind_rwrd_EEC_3 -0.162 0.123 -1.323 0.186 -0.168 -0.057
ind_rw__IM_EEC 0.011 0.065 0.168 0.867 0.011 0.007
tt_rwrd_mn_EEC 0.108 0.119 0.904 0.366 0.111 0.045
eco2_vs_c1_EEF -0.034 0.132 -0.254 0.799 -0.032 -0.012
eco3_vs_c1_EEF -0.107 0.139 -0.768 0.442 -0.101 -0.036
eco1_vs_c2_EEF 0.034 0.132 0.254 0.799 0.032 0.012
eco_main_EEF -0.070 0.116 -0.603 0.546 -0.066 -0.024
eco2_vs_ec1_IM 0.039 0.140 0.277 0.781 0.043 0.017
eco3_vs_ec1_IM -0.031 0.147 -0.214 0.831 -0.034 -0.016
eco1_vs_ec2_IM -0.039 0.140 -0.277 0.781 -0.043 -0.017
in_1__2_IM_EEF -0.024 0.088 -0.275 0.783 -0.023 -0.009
in_2__1_IM_EEF 0.024 0.088 0.275 0.783 0.023 0.009
in_3__1_IM_EEF -0.020 0.091 -0.214 0.831 -0.018 -0.009
ind_c_m_IM_EEF 0.002 0.075 0.031 0.975 0.002 0.000
tt_c1_vs_2_EEF 0.009 0.148 0.062 0.950 0.009 0.003
tt_c2_vs_1_EEF -0.009 0.148 -0.062 0.950 -0.009 -0.003
tt_c3_vs_1_EEF -0.127 0.157 -0.809 0.419 -0.119 -0.044
tot_eco_mn_EEF -0.068 0.131 -0.520 0.603 -0.064 -0.024
eco2_vs_c1_EEC 0.132 0.136 0.972 0.331 0.137 0.054
eco3_vs_c1_EEC 0.004 0.141 0.028 0.977 0.004 -0.003
eco_main_EEC 0.068 0.121 0.564 0.572 0.070 0.026
in_2__1_IM_EEC 0.020 0.073 0.277 0.782 0.021 0.008
in_3__1_IM_EEC -0.016 0.076 -0.214 0.831 -0.017 -0.008
ind_c_m_IM_EEC 0.002 0.063 0.031 0.975 0.002 0.000
tt_c2_vs_1_EEC 0.152 0.152 1.003 0.316 0.157 0.062
tt_c3_vs_1_EEC -0.012 0.139 -0.088 0.930 -0.013 -0.010
tot_eco_mn_EEC 0.070 0.127 0.553 0.580 0.072 0.026
eco_main_IM 0.004 0.121 0.031 0.975 0.004 0.001
eco3_vs_c2_EEF -0.074 0.139 -0.529 0.597 -0.069 -0.024
in_3__2_IM_EEF -0.044 0.097 -0.450 0.653 -0.041 -0.018
tt_c3_vs_2_EEF -0.117 0.158 -0.743 0.457 -0.111 -0.042
eco3_vs_c2_EEC -0.128 0.136 -0.945 0.344 -0.133 -0.057
in_3__2_IM_EEC -0.036 0.081 -0.452 0.651 -0.038 -0.016
tt_c3_vs_2_EEC -0.165 0.143 -1.149 0.251 -0.170 -0.073
reward_IM_eco1 0.160 0.202 0.793 0.428 0.176 0.067
reward_IM_eco2 0.216 0.207 1.045 0.296 0.237 0.093
reward_IM_eco3 -0.313 0.229 -1.370 0.171 -0.344 -0.117
reward_main_IM 0.021 0.125 0.168 0.867 0.023 0.014
r_3_EEF___1_EE -0.012 0.222 -0.054 0.957 -0.011 -0.007
r_2_EEF___1_EE -0.019 0.199 -0.095 0.925 -0.018 -0.006
r_2_EEC___1_EE 0.079 0.184 0.426 0.670 0.081 0.033
r_3_EEC___2_EE -0.153 0.199 -0.771 0.441 -0.158 -0.067
r_3_EEC___1_EE -0.075 0.217 -0.345 0.730 -0.077 -0.034
rw_2_IM___1_IM 0.067 0.180 0.371 0.710 0.073 0.030
rw_3_IM___1_IM -0.268 0.195 -1.374 0.169 -0.294 -0.108
i__2_EEC___1_E 0.035 0.093 0.371 0.711 0.036 0.015
i__3_EEC___1_E -0.139 0.105 -1.323 0.186 -0.144 -0.053
i__3_EEC___2_E -0.174 0.101 -1.720 0.085 -0.179 -0.067
t__2_EEC___1_E 0.113 0.208 0.546 0.585 0.117 0.048
t__3_EEC___1_E -0.214 0.225 -0.951 0.341 -0.221 -0.087
t__3_EEC___2_E -0.327 0.206 -1.588 0.112 -0.338 -0.135Mediation 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 0.156 0.136 1.148 0.251 -0.116
86 ind_reward_main_IM_EEF 0.013 0.065 0.203 0.839 -0.170
87 tot_reward_main_EEF 0.169 0.133 1.274 0.203 -0.116
91 reward_main_EEC 0.097 0.120 0.806 0.420 -0.171
95 ind_reward_main_IM_EEC 0.011 0.055 0.196 0.845 -0.106
96 tot_reward_main_EEC 0.108 0.110 0.976 0.329 -0.109
98 eco3_vs_eco1_EEF -0.107 0.126 -0.849 0.396 -0.355
99 eco1_vs_eco2_EEF 0.034 0.136 0.246 0.806 -0.196
100 eco_main_EEF -0.070 0.108 -0.651 0.515 -0.313
101 eco2_vs_eco1_IM 0.039 0.141 0.276 0.783 -0.278
102 eco3_vs_eco1_IM -0.031 0.118 -0.267 0.790 -0.271
103 eco1_vs_eco2_IM -0.039 0.141 -0.276 0.783 -0.324
104 ind_eco1_vs_eco2_IM_EEF -0.024 0.090 -0.270 0.787 -0.244
106 ind_eco3_vs_eco1_IM_EEF -0.020 0.076 -0.256 0.798 -0.209
107 ind_eco_main_IM_EEF 0.002 0.066 0.035 0.972 -0.111
108 tot_eco1_vs_eco2_EEF 0.009 0.158 0.059 0.953 -0.377
110 tot_eco3_vs_eco1_EEF -0.127 0.128 -0.989 0.323 -0.422
111 tot_eco_main_EEF -0.068 0.123 -0.554 0.579 -0.356
112 eco2_vs_eco1_EEC 0.132 0.145 0.910 0.363 -0.253
113 eco3_vs_eco1_EEC 0.004 0.153 0.026 0.979 -0.387
114 eco_main_EEC 0.068 0.132 0.518 0.605 -0.290
115 ind_eco2_vs_eco1_IM_EEC 0.020 0.076 0.265 0.791 -0.147
116 ind_eco3_vs_eco1_IM_EEC -0.016 0.063 -0.258 0.796 -0.176
117 ind_eco_main_IM_EEC 0.002 0.055 0.036 0.972 -0.122
118 tot_eco2_vs_eco1_EEC 0.152 0.165 0.925 0.355 -0.231
119 tot_eco3_vs_eco1_EEC -0.012 0.142 -0.087 0.931 -0.390
120 tot_eco_main_EEC 0.070 0.137 0.513 0.608 -0.265
121 eco_main_IM 0.004 0.104 0.036 0.971 -0.230
125 eco3_vs_eco2_EEC -0.128 0.142 -0.907 0.364 -0.447
126 ind_eco3_vs_eco2_IM_EEC -0.036 0.087 -0.419 0.675 -0.255
127 tot_eco3_vs_eco2_EEC -0.165 0.141 -1.172 0.241 -0.526
131 reward_main_IM 0.021 0.102 0.206 0.837 -0.245
132 reward_eco3_EEF_vs_reward_eco1_EEF -0.012 0.197 -0.061 0.951 -0.451
133 reward_eco2_EEF_vs_reward_eco1_EEF -0.019 0.167 -0.113 0.910 -0.459
134 reward_eco2_EEC_vs_reward_eco1_EEC 0.079 0.210 0.375 0.708 -0.408
135 reward_eco3_EEC_vs_reward_eco2_EEC -0.153 0.204 -0.751 0.453 -0.520
137 reward_eco2_IM_vs_reward_eco1_IM 0.067 0.159 0.419 0.675 -0.297
138 reward_eco3_IM_vs_reward_eco1_IM -0.268 0.137 -1.957 0.050 -0.611
139 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.035 0.079 0.436 0.663 -0.163
140 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.139 0.080 -1.743 0.081 -0.407
141 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.174 0.095 -1.820 0.069 -0.451
142 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.113 0.227 0.500 0.617 -0.404
143 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.214 0.184 -1.163 0.245 -0.617
144 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.327 0.211 -1.551 0.121 -0.746
ci.upper std.lv std.all std.nox
82 0.486 0.147 0.053 0.147
86 0.147 0.012 0.008 0.012
87 0.516 0.160 0.061 0.160
91 0.387 0.100 0.038 0.100
95 0.164 0.011 0.007 0.011
96 0.381 0.111 0.045 0.111
98 0.110 -0.101 -0.036 -0.101
99 0.407 0.032 0.012 0.032
100 0.130 -0.066 -0.024 -0.066
101 0.324 0.043 0.017 0.043
102 0.198 -0.034 -0.016 -0.034
103 0.278 -0.043 -0.017 -0.043
104 0.137 -0.023 -0.009 -0.023
106 0.135 -0.018 -0.009 -0.018
107 0.158 0.002 0.000 0.002
108 0.314 0.009 0.003 0.009
110 0.140 -0.119 -0.044 -0.119
111 0.193 -0.064 -0.024 -0.064
112 0.337 0.137 0.054 0.137
113 0.299 0.004 -0.003 0.004
114 0.306 0.070 0.026 0.070
115 0.200 0.021 0.008 0.021
116 0.087 -0.017 -0.008 -0.017
117 0.095 0.002 0.000 0.002
118 0.502 0.157 0.062 0.157
119 0.284 -0.013 -0.010 -0.013
120 0.316 0.072 0.026 0.072
121 0.205 0.004 0.001 0.004
125 0.137 -0.133 -0.057 -0.133
126 0.129 -0.038 -0.016 -0.038
127 0.063 -0.170 -0.073 -0.170
131 0.231 0.023 0.014 0.023
132 0.356 -0.011 -0.007 -0.011
133 0.322 -0.018 -0.006 -0.018
134 0.423 0.081 0.033 0.081
135 0.311 -0.158 -0.067 -0.158
137 0.456 0.073 0.030 0.073
138 0.033 -0.294 -0.108 -0.294
139 0.244 0.036 0.015 0.036
140 0.011 -0.144 -0.053 -0.144
141 0.100 -0.179 -0.067 -0.179
142 0.484 0.117 0.048 0.117
143 0.115 -0.221 -0.087 -0.221
144 0.137 -0.338 -0.135 -0.338With control variableslavaan 0.6-21 ended normally after 61 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 53
Number of observations 234
Model Test User Model:
Standard Scaled
Test Statistic 233.101 217.589
Degrees of freedom 157 157
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.071
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2881.080 2318.492
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.243
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.972 0.971
Tucker-Lewis Index (TLI) 0.965 0.965
Robust Comparative Fit Index (CFI) 0.975
Robust Tucker-Lewis Index (TLI) 0.969
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4226.093 -4226.093
Scaling correction factor 1.707
for the MLR correction
Loglikelihood unrestricted model (H1) -4109.543 -4109.543
Scaling correction factor 1.232
for the MLR correction
Akaike (AIC) 8558.186 8558.186
Bayesian (BIC) 8741.318 8741.318
Sample-size adjusted Bayesian (SABIC) 8573.332 8573.332
Root Mean Square Error of Approximation:
RMSEA 0.046 0.041
90 Percent confidence interval - lower 0.033 0.027
90 Percent confidence interval - upper 0.057 0.053
P-value H_0: RMSEA <= 0.050 0.720 0.896
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.027
90 Percent confidence interval - upper 0.055
P-value H_0: Robust RMSEA <= 0.050 0.837
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.112 0.112
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 1.314 0.888
TR2 1.084 0.046 23.470 0.000 1.424 0.938
TR3 1.046 0.047 22.442 0.000 1.374 0.921
ADT =~
ADT1 1.000 0.823 0.840
ADT2 1.095 0.081 13.477 0.000 0.902 0.905
ADT3 1.109 0.077 14.353 0.000 0.913 0.860
IM =~
IM1 1.000 0.910 0.872
IM2 0.683 0.104 6.546 0.000 0.621 0.737
IM3 0.754 0.105 7.169 0.000 0.686 0.711
EEF =~
EEF1 1.000 1.057 0.910
EEF2 0.982 0.049 20.020 0.000 1.039 0.911
EEF3 0.948 0.043 21.899 0.000 1.003 0.897
EEC =~
EEC1 1.000 0.967 0.724
EEC2 1.275 0.105 12.096 0.000 1.233 0.873
EEC3 1.348 0.090 14.895 0.000 1.303 0.943
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.150 0.215 0.700 0.484 0.165 0.063
rwrd0_2 (b_02) 0.039 0.216 0.179 0.858 0.042 0.017
rwrd1_2 (b_12) 0.210 0.189 1.107 0.268 0.230 0.090
rwrd0_3 (b_03) 0.221 0.229 0.963 0.336 0.243 0.082
rwrd1_3 (b_13) -0.109 0.193 -0.564 0.573 -0.120 -0.041
PEB_yes (b_PE) 0.930 0.127 7.347 0.000 1.022 0.422
EEF ~
rwrd1_1 (c_11) 0.059 0.210 0.282 0.778 0.056 0.021
rwrd0_2 (c_02) -0.016 0.185 -0.087 0.930 -0.015 -0.006
rwrd1_2 (c_12) 0.027 0.170 0.158 0.874 0.026 0.010
rwrd0_3 (c_03) -0.198 0.182 -1.090 0.276 -0.188 -0.064
rwrd1_3 (c_13) 0.078 0.195 0.400 0.689 0.074 0.025
IM (c_IM) 0.697 0.098 7.139 0.000 0.600 0.600
PEB_yes (c_PE) 0.276 0.190 1.455 0.146 0.261 0.108
EEC ~
rwrd1_1 (d_11) 0.162 0.208 0.781 0.435 0.168 0.064
rwrd0_2 (d_02) 0.215 0.200 1.074 0.283 0.222 0.087
rwrd1_2 (d_12) 0.229 0.190 1.201 0.230 0.236 0.092
rwrd0_3 (d_03) 0.084 0.193 0.438 0.662 0.087 0.030
rwrd1_3 (d_13) 0.117 0.225 0.520 0.603 0.121 0.041
IM (d_IM) 0.586 0.089 6.553 0.000 0.551 0.551
PEB_yes (d_PE) -0.016 0.178 -0.088 0.930 -0.016 -0.007
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.119 0.059 2.030 0.042 0.119 0.309
TR ~~
ADT 0.434 0.089 4.892 0.000 0.401 0.401
.EEF ~~
.EEC 0.282 0.074 3.833 0.000 0.440 0.440
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.464 0.076 6.098 0.000 0.464 0.212
.TR2 0.278 0.067 4.143 0.000 0.278 0.120
.TR3 0.336 0.082 4.089 0.000 0.336 0.151
.ADT1 0.283 0.061 4.659 0.000 0.283 0.295
.ADT2 0.180 0.048 3.735 0.000 0.180 0.181
.ADT3 0.295 0.080 3.662 0.000 0.295 0.261
.IM1 0.260 0.072 3.634 0.000 0.260 0.239
.IM2 0.324 0.076 4.252 0.000 0.324 0.456
.IM3 0.462 0.171 2.706 0.007 0.462 0.495
.EEF1 0.231 0.051 4.525 0.000 0.231 0.171
.EEF2 0.222 0.042 5.304 0.000 0.222 0.171
.EEF3 0.245 0.057 4.277 0.000 0.245 0.196
.EEC1 0.848 0.096 8.856 0.000 0.848 0.475
.EEC2 0.475 0.097 4.900 0.000 0.475 0.238
.EEC3 0.212 0.062 3.407 0.001 0.212 0.111
TR 1.726 0.166 10.407 0.000 1.000 1.000
ADT 0.678 0.090 7.547 0.000 1.000 1.000
.IM 0.672 0.134 5.001 0.000 0.811 0.811
.EEF 0.639 0.118 5.398 0.000 0.571 0.571
.EEC 0.645 0.111 5.829 0.000 0.689 0.689
R-Square:
Estimate
TR1 0.788
TR2 0.880
TR3 0.849
ADT1 0.705
ADT2 0.819
ADT3 0.739
IM1 0.761
IM2 0.544
IM3 0.505
EEF1 0.829
EEF2 0.829
EEF3 0.804
EEC1 0.525
EEC2 0.762
EEC3 0.889
IM 0.189
EEF 0.429
EEC 0.311###Comparing difference between model fits