KMO
KMOKaiser-Meyer-Olkin factor adequacy
Call: KMO(r = efa_data_good2)
Overall MSA = 0.85
MSA for each item =
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2 TR3
0.90 0.85 0.84 0.87 0.88 0.90 0.90 0.84 0.81 0.88 0.79 0.82 0.85 0.76 0.81 R was not square, finding R from data$chisq
[1] 2813.971
$p.value
[1] 0
$df
[1] 105 IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1
IM1 1.0000000 0.64908860 0.62902842 0.5030574 0.5108604 0.5183923 0.4248093
IM2 0.6490886 1.00000000 0.67925656 0.4298624 0.4821681 0.4794951 0.3248557
IM3 0.6290284 0.67925656 1.00000000 0.3688290 0.4089743 0.4521843 0.4298071
EEF1 0.5030574 0.42986238 0.36882900 1.0000000 0.8385469 0.8178434 0.4839119
EEF2 0.5108604 0.48216812 0.40897434 0.8385469 1.0000000 0.8180608 0.4735416
EEF3 0.5183923 0.47949508 0.45218430 0.8178434 0.8180608 1.0000000 0.4629315
EEC1 0.4248093 0.32485572 0.42980715 0.4839119 0.4735416 0.4629315 1.0000000
EEC2 0.4828787 0.33831251 0.34707394 0.5096480 0.5369683 0.5144853 0.6026213
EEC3 0.4745346 0.27923503 0.33865752 0.5268661 0.5103938 0.5276385 0.7004753
ADT1 0.2885618 0.15203282 0.17343473 0.3502560 0.3481028 0.3415795 0.2441526
ADT2 0.1586372 0.05269908 0.09063625 0.2675603 0.2375339 0.2479717 0.2188936
ADT3 0.2033126 0.11299671 0.12783047 0.3264008 0.2792672 0.2675271 0.2203237
TR1 0.2062876 0.10241935 0.14494417 0.2198742 0.1589376 0.1832998 0.2189545
TR2 0.1977604 0.06607060 0.10209887 0.1614227 0.1201610 0.1748955 0.1221432
TR3 0.1810651 0.08823418 0.12436522 0.2163160 0.1570044 0.2092947 0.1712591
EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2
IM1 0.4828787 0.4745346 0.2885618 0.15863718 0.2033126 0.2062876 0.1977604
IM2 0.3383125 0.2792350 0.1520328 0.05269908 0.1129967 0.1024193 0.0660706
IM3 0.3470739 0.3386575 0.1734347 0.09063625 0.1278305 0.1449442 0.1020989
EEF1 0.5096480 0.5268661 0.3502560 0.26756025 0.3264008 0.2198742 0.1614227
EEF2 0.5369683 0.5103938 0.3481028 0.23753393 0.2792672 0.1589376 0.1201610
EEF3 0.5144853 0.5276385 0.3415795 0.24797169 0.2675271 0.1832998 0.1748955
EEC1 0.6026213 0.7004753 0.2441526 0.21889360 0.2203237 0.2189545 0.1221432
EEC2 1.0000000 0.8310923 0.3159584 0.27070040 0.3008276 0.2327578 0.1521836
EEC3 0.8310923 1.0000000 0.3298560 0.27175711 0.2712304 0.3003763 0.2332533
ADT1 0.3159584 0.3298560 1.0000000 0.75330321 0.7169065 0.3262829 0.3278455
ADT2 0.2707004 0.2717571 0.7533032 1.00000000 0.7793729 0.3017116 0.2866740
ADT3 0.3008276 0.2712304 0.7169065 0.77937291 1.0000000 0.3147076 0.2761688
TR1 0.2327578 0.3003763 0.3262829 0.30171165 0.3147076 1.0000000 0.8371579
TR2 0.1521836 0.2332533 0.3278455 0.28667398 0.2761688 0.8371579 1.0000000
TR3 0.1680663 0.2533074 0.3439945 0.29667897 0.3435770 0.8170855 0.8646461
TR3
IM1 0.18106513
IM2 0.08823418
IM3 0.12436522
EEF1 0.21631603
EEF2 0.15700443
EEF3 0.20929468
EEC1 0.17125909
EEC2 0.16806631
EEC3 0.25330741
ADT1 0.34399446
ADT2 0.29667897
ADT3 0.34357699
TR1 0.81708555
TR2 0.86464614
TR3 1.00000000
Loading required namespace: GPArotationThreshold = 0.35
Loadings:
MR1 MR2 MR3 MR4 MR5
IM1 NA NA NA NA 0.659
IM2 NA NA NA NA 0.837
IM3 NA NA NA NA 0.841
EEF1 0.933 NA NA NA NA
EEF2 0.910 NA NA NA NA
EEF3 0.841 NA NA NA NA
EEC1 NA NA NA 0.603 NA
EEC2 NA NA NA 0.758 NA
EEC3 NA NA NA 1.020 NA
ADT1 NA NA 0.791 NA NA
ADT2 NA NA 0.936 NA NA
ADT3 NA NA 0.854 NA NA
TR1 NA 0.870 NA NA NA
TR2 NA 0.959 NA NA NA
TR3 NA 0.912 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 0.200 0.357 0.588 0.581
2 0.200 1.000 0.378 0.258 0.143
3 0.357 0.378 1.000 0.338 0.165
4 0.588 0.258 0.338 1.000 0.435
5 0.581 0.143 0.165 0.435 1.000
1 2 3 4 5
1 1.000 0.201 0.357 0.591 0.582
2 0.201 1.000 0.378 0.259 0.143
3 0.357 0.378 1.000 0.338 0.165
4 0.591 0.259 0.338 1.000 0.438
5 0.582 0.143 0.165 0.438 1.000lavaan 0.6-21 ended normally after 34 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 21
Number of observations 243
Model Test User Model:
Standard Scaled
Test Statistic 67.048 50.319
Degrees of freedom 24 24
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.332
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1637.509 874.691
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.872
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.973 0.969
Tucker-Lewis Index (TLI) 0.960 0.953
Robust Comparative Fit Index (CFI) 0.978
Robust Tucker-Lewis Index (TLI) 0.966
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2619.525 -2619.525
Scaling correction factor 2.246
for the MLR correction
Loglikelihood unrestricted model (H1) -2586.001 -2586.001
Scaling correction factor 1.759
for the MLR correction
Akaike (AIC) 5281.049 5281.049
Bayesian (BIC) 5354.404 5354.404
Sample-size adjusted Bayesian (SABIC) 5287.837 5287.837
Root Mean Square Error of Approximation:
RMSEA 0.086 0.067
90 Percent confidence interval - lower 0.062 0.044
90 Percent confidence interval - upper 0.111 0.090
P-value H_0: RMSEA <= 0.050 0.009 0.101
P-value H_0: RMSEA >= 0.080 0.678 0.185
Robust RMSEA 0.078
90 Percent confidence interval - lower 0.047
90 Percent confidence interval - upper 0.108
P-value H_0: Robust RMSEA <= 0.050 0.066
P-value H_0: Robust RMSEA >= 0.080 0.475
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 1.268 0.099 12.767 0.000 1.073 1.462
EEC3 1.332 0.085 15.607 0.000 1.164 1.499
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.988 0.047 21.207 0.000 0.896 1.079
EEF3 0.943 0.043 21.691 0.000 0.857 1.028
IM =~
IM1 1.000 1.000 1.000
IM2 0.807 0.088 9.143 0.000 0.634 0.980
IM3 0.895 0.108 8.307 0.000 0.684 1.106
Std.lv Std.all
0.979 0.733
1.241 0.875
1.303 0.945
1.078 0.911
1.065 0.916
1.016 0.898
0.853 0.815
0.689 0.816
0.763 0.791
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC ~~
EEF 0.663 0.105 6.343 0.000 0.458 0.868
IM 0.429 0.090 4.750 0.000 0.252 0.606
EEF ~~
IM 0.580 0.089 6.545 0.000 0.406 0.753
Std.lv Std.all
0.629 0.629
0.514 0.514
0.631 0.631
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.824 0.093 8.879 0.000 0.642 1.006
.EEC2 0.469 0.094 4.968 0.000 0.284 0.654
.EEC3 0.203 0.058 3.492 0.000 0.089 0.318
.EEF1 0.238 0.049 4.833 0.000 0.142 0.335
.EEF2 0.219 0.041 5.314 0.000 0.138 0.299
.EEF3 0.246 0.056 4.421 0.000 0.137 0.356
.IM1 0.367 0.068 5.383 0.000 0.234 0.501
.IM2 0.238 0.059 4.019 0.000 0.122 0.354
.IM3 0.349 0.180 1.939 0.052 -0.004 0.701
EEC 0.958 0.141 6.787 0.000 0.681 1.234
EEF 1.162 0.168 6.918 0.000 0.833 1.491
IM 0.728 0.104 7.018 0.000 0.524 0.931
Std.lv Std.all
0.824 0.462
0.469 0.234
0.203 0.107
0.238 0.170
0.219 0.162
0.246 0.193
0.367 0.335
0.238 0.334
0.349 0.375
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.538
EEC2 0.766
EEC3 0.893
EEF1 0.830
EEF2 0.838
EEF3 0.807
IM1 0.665
IM2 0.666
IM3 0.625Cronbach’s Alpha: EEC EEF IM
0.881 0.934 0.844 Omega: EEC EEF IM
0.899 0.934 0.848 Average Variance Extracted (AVE): EEC EEF IM
0.737 0.826 0.652 Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
28 EEC =~ IM1 17.138 0.271 0.265 0.253 0.253
29 EEC =~ IM2 11.803 -0.181 -0.177 -0.210 -0.210
39 IM =~ EEC3 10.933 -0.276 -0.235 -0.171 -0.171
43 EEC1 ~~ EEC2 11.184 -0.240 -0.240 -0.386 -0.386
50 EEC1 ~~ IM3 11.024 0.136 0.136 0.253 0.253
62 EEC3 ~~ IM2 10.022 -0.082 -0.082 -0.371 -0.371
78 IM2 ~~ IM3 11.983 0.148 0.148 0.513 0.513Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
43 EEC1 ~~ EEC2 11.184 -0.240 -0.240 -0.386 -0.386
50 EEC1 ~~ IM3 11.024 0.136 0.136 0.253 0.253
62 EEC3 ~~ IM2 10.022 -0.082 -0.082 -0.371 -0.371
78 IM2 ~~ IM3 11.983 0.148 0.148 0.513 0.513$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.074 0.000
EEC3 0.014 0.007 0.000
EEF1 0.101 0.014 -0.023 0.000
EEF2 0.080 0.055 -0.054 0.006 0.000
EEF3 0.074 0.032 -0.009 -0.001 -0.006 0.000
IM1 0.164 0.172 0.113 0.043 0.049 0.067 0.000
IM2 0.020 -0.034 -0.136 -0.039 0.011 0.017 -0.014 0.000
IM3 0.170 -0.012 -0.061 -0.098 -0.053 0.005 -0.016 0.028 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -1.722 0.000
EEC3 0.348 0.107 0.000
EEF1 1.478 0.225 -0.392 0.000
EEF2 1.355 0.918 -1.006 0.232 0.000
EEF3 1.148 0.570 -0.180 -0.031 -0.297 0.000
IM1 2.354 2.566 1.884 0.725 0.888 1.184 0.000
IM2 0.370 -0.815 -2.805 -0.700 0.331 0.399 -0.971 0.000
IM3 1.906 -0.228 -1.263 -2.075 -1.390 0.114 -0.750 1.332 0.000Allowing 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 243
Model Test User Model:
Standard Scaled
Test Statistic 55.152 42.845
Degrees of freedom 23 23
P-value (Chi-square) 0.000 0.007
Scaling correction factor 1.287
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1637.509 874.691
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.872
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.980 0.976
Tucker-Lewis Index (TLI) 0.969 0.963
Robust Comparative Fit Index (CFI) 0.984
Robust Tucker-Lewis Index (TLI) 0.975
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2613.576 -2613.576
Scaling correction factor 2.252
for the MLR correction
Loglikelihood unrestricted model (H1) -2586.001 -2586.001
Scaling correction factor 1.759
for the MLR correction
Akaike (AIC) 5271.153 5271.153
Bayesian (BIC) 5348.000 5348.000
Sample-size adjusted Bayesian (SABIC) 5278.263 5278.263
Root Mean Square Error of Approximation:
RMSEA 0.076 0.060
90 Percent confidence interval - lower 0.050 0.034
90 Percent confidence interval - upper 0.102 0.084
P-value H_0: RMSEA <= 0.050 0.048 0.241
P-value H_0: RMSEA >= 0.080 0.421 0.085
Robust RMSEA 0.068
90 Percent confidence interval - lower 0.035
90 Percent confidence interval - upper 0.099
P-value H_0: Robust RMSEA <= 0.050 0.167
P-value H_0: Robust RMSEA >= 0.080 0.277
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 1.269 0.100 12.706 0.000 1.073 1.464
EEC3 1.332 0.085 15.584 0.000 1.164 1.499
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.985 0.047 20.774 0.000 0.892 1.078
EEF3 0.940 0.043 21.655 0.000 0.855 1.025
IM =~
IM1 1.000 1.000 1.000
IM2 0.653 0.103 6.365 0.000 0.452 0.854
IM3 0.722 0.099 7.274 0.000 0.528 0.917
Std.lv Std.all
0.978 0.733
1.241 0.876
1.303 0.945
1.080 0.912
1.064 0.915
1.015 0.897
0.937 0.896
0.612 0.725
0.677 0.702
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.139 0.063 2.196 0.028 0.015 0.263
EEC ~~
EEF 0.664 0.104 6.354 0.000 0.459 0.869
IM 0.514 0.095 5.415 0.000 0.328 0.700
EEF ~~
IM 0.648 0.092 7.021 0.000 0.467 0.828
Std.lv Std.all
0.139 0.347
0.629 0.629
0.560 0.560
0.640 0.640
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.825 0.093 8.832 0.000 0.642 1.008
.EEC2 0.468 0.095 4.943 0.000 0.282 0.654
.EEC3 0.204 0.059 3.459 0.001 0.088 0.320
.EEF1 0.234 0.050 4.680 0.000 0.136 0.333
.EEF2 0.220 0.041 5.309 0.000 0.139 0.301
.EEF3 0.249 0.056 4.462 0.000 0.140 0.358
.IM1 0.216 0.073 2.963 0.003 0.073 0.360
.IM2 0.338 0.078 4.321 0.000 0.185 0.491
.IM3 0.473 0.164 2.883 0.004 0.151 0.794
EEC 0.957 0.141 6.781 0.000 0.680 1.234
EEF 1.166 0.169 6.916 0.000 0.835 1.496
IM 0.879 0.136 6.482 0.000 0.613 1.144
Std.lv Std.all
0.825 0.463
0.468 0.233
0.204 0.107
0.234 0.167
0.220 0.163
0.249 0.195
0.216 0.198
0.338 0.474
0.473 0.508
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.537
EEC2 0.767
EEC3 0.893
EEF1 0.833
EEF2 0.837
EEF3 0.805
IM1 0.802
IM2 0.526
IM3 0.492Cronbach’s Alpha: EEC EEF IM
0.881 0.934 0.844 Omega: EEC EEF IM
0.899 0.934 0.792 Average Variance Extracted (AVE): EEC EEF IM
0.737 0.826 0.625 Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
44 EEC1 ~~ EEC2 10.716 -0.230 -0.230 -0.369 -0.369
51 EEC1 ~~ IM3 10.938 0.134 0.134 0.214 0.214Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
44 EEC1 ~~ EEC2 10.716 -0.230 -0.230 -0.369 -0.369
51 EEC1 ~~ IM3 10.938 0.134 0.134 0.214 0.214$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.074 0.000
EEC3 0.015 0.007 0.000
EEF1 0.100 0.012 -0.025 0.000
EEF2 0.081 0.055 -0.053 0.005 0.000
EEF3 0.075 0.033 -0.008 -0.001 -0.004 0.000
IM1 0.080 0.064 0.000 -0.025 -0.017 0.005 0.000
IM2 0.031 -0.021 -0.122 0.006 0.057 0.060 0.000 0.000
IM3 0.182 0.004 -0.044 -0.047 -0.002 0.054 0.001 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -2.703 0.000
EEC3 0.581 0.403 0.000
EEF1 1.642 0.269 -0.705 0.000
EEF2 1.392 1.209 -1.565 0.246 0.000
EEF3 1.244 0.768 -0.229 -0.079 -0.251 0.000
IM1 1.304 1.680 0.025 -0.905 -0.578 0.159 0.000
IM2 0.544 -0.562 -2.732 0.148 1.550 1.665 -0.029 0.000
IM3 1.937 0.067 -0.829 -1.285 -0.053 1.665 0.029 0.000 0.000Allowing covariance between IM2 ~~ IM3 and EEC1 ~~ EEC2lavaan 0.6-21 ended normally after 38 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 23
Number of observations 243
Model Test User Model:
Standard Scaled
Test Statistic 42.821 32.519
Degrees of freedom 22 22
P-value (Chi-square) 0.005 0.069
Scaling correction factor 1.317
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1637.509 874.691
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.872
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.987 0.987
Tucker-Lewis Index (TLI) 0.979 0.979
Robust Comparative Fit Index (CFI) 0.991
Robust Tucker-Lewis Index (TLI) 0.986
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2607.411 -2607.411
Scaling correction factor 2.182
for the MLR correction
Loglikelihood unrestricted model (H1) -2586.001 -2586.001
Scaling correction factor 1.759
for the MLR correction
Akaike (AIC) 5260.822 5260.822
Bayesian (BIC) 5341.163 5341.163
Sample-size adjusted Bayesian (SABIC) 5268.256 5268.256
Root Mean Square Error of Approximation:
RMSEA 0.062 0.044
90 Percent confidence interval - lower 0.034 0.005
90 Percent confidence interval - upper 0.090 0.071
P-value H_0: RMSEA <= 0.050 0.213 0.604
P-value H_0: RMSEA >= 0.080 0.158 0.011
Robust RMSEA 0.051
90 Percent confidence interval - lower 0.000
90 Percent confidence interval - upper 0.086
P-value H_0: Robust RMSEA <= 0.050 0.448
P-value H_0: Robust RMSEA >= 0.080 0.090
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 1.242 0.093 13.290 0.000 1.059 1.426
EEC3 1.165 0.098 11.930 0.000 0.974 1.357
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.988 0.047 20.828 0.000 0.895 1.081
EEF3 0.940 0.043 21.684 0.000 0.855 1.025
IM =~
IM1 1.000 1.000 1.000
IM2 0.664 0.098 6.757 0.000 0.472 0.857
IM3 0.736 0.096 7.660 0.000 0.547 0.924
Std.lv Std.all
1.057 0.792
1.313 0.927
1.232 0.893
1.079 0.912
1.066 0.917
1.014 0.897
0.929 0.888
0.617 0.731
0.683 0.708
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.131 0.062 2.116 0.034 0.010 0.253
.EEC1 ~~
.EEC2 -0.248 0.072 -3.447 0.001 -0.389 -0.107
EEC ~~
EEF 0.722 0.106 6.808 0.000 0.514 0.929
IM 0.567 0.094 6.023 0.000 0.383 0.752
EEF ~~
IM 0.645 0.092 6.997 0.000 0.464 0.825
Std.lv Std.all
0.131 0.335
-0.248 -0.571
0.633 0.633
0.577 0.577
0.643 0.643
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.665 0.114 5.807 0.000 0.440 0.889
.EEC2 0.284 0.109 2.614 0.009 0.071 0.496
.EEC3 0.385 0.086 4.494 0.000 0.217 0.553
.EEF1 0.236 0.050 4.716 0.000 0.138 0.334
.EEF2 0.216 0.040 5.353 0.000 0.137 0.295
.EEF3 0.251 0.057 4.436 0.000 0.140 0.362
.IM1 0.232 0.069 3.343 0.001 0.096 0.368
.IM2 0.331 0.076 4.338 0.000 0.182 0.481
.IM3 0.464 0.162 2.865 0.004 0.147 0.782
EEC 1.117 0.161 6.953 0.000 0.802 1.432
EEF 1.164 0.168 6.908 0.000 0.834 1.494
IM 0.863 0.128 6.732 0.000 0.612 1.114
Std.lv Std.all
0.665 0.373
0.284 0.141
0.385 0.202
0.236 0.169
0.216 0.160
0.251 0.196
0.232 0.212
0.331 0.465
0.464 0.498
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.627
EEC2 0.859
EEC3 0.798
EEF1 0.831
EEF2 0.840
EEF3 0.804
IM1 0.788
IM2 0.535
IM3 0.502Cronbach’s Alpha: EEC EEF IM
0.881 0.934 0.844 Omega: EEC EEF IM
0.940 0.934 0.794 Average Variance Extracted (AVE): EEC EEF IM
0.766 0.826 0.625 Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 10.342 0.128 0.128 0.23 0.23Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 10.342 0.128 0.128 0.23 0.23$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.012 0.007 0.000
EEF1 0.043 -0.042 0.019 0.000
EEF2 0.022 -0.001 -0.012 0.004 0.000
EEF3 0.021 -0.018 0.033 0.001 -0.005 0.000
IM1 0.026 0.012 0.024 -0.022 -0.015 0.008 0.000
IM2 -0.011 -0.063 -0.114 0.001 0.050 0.055 0.000 0.000
IM3 0.136 -0.044 -0.035 -0.053 -0.010 0.048 0.000 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.476 0.350 0.000
EEF1 0.858 -0.941 0.516 0.000
EEF2 0.462 -0.024 -0.376 0.271 0.000
EEF3 0.416 -0.451 0.865 0.052 -0.473 0.000
IM1 0.483 0.409 0.711 -0.878 -0.512 0.272 0.000
IM2 -0.193 -1.896 -2.766 0.022 1.341 1.528 -0.021 0.000
IM3 1.422 -0.781 -0.737 -1.426 -0.236 1.474 0.017 0.000 0.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC
IM "1" "0.64 (0)" "0.58 (0)"
EEF "0.64 (0)" "1" "0.63 (0)"
EEC "0.58 (0)" "0.63 (0)" "1" Discriminant validity check lhs op rhs est.std se z pvalue ci.lower ci.upper
1 EEC =~ EEC1 0.792 0.040 19.840 0 0.714 0.870
2 EEC =~ EEC2 0.927 0.029 31.483 0 0.869 0.984
3 EEC =~ EEC3 0.893 0.027 32.688 0 0.840 0.947
4 EEF =~ EEF1 0.912 0.021 44.342 0 0.871 0.952
5 EEF =~ EEF2 0.917 0.018 52.306 0 0.882 0.951
6 EEF =~ EEF3 0.897 0.028 32.121 0 0.842 0.951
7 IM =~ IM1 0.888 0.037 23.923 0 0.815 0.961
8 IM =~ IM2 0.731 0.069 10.575 0 0.596 0.867
9 IM =~ IM3 0.708 0.090 7.876 0 0.532 0.884AVE (IM, EEF, EEC)[1] 0.6082245[1] 0.8250884[1] 0.7611189Square root of AVE (IM, EEF, EEC)[1] 0.7798875[1] 0.9083438[1] 0.8724213 lhs rhs est.std
24 EEC EEF 0.633
25 EEC IM 0.577
26 EEF IM 0.643Correlations between square root AVE with correlations (sqrt vs. correlations with the other constructsIM[1] 0.7798875[1] 0.6432243[1] 0.577488EEF[1] 0.9083438[1] 0.6432243[1] 0.6328516EEC[1] 0.8724213[1] 0.577488[1] 0.6328516lavaan 0.6-21 ended normally after 48 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 243
Model Test User Model:
Standard Scaled
Test Statistic 123.486 105.195
Degrees of freedom 79 79
P-value (Chi-square) 0.001 0.026
Scaling correction factor 1.174
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2895.391 1959.933
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.477
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.984 0.986
Tucker-Lewis Index (TLI) 0.979 0.981
Robust Comparative Fit Index (CFI) 0.989
Robust Tucker-Lewis Index (TLI) 0.985
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4388.631 -4388.631
Scaling correction factor 1.915
for the MLR correction
Loglikelihood unrestricted model (H1) -4326.888 -4326.888
Scaling correction factor 1.427
for the MLR correction
Akaike (AIC) 8859.262 8859.262
Bayesian (BIC) 9002.477 9002.477
Sample-size adjusted Bayesian (SABIC) 8872.513 8872.513
Root Mean Square Error of Approximation:
RMSEA 0.048 0.037
90 Percent confidence interval - lower 0.031 0.016
90 Percent confidence interval - upper 0.064 0.053
P-value H_0: RMSEA <= 0.050 0.557 0.902
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.040
90 Percent confidence interval - lower 0.015
90 Percent confidence interval - upper 0.059
P-value H_0: Robust RMSEA <= 0.050 0.790
P-value H_0: Robust RMSEA >= 0.080 0.000
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
IM =~
IM1 1.000 1.000 1.000
IM2 0.650 0.106 6.109 0.000 0.441 0.858
IM3 0.719 0.102 7.046 0.000 0.519 0.920
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.984 0.048 20.520 0.000 0.890 1.078
EEF3 0.938 0.044 21.563 0.000 0.853 1.024
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.268 0.099 12.750 0.000 1.073 1.463
EEC3 1.337 0.086 15.496 0.000 1.168 1.506
TR =~
TR1 1.000 1.000 1.000
TR2 1.081 0.045 23.893 0.000 0.992 1.170
TR3 1.046 0.046 22.879 0.000 0.956 1.135
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.067 0.080 13.383 0.000 0.911 1.223
ADT3 1.099 0.076 14.423 0.000 0.950 1.249
Std.lv Std.all
0.939 0.898
0.611 0.723
0.676 0.700
1.081 0.913
1.063 0.915
1.014 0.897
0.977 0.732
1.238 0.874
1.306 0.947
1.313 0.892
1.420 0.938
1.373 0.920
0.832 0.843
0.888 0.893
0.915 0.864
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.141 0.065 2.165 0.030 0.013 0.268
IM ~~
EEF 0.649 0.093 6.997 0.000 0.467 0.830
EEC 0.513 0.095 5.368 0.000 0.325 0.700
TR 0.262 0.110 2.386 0.017 0.047 0.477
ADT 0.190 0.071 2.676 0.007 0.051 0.329
EEF ~~
EEC 0.662 0.105 6.335 0.000 0.457 0.867
TR 0.294 0.110 2.669 0.008 0.078 0.510
ADT 0.330 0.079 4.169 0.000 0.175 0.485
EEC ~~
TR 0.347 0.100 3.486 0.000 0.152 0.542
ADT 0.291 0.069 4.238 0.000 0.156 0.426
TR ~~
ADT 0.421 0.087 4.830 0.000 0.250 0.592
Std.lv Std.all
0.141 0.350
0.639 0.639
0.559 0.559
0.212 0.212
0.243 0.243
0.627 0.627
0.207 0.207
0.367 0.367
0.271 0.271
0.358 0.358
0.385 0.385
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.212 0.079 2.706 0.007 0.059 0.366
.IM2 0.340 0.079 4.279 0.000 0.184 0.495
.IM3 0.474 0.163 2.912 0.004 0.155 0.794
.EEF1 0.232 0.050 4.602 0.000 0.133 0.331
.EEF2 0.221 0.042 5.296 0.000 0.139 0.303
.EEF3 0.250 0.056 4.489 0.000 0.141 0.359
.EEC1 0.827 0.093 8.890 0.000 0.645 1.010
.EEC2 0.475 0.095 4.974 0.000 0.288 0.662
.EEC3 0.195 0.060 3.271 0.001 0.078 0.312
.TR1 0.443 0.074 6.006 0.000 0.299 0.588
.TR2 0.276 0.065 4.228 0.000 0.148 0.405
.TR3 0.340 0.080 4.230 0.000 0.183 0.498
.ADT1 0.281 0.060 4.648 0.000 0.162 0.399
.ADT2 0.200 0.048 4.150 0.000 0.106 0.294
.ADT3 0.284 0.076 3.732 0.000 0.135 0.433
IM 0.882 0.142 6.232 0.000 0.605 1.160
EEF 1.168 0.169 6.913 0.000 0.837 1.499
EEC 0.954 0.141 6.785 0.000 0.679 1.230
TR 1.724 0.160 10.753 0.000 1.410 2.038
ADT 0.692 0.090 7.722 0.000 0.517 0.868
Std.lv Std.all
0.212 0.194
0.340 0.477
0.474 0.510
0.232 0.166
0.221 0.163
0.250 0.195
0.827 0.464
0.475 0.236
0.195 0.103
0.443 0.205
0.276 0.121
0.340 0.153
0.281 0.289
0.200 0.202
0.284 0.253
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.806
IM2 0.523
IM3 0.490
EEF1 0.834
EEF2 0.837
EEF3 0.805
EEC1 0.536
EEC2 0.764
EEC3 0.897
TR1 0.795
TR2 0.879
TR3 0.847
ADT1 0.711
ADT2 0.798
ADT3 0.747Cronbach’s Alpha: IM EEF EEC TR ADT
0.844 0.934 0.881 0.940 0.899 Omega: IM EEF EEC TR ADT
0.791 0.934 0.899 0.941 0.902 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.625 0.826 0.737 0.841 0.752 $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 -0.021 0.008 -0.040 0.000
EEF2 -0.014 0.060 0.000 0.003 0.000
EEF3 0.004 0.065 0.051 -0.001 -0.002 0.000
EEC1 0.058 0.029 0.144 0.065 0.054 0.051 0.000
EEC2 0.045 -0.015 0.005 0.009 0.036 0.023 -0.037 0.000
EEC3 0.000 -0.103 -0.032 -0.016 -0.033 -0.005 0.007 0.003 0.000
TR1 0.036 -0.035 0.012 0.051 -0.010 0.017 0.042 0.022 0.072 0.000
TR2 0.019 -0.078 -0.037 -0.016 -0.058 0.001 -0.064 -0.070 -0.007 0.001
TR3 0.005 -0.053 -0.013 0.042 -0.018 0.038 -0.011 -0.050 0.017 -0.004
ADT1 0.105 0.004 0.030 0.068 0.065 0.064 0.023 0.052 0.044 0.037
ADT2 -0.036 -0.104 -0.061 -0.032 -0.062 -0.046 -0.015 -0.009 -0.031 -0.005
ADT3 0.015 -0.039 -0.019 0.037 -0.011 -0.017 -0.006 0.030 -0.022 0.018
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.002 0.000
ADT1 0.023 0.045 0.000
ADT2 -0.036 -0.020 0.000 0.000
ADT3 -0.036 0.037 -0.012 0.008 0.000
$cov.z
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.009 0.000
IM3 0.010 0.000 0.000
EEF1 -0.643 0.173 -1.031 0.000
EEF2 -0.438 1.352 -0.005 0.116 0.000
EEF3 0.108 1.472 1.476 -0.060 -0.092 0.000
EEC1 1.233 0.555 1.840 1.514 1.348 1.212 0.000
EEC2 1.551 -0.425 0.105 0.274 1.200 0.728 -1.360 0.000
EEC3 -0.019 -2.601 -0.656 -0.591 -1.206 -0.178 0.275 0.134 0.000
TR1 1.013 -0.873 0.196 1.412 -0.344 0.476 0.874 0.582 2.250 0.000
TR2 0.632 -1.893 -0.808 -0.475 -2.059 0.015 -1.343 -1.986 -0.336 0.032
TR3 0.170 -1.240 -0.211 1.313 -0.552 1.061 -0.240 -1.356 0.702 -0.147
ADT1 2.733 0.085 0.666 1.614 1.600 1.606 0.483 1.265 1.550 0.780
ADT2 -1.148 -2.182 -1.290 -1.001 -1.861 -1.418 -0.349 -0.251 -1.381 -0.149
ADT3 0.449 -0.946 -0.348 1.047 -0.287 -0.479 -0.145 0.826 -0.798 0.499
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.053 0.000
ADT1 0.613 1.036 0.000
ADT2 -1.289 -0.610 0.000 0.000
ADT3 -1.073 1.071 -0.642 0.438 0.000
$summary
cov
srmr 0.038
srmr.se 0.006
srmr.exactfit.z 0.332
srmr.exactfit.pvalue 0.370
usrmr 0.011
usrmr.se 0.008
usrmr.ci.lower -0.002
usrmr.ci.upper 0.024
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -4.935
usrmr.closefit.pvalue 1.000 IM EEF EEC TR ADT
IM 1.000
EEF 0.639 1.000
EEC 0.559 0.627 1.000
TR 0.212 0.207 0.271 1.000
ADT 0.243 0.367 0.358 0.385 1.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC TR ADT
IM "1" "0.64 (0)" "0.56 (0)" "0.21 (0.008)" "0.24 (0.001)"
EEF "0.64 (0)" "1" "0.63 (0)" "0.21 (0.003)" "0.37 (0)"
EEC "0.56 (0)" "0.63 (0)" "1" "0.27 (0)" "0.36 (0)"
TR "0.21 (0.008)" "0.21 (0.003)" "0.27 (0)" "1" "0.39 (0)"
ADT "0.24 (0.001)" "0.37 (0)" "0.36 (0)" "0.39 (0)" "1" Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 10.941 0.134 0.134 0.213 0.213Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 10.941 0.134 0.134 0.213 0.213$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.000 0.000
IM3 0.000 0.000 0.000
EEF1 -0.026 0.008 -0.045 0.000
EEF2 -0.017 0.058 0.000 0.004 0.000
EEF3 0.005 0.062 0.056 -0.002 -0.003 0.000
EEC1 0.081 0.033 0.185 0.102 0.083 0.077 0.000
EEC2 0.066 -0.018 0.007 0.015 0.059 0.037 -0.070 0.000
EEC3 -0.001 -0.120 -0.042 -0.026 -0.053 -0.008 0.013 0.006 0.000
TR1 0.056 -0.043 0.017 0.089 -0.017 0.029 0.083 0.046 0.146 0.000
TR2 0.030 -0.100 -0.055 -0.029 -0.101 0.001 -0.128 -0.149 -0.015 0.002
TR3 0.009 -0.067 -0.018 0.074 -0.030 0.064 -0.022 -0.105 0.036 -0.008
ADT1 0.108 0.003 0.029 0.079 0.075 0.071 0.030 0.073 0.060 0.053
ADT2 -0.037 -0.087 -0.059 -0.037 -0.072 -0.052 -0.020 -0.012 -0.043 -0.007
ADT3 0.017 -0.035 -0.019 0.046 -0.013 -0.020 -0.009 0.046 -0.032 0.028
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.003 0.000
ADT1 0.035 0.066 0.000
ADT2 -0.054 -0.030 0.000 0.000
ADT3 -0.058 0.059 -0.012 0.008 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.009 0.000
IM3 0.010 0.000 0.000
EEF1 -0.643 0.173 -1.031 0.000
EEF2 -0.438 1.352 -0.005 0.116 0.000
EEF3 0.108 1.472 1.476 -0.060 -0.092 0.000
EEC1 1.233 0.555 1.840 1.514 1.348 1.212 0.000
EEC2 1.551 -0.425 0.105 0.274 1.200 0.728 -1.360 0.000
EEC3 -0.019 -2.601 -0.656 -0.591 -1.206 -0.178 0.275 0.134 0.000
TR1 1.013 -0.873 0.196 1.412 -0.344 0.476 0.874 0.582 2.250 0.000
TR2 0.632 -1.893 -0.808 -0.475 -2.059 0.015 -1.343 -1.986 -0.336 0.032
TR3 0.170 -1.240 -0.211 1.313 -0.552 1.061 -0.240 -1.356 0.702 -0.147
ADT1 2.733 0.085 0.666 1.614 1.600 1.606 0.483 1.265 1.550 0.780
ADT2 -1.148 -2.182 -1.290 -1.001 -1.861 -1.418 -0.349 -0.251 -1.381 -0.149
ADT3 0.449 -0.946 -0.348 1.047 -0.287 -0.479 -0.145 0.826 -0.798 0.499
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.053 0.000
ADT1 0.613 1.036 0.000
ADT2 -1.289 -0.610 0.006 0.000
ADT3 -1.073 1.071 -0.642 0.438 0.000lavaan 0.6-21 ended normally after 48 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 243
Model Test User Model:
Standard Scaled
Test Statistic 123.486 105.195
Degrees of freedom 79 79
P-value (Chi-square) 0.001 0.026
Scaling correction factor 1.174
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2895.391 1959.933
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.477
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.984 0.986
Tucker-Lewis Index (TLI) 0.979 0.981
Robust Comparative Fit Index (CFI) 0.989
Robust Tucker-Lewis Index (TLI) 0.985
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4388.631 -4388.631
Scaling correction factor 1.915
for the MLR correction
Loglikelihood unrestricted model (H1) -4326.888 -4326.888
Scaling correction factor 1.427
for the MLR correction
Akaike (AIC) 8859.262 8859.262
Bayesian (BIC) 9002.477 9002.477
Sample-size adjusted Bayesian (SABIC) 8872.513 8872.513
Root Mean Square Error of Approximation:
RMSEA 0.048 0.037
90 Percent confidence interval - lower 0.031 0.016
90 Percent confidence interval - upper 0.064 0.053
P-value H_0: RMSEA <= 0.050 0.557 0.902
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.040
90 Percent confidence interval - lower 0.015
90 Percent confidence interval - upper 0.059
P-value H_0: Robust RMSEA <= 0.050 0.790
P-value H_0: Robust RMSEA >= 0.080 0.000
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
IM =~
IM1 1.000 1.000 1.000
IM2 0.650 0.106 6.109 0.000 0.441 0.858
IM3 0.719 0.102 7.046 0.000 0.519 0.920
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.984 0.048 20.520 0.000 0.890 1.078
EEF3 0.938 0.044 21.563 0.000 0.853 1.024
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.268 0.099 12.750 0.000 1.073 1.463
EEC3 1.337 0.086 15.496 0.000 1.168 1.506
TR =~
TR1 1.000 1.000 1.000
TR2 1.081 0.045 23.893 0.000 0.992 1.170
TR3 1.046 0.046 22.879 0.000 0.956 1.135
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.067 0.080 13.383 0.000 0.911 1.223
ADT3 1.099 0.076 14.423 0.000 0.950 1.249
Std.lv Std.all
0.939 0.898
0.611 0.723
0.676 0.700
1.081 0.913
1.063 0.915
1.014 0.897
0.977 0.732
1.238 0.874
1.306 0.947
1.313 0.892
1.420 0.938
1.373 0.920
0.832 0.843
0.888 0.893
0.915 0.864
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.141 0.065 2.165 0.030 0.013 0.268
IM ~~
EEF 0.649 0.093 6.997 0.000 0.467 0.830
EEC 0.513 0.095 5.368 0.000 0.325 0.700
TR 0.262 0.110 2.386 0.017 0.047 0.477
ADT 0.190 0.071 2.676 0.007 0.051 0.329
EEF ~~
EEC 0.662 0.105 6.335 0.000 0.457 0.867
TR 0.294 0.110 2.669 0.008 0.078 0.510
ADT 0.330 0.079 4.169 0.000 0.175 0.485
EEC ~~
TR 0.347 0.100 3.486 0.000 0.152 0.542
ADT 0.291 0.069 4.238 0.000 0.156 0.426
TR ~~
ADT 0.421 0.087 4.830 0.000 0.250 0.592
Std.lv Std.all
0.141 0.350
0.639 0.639
0.559 0.559
0.212 0.212
0.243 0.243
0.627 0.627
0.207 0.207
0.367 0.367
0.271 0.271
0.358 0.358
0.385 0.385
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.212 0.079 2.706 0.007 0.059 0.366
.IM2 0.340 0.079 4.279 0.000 0.184 0.495
.IM3 0.474 0.163 2.912 0.004 0.155 0.794
.EEF1 0.232 0.050 4.602 0.000 0.133 0.331
.EEF2 0.221 0.042 5.296 0.000 0.139 0.303
.EEF3 0.250 0.056 4.489 0.000 0.141 0.359
.EEC1 0.827 0.093 8.890 0.000 0.645 1.010
.EEC2 0.475 0.095 4.974 0.000 0.288 0.662
.EEC3 0.195 0.060 3.271 0.001 0.078 0.312
.TR1 0.443 0.074 6.006 0.000 0.299 0.588
.TR2 0.276 0.065 4.228 0.000 0.148 0.405
.TR3 0.340 0.080 4.230 0.000 0.183 0.498
.ADT1 0.281 0.060 4.648 0.000 0.162 0.399
.ADT2 0.200 0.048 4.150 0.000 0.106 0.294
.ADT3 0.284 0.076 3.732 0.000 0.135 0.433
IM 0.882 0.142 6.232 0.000 0.605 1.160
EEF 1.168 0.169 6.913 0.000 0.837 1.499
EEC 0.954 0.141 6.785 0.000 0.679 1.230
TR 1.724 0.160 10.753 0.000 1.410 2.038
ADT 0.692 0.090 7.722 0.000 0.517 0.868
Std.lv Std.all
0.212 0.194
0.340 0.477
0.474 0.510
0.232 0.166
0.221 0.163
0.250 0.195
0.827 0.464
0.475 0.236
0.195 0.103
0.443 0.205
0.276 0.121
0.340 0.153
0.281 0.289
0.200 0.202
0.284 0.253
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.806
IM2 0.523
IM3 0.490
EEF1 0.834
EEF2 0.837
EEF3 0.805
EEC1 0.536
EEC2 0.764
EEC3 0.897
TR1 0.795
TR2 0.879
TR3 0.847
ADT1 0.711
ADT2 0.798
ADT3 0.747Cronbach’s Alpha: IM EEF EEC TR ADT
0.844 0.934 0.881 0.940 0.899 Omega: IM EEF EEC TR ADT
0.791 0.934 0.899 0.941 0.902 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.625 0.826 0.737 0.841 0.752 Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 10.941 0.134 0.134 0.213 0.213Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 10.941 0.134 0.134 0.213 0.213$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.000 0.000
IM3 0.000 0.000 0.000
EEF1 -0.026 0.008 -0.045 0.000
EEF2 -0.017 0.058 0.000 0.004 0.000
EEF3 0.005 0.062 0.056 -0.002 -0.003 0.000
EEC1 0.081 0.033 0.185 0.102 0.083 0.077 0.000
EEC2 0.066 -0.018 0.007 0.015 0.059 0.037 -0.070 0.000
EEC3 -0.001 -0.120 -0.042 -0.026 -0.053 -0.008 0.013 0.006 0.000
TR1 0.056 -0.043 0.017 0.089 -0.017 0.029 0.083 0.046 0.146 0.000
TR2 0.030 -0.100 -0.055 -0.029 -0.101 0.001 -0.128 -0.149 -0.015 0.002
TR3 0.009 -0.067 -0.018 0.074 -0.030 0.064 -0.022 -0.105 0.036 -0.008
ADT1 0.108 0.003 0.029 0.079 0.075 0.071 0.030 0.073 0.060 0.053
ADT2 -0.037 -0.087 -0.059 -0.037 -0.072 -0.052 -0.020 -0.012 -0.043 -0.007
ADT3 0.017 -0.035 -0.019 0.046 -0.013 -0.020 -0.009 0.046 -0.032 0.028
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.003 0.000
ADT1 0.035 0.066 0.000
ADT2 -0.054 -0.030 0.000 0.000
ADT3 -0.058 0.059 -0.012 0.008 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.009 0.000
IM3 0.010 0.000 0.000
EEF1 -0.643 0.173 -1.031 0.000
EEF2 -0.438 1.352 -0.005 0.116 0.000
EEF3 0.108 1.472 1.476 -0.060 -0.092 0.000
EEC1 1.233 0.555 1.840 1.514 1.348 1.212 0.000
EEC2 1.551 -0.425 0.105 0.274 1.200 0.728 -1.360 0.000
EEC3 -0.019 -2.601 -0.656 -0.591 -1.206 -0.178 0.275 0.134 0.000
TR1 1.013 -0.873 0.196 1.412 -0.344 0.476 0.874 0.582 2.250 0.000
TR2 0.632 -1.893 -0.808 -0.475 -2.059 0.015 -1.343 -1.986 -0.336 0.032
TR3 0.170 -1.240 -0.211 1.313 -0.552 1.061 -0.240 -1.356 0.702 -0.147
ADT1 2.733 0.085 0.666 1.614 1.600 1.606 0.483 1.265 1.550 0.780
ADT2 -1.148 -2.182 -1.290 -1.001 -1.861 -1.418 -0.349 -0.251 -1.381 -0.149
ADT3 0.449 -0.946 -0.348 1.047 -0.287 -0.479 -0.145 0.826 -0.798 0.499
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.053 0.000
ADT1 0.613 1.036 0.000
ADT2 -1.289 -0.610 0.006 0.000
ADT3 -1.073 1.071 -0.642 0.438 0.000lavaan 0.6-21 ended normally after 68 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 131
0 112
Model Test User Model:
Standard Scaled
Test Statistic 232.273 220.974
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.051
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 106.392 106.392
0 114.582 114.582
Model Test Baseline Model:
Test statistic 2566.531 1973.797
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.300
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.968 0.964
Tucker-Lewis Index (TLI) 0.958 0.953
Robust Comparative Fit Index (CFI) 0.971
Robust Tucker-Lewis Index (TLI) 0.962
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4197.443 -4197.443
Scaling correction factor 1.519
for the MLR correction
Loglikelihood unrestricted model (H1) -4081.307 -4081.307
Scaling correction factor 1.245
for the MLR correction
Akaike (AIC) 8618.886 8618.886
Bayesian (BIC) 9010.109 9010.109
Sample-size adjusted Bayesian (SABIC) 8655.085 8655.085
Root Mean Square Error of Approximation:
RMSEA 0.062 0.057
90 Percent confidence interval - lower 0.044 0.039
90 Percent confidence interval - upper 0.079 0.074
P-value H_0: RMSEA <= 0.050 0.124 0.242
P-value H_0: RMSEA >= 0.080 0.038 0.011
Robust RMSEA 0.059
90 Percent confidence interval - lower 0.039
90 Percent confidence interval - upper 0.076
P-value H_0: Robust RMSEA <= 0.050 0.215
P-value H_0: Robust RMSEA >= 0.080 0.022
Standardized Root Mean Square Residual:
SRMR 0.056 0.056
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 0.865 0.853
IM2 0.771 0.132 5.823 0.000 0.667 0.785
IM3 0.776 0.112 6.953 0.000 0.671 0.651
EEF =~
EEF1 1.000 0.897 0.891
EEF2 1.003 0.070 14.431 0.000 0.901 0.903
EEF3 0.911 0.069 13.186 0.000 0.818 0.861
EEC =~
EEC1 1.000 1.056 0.753
EEC2 1.102 0.101 10.934 0.000 1.164 0.870
EEC3 1.191 0.100 11.907 0.000 1.257 0.934
TR =~
TR1 1.000 1.353 0.894
TR2 1.042 0.066 15.836 0.000 1.409 0.923
TR3 1.036 0.065 15.937 0.000 1.401 0.909
ADT =~
ADT1 1.000 0.398 0.625
ADT2 1.341 0.303 4.420 0.000 0.534 0.887
ADT3 0.993 0.246 4.045 0.000 0.396 0.635
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.087 0.056 1.553 0.120 0.087 0.211
IM ~~
EEF 0.509 0.082 6.241 0.000 0.656 0.656
EEC 0.511 0.118 4.323 0.000 0.560 0.560
TR 0.197 0.132 1.498 0.134 0.169 0.169
ADT 0.035 0.042 0.831 0.406 0.101 0.101
EEF ~~
EEC 0.594 0.115 5.147 0.000 0.627 0.627
TR 0.243 0.125 1.949 0.051 0.200 0.200
ADT 0.091 0.046 1.968 0.049 0.253 0.253
EEC ~~
TR 0.348 0.132 2.634 0.008 0.244 0.244
ADT 0.105 0.050 2.123 0.034 0.251 0.251
TR ~~
ADT 0.198 0.083 2.395 0.017 0.367 0.367
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.466 0.089 61.716 0.000 5.466 5.392
.IM2 5.893 0.074 79.413 0.000 5.893 6.938
.IM3 5.710 0.090 63.450 0.000 5.710 5.544
.EEF1 5.618 0.088 63.839 0.000 5.618 5.578
.EEF2 5.756 0.087 66.084 0.000 5.756 5.774
.EEF3 5.809 0.083 69.988 0.000 5.809 6.115
.EEC1 4.595 0.123 37.511 0.000 4.595 3.277
.EEC2 4.718 0.117 40.353 0.000 4.718 3.526
.EEC3 4.771 0.118 40.587 0.000 4.771 3.546
.TR1 4.122 0.132 31.175 0.000 4.122 2.724
.TR2 4.076 0.133 30.565 0.000 4.076 2.670
.TR3 3.824 0.135 28.411 0.000 3.824 2.482
.ADT1 6.076 0.056 109.096 0.000 6.076 9.532
.ADT2 6.061 0.053 115.192 0.000 6.061 10.064
.ADT3 6.092 0.054 111.851 0.000 6.092 9.772
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.280 0.097 2.897 0.004 0.280 0.272
.IM2 0.277 0.090 3.072 0.002 0.277 0.384
.IM3 0.611 0.291 2.099 0.036 0.611 0.576
.EEF1 0.209 0.071 2.937 0.003 0.209 0.206
.EEF2 0.183 0.055 3.294 0.001 0.183 0.184
.EEF3 0.234 0.064 3.673 0.000 0.234 0.259
.EEC1 0.851 0.144 5.918 0.000 0.851 0.433
.EEC2 0.436 0.120 3.624 0.000 0.436 0.244
.EEC3 0.230 0.086 2.658 0.008 0.230 0.127
.TR1 0.461 0.113 4.063 0.000 0.461 0.201
.TR2 0.345 0.109 3.149 0.002 0.345 0.148
.TR3 0.411 0.139 2.958 0.003 0.411 0.173
.ADT1 0.248 0.071 3.506 0.000 0.248 0.610
.ADT2 0.077 0.061 1.269 0.204 0.077 0.213
.ADT3 0.232 0.043 5.358 0.000 0.232 0.597
IM 0.748 0.132 5.670 0.000 1.000 1.000
EEF 0.805 0.143 5.647 0.000 1.000 1.000
EEC 1.115 0.200 5.583 0.000 1.000 1.000
TR 1.829 0.229 8.003 0.000 1.000 1.000
ADT 0.159 0.055 2.898 0.004 1.000 1.000
Group 2 [0]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM =~
IM1 1.000 0.918 0.884
IM2 0.615 0.187 3.294 0.001 0.564 0.685
IM3 0.743 0.204 3.647 0.000 0.682 0.788
EEF =~
EEF1 1.000 1.161 0.914
EEF2 0.982 0.068 14.503 0.000 1.140 0.912
EEF3 0.959 0.067 14.307 0.000 1.113 0.909
EEC =~
EEC1 1.000 0.801 0.675
EEC2 1.449 0.226 6.411 0.000 1.161 0.845
EEC3 1.598 0.194 8.242 0.000 1.280 0.969
TR =~
TR1 1.000 1.163 0.871
TR2 1.178 0.080 14.761 0.000 1.370 0.961
TR3 1.052 0.069 15.240 0.000 1.224 0.920
ADT =~
ADT1 1.000 0.461 0.661
ADT2 0.785 0.490 1.601 0.109 0.362 0.522
ADT3 0.952 0.647 1.473 0.141 0.439 0.601
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.165 0.121 1.364 0.173 0.165 0.515
IM ~~
EEF 0.675 0.150 4.509 0.000 0.633 0.633
EEC 0.370 0.138 2.682 0.007 0.503 0.503
TR 0.181 0.172 1.052 0.293 0.169 0.169
ADT 0.080 0.121 0.662 0.508 0.190 0.190
EEF ~~
EEC 0.513 0.150 3.410 0.001 0.551 0.551
TR 0.115 0.153 0.754 0.451 0.085 0.085
ADT 0.120 0.117 1.027 0.304 0.225 0.225
EEC ~~
TR 0.170 0.115 1.474 0.140 0.183 0.183
ADT 0.090 0.084 1.070 0.284 0.243 0.243
TR ~~
ADT 0.139 0.115 1.204 0.228 0.259 0.259
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.045 0.098 51.411 0.000 5.045 4.858
.IM2 5.688 0.078 73.039 0.000 5.688 6.902
.IM3 5.473 0.082 66.916 0.000 5.473 6.323
.EEF1 4.955 0.120 41.278 0.000 4.955 3.900
.EEF2 5.134 0.118 43.467 0.000 5.134 4.107
.EEF3 5.170 0.116 44.701 0.000 5.170 4.224
.EEC1 4.054 0.112 36.155 0.000 4.054 3.416
.EEC2 3.884 0.130 29.912 0.000 3.884 2.826
.EEC3 4.071 0.125 32.619 0.000 4.071 3.082
.TR1 3.455 0.126 27.380 0.000 3.455 2.587
.TR2 3.446 0.135 25.582 0.000 3.446 2.417
.TR3 3.098 0.126 24.665 0.000 3.098 2.331
.ADT1 4.616 0.066 70.037 0.000 4.616 6.618
.ADT2 4.545 0.065 69.410 0.000 4.545 6.559
.ADT3 4.455 0.069 64.541 0.000 4.455 6.099
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.236 0.134 1.766 0.077 0.236 0.219
.IM2 0.361 0.124 2.906 0.004 0.361 0.531
.IM3 0.284 0.130 2.184 0.029 0.284 0.379
.EEF1 0.267 0.067 3.978 0.000 0.267 0.165
.EEF2 0.263 0.061 4.291 0.000 0.263 0.168
.EEF3 0.259 0.101 2.577 0.010 0.259 0.173
.EEC1 0.766 0.099 7.722 0.000 0.766 0.544
.EEC2 0.541 0.154 3.503 0.000 0.541 0.286
.EEC3 0.106 0.090 1.178 0.239 0.106 0.061
.TR1 0.431 0.087 4.938 0.000 0.431 0.242
.TR2 0.155 0.058 2.653 0.008 0.155 0.076
.TR3 0.270 0.072 3.729 0.000 0.270 0.153
.ADT1 0.274 0.144 1.907 0.056 0.274 0.563
.ADT2 0.349 0.099 3.541 0.000 0.349 0.727
.ADT3 0.341 0.191 1.785 0.074 0.341 0.639
IM 0.843 0.248 3.393 0.001 1.000 1.000
EEF 1.347 0.273 4.933 0.000 1.000 1.000
EEC 0.642 0.186 3.458 0.001 1.000 1.000
TR 1.353 0.206 6.570 0.000 1.000 1.000
ADT 0.213 0.142 1.498 0.134 1.000 1.000lavaan 0.6-21 ended normally after 65 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 107
0 136
Model Test User Model:
Standard Scaled
Test Statistic 249.171 243.603
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.023
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 137.348 137.348
0 106.255 106.255
Model Test Baseline Model:
Test statistic 2542.192 1945.524
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.307
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.961 0.951
Tucker-Lewis Index (TLI) 0.948 0.934
Robust Comparative Fit Index (CFI) 0.961
Robust Tucker-Lewis Index (TLI) 0.949
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4160.919 -4160.919
Scaling correction factor 1.587
for the MLR correction
Loglikelihood unrestricted model (H1) -4036.334 -4036.334
Scaling correction factor 1.257
for the MLR correction
Akaike (AIC) 8545.839 8545.839
Bayesian (BIC) 8937.062 8937.062
Sample-size adjusted Bayesian (SABIC) 8582.038 8582.038
Root Mean Square Error of Approximation:
RMSEA 0.069 0.067
90 Percent confidence interval - lower 0.052 0.050
90 Percent confidence interval - upper 0.085 0.083
P-value H_0: RMSEA <= 0.050 0.033 0.051
P-value H_0: RMSEA >= 0.080 0.130 0.088
Robust RMSEA 0.068
90 Percent confidence interval - lower 0.050
90 Percent confidence interval - upper 0.084
P-value H_0: Robust RMSEA <= 0.050 0.048
P-value H_0: Robust RMSEA >= 0.080 0.107
Standardized Root Mean Square Residual:
SRMR 0.056 0.056
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 0.804 0.866
IM2 0.926 0.132 7.004 0.000 0.745 0.894
IM3 0.892 0.151 5.912 0.000 0.717 0.751
EEF =~
EEF1 1.000 0.974 0.925
EEF2 1.042 0.059 17.616 0.000 1.015 0.901
EEF3 0.888 0.084 10.517 0.000 0.865 0.853
EEC =~
EEC1 1.000 0.855 0.742
EEC2 1.245 0.165 7.545 0.000 1.065 0.823
EEC3 1.297 0.138 9.399 0.000 1.110 0.899
TR =~
TR1 1.000 0.326 0.426
TR2 1.269 0.370 3.431 0.001 0.414 0.718
TR3 1.556 0.487 3.198 0.001 0.507 0.736
ADT =~
ADT1 1.000 0.923 0.923
ADT2 0.921 0.088 10.479 0.000 0.850 0.897
ADT3 0.938 0.065 14.340 0.000 0.865 0.837
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.037 0.074 0.492 0.623 0.037 0.156
IM ~~
EEF 0.528 0.099 5.336 0.000 0.674 0.674
EEC 0.279 0.104 2.689 0.007 0.406 0.406
TR 0.002 0.047 0.051 0.959 0.009 0.009
ADT 0.162 0.102 1.592 0.111 0.219 0.219
EEF ~~
EEC 0.486 0.110 4.412 0.000 0.584 0.584
TR 0.072 0.047 1.536 0.125 0.226 0.226
ADT 0.344 0.124 2.768 0.006 0.383 0.383
EEC ~~
TR 0.062 0.049 1.259 0.208 0.223 0.223
ADT 0.285 0.095 3.006 0.003 0.362 0.362
TR ~~
ADT 0.125 0.059 2.115 0.034 0.416 0.416
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.430 0.090 60.500 0.000 5.430 5.849
.IM2 5.869 0.080 72.921 0.000 5.869 7.050
.IM3 5.720 0.092 61.951 0.000 5.720 5.989
.EEF1 5.514 0.102 54.147 0.000 5.514 5.235
.EEF2 5.598 0.109 51.417 0.000 5.598 4.971
.EEF3 5.710 0.098 58.252 0.000 5.710 5.631
.EEC1 4.561 0.112 40.901 0.000 4.561 3.954
.EEC2 4.626 0.125 36.993 0.000 4.626 3.576
.EEC3 4.804 0.119 40.275 0.000 4.804 3.893
.TR1 5.112 0.074 69.105 0.000 5.112 6.681
.TR2 5.206 0.056 93.516 0.000 5.206 9.040
.TR3 4.804 0.067 72.060 0.000 4.804 6.966
.ADT1 5.692 0.097 58.923 0.000 5.692 5.696
.ADT2 5.664 0.092 61.886 0.000 5.664 5.983
.ADT3 5.654 0.100 56.612 0.000 5.654 5.473
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.215 0.082 2.619 0.009 0.215 0.250
.IM2 0.139 0.070 1.989 0.047 0.139 0.200
.IM3 0.397 0.192 2.065 0.039 0.397 0.436
.EEF1 0.161 0.062 2.616 0.009 0.161 0.145
.EEF2 0.239 0.066 3.646 0.000 0.239 0.188
.EEF3 0.280 0.080 3.492 0.000 0.280 0.272
.EEC1 0.599 0.108 5.560 0.000 0.599 0.450
.EEC2 0.540 0.147 3.684 0.000 0.540 0.323
.EEC3 0.291 0.111 2.624 0.009 0.291 0.191
.TR1 0.479 0.115 4.160 0.000 0.479 0.819
.TR2 0.161 0.040 4.053 0.000 0.161 0.484
.TR3 0.218 0.088 2.476 0.013 0.218 0.459
.ADT1 0.147 0.053 2.787 0.005 0.147 0.148
.ADT2 0.174 0.056 3.101 0.002 0.174 0.195
.ADT3 0.319 0.150 2.128 0.033 0.319 0.299
IM 0.647 0.120 5.378 0.000 1.000 1.000
EEF 0.949 0.193 4.913 0.000 1.000 1.000
EEC 0.732 0.150 4.890 0.000 1.000 1.000
TR 0.106 0.063 1.687 0.092 1.000 1.000
ADT 0.851 0.141 6.047 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 0.992 0.890
IM2 0.542 0.125 4.340 0.000 0.538 0.634
IM3 0.667 0.123 5.421 0.000 0.662 0.687
EEF =~
EEF1 1.000 1.126 0.898
EEF2 0.978 0.060 16.173 0.000 1.101 0.932
EEF3 0.977 0.049 20.050 0.000 1.100 0.923
EEC =~
EEC1 1.000 1.035 0.719
EEC2 1.268 0.134 9.433 0.000 1.312 0.895
EEC3 1.334 0.112 11.943 0.000 1.380 0.970
TR =~
TR1 1.000 0.806 0.788
TR2 0.990 0.101 9.850 0.000 0.798 0.798
TR3 1.077 0.109 9.911 0.000 0.869 0.801
ADT =~
ADT1 1.000 0.685 0.749
ADT2 1.233 0.161 7.653 0.000 0.845 0.875
ADT3 1.280 0.165 7.735 0.000 0.877 0.868
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.172 0.089 1.937 0.053 0.172 0.374
IM ~~
EEF 0.672 0.139 4.850 0.000 0.602 0.602
EEC 0.647 0.144 4.500 0.000 0.630 0.630
TR 0.185 0.105 1.761 0.078 0.231 0.231
ADT 0.134 0.082 1.636 0.102 0.197 0.197
EEF ~~
EEC 0.736 0.159 4.618 0.000 0.631 0.631
TR 0.134 0.094 1.425 0.154 0.148 0.148
ADT 0.242 0.094 2.572 0.010 0.313 0.313
EEC ~~
TR 0.098 0.091 1.076 0.282 0.118 0.118
ADT 0.199 0.087 2.288 0.022 0.281 0.281
TR ~~
ADT 0.099 0.063 1.574 0.116 0.179 0.179
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.147 0.096 53.837 0.000 5.147 4.616
.IM2 5.743 0.073 78.896 0.000 5.743 6.765
.IM3 5.507 0.083 66.728 0.000 5.507 5.722
.EEF1 5.154 0.108 47.947 0.000 5.154 4.111
.EEF2 5.368 0.101 53.013 0.000 5.368 4.546
.EEF3 5.360 0.102 52.428 0.000 5.360 4.496
.EEC1 4.176 0.123 33.838 0.000 4.176 2.902
.EEC2 4.103 0.126 32.623 0.000 4.103 2.797
.EEC3 4.169 0.122 34.185 0.000 4.169 2.931
.TR1 2.794 0.088 31.863 0.000 2.794 2.732
.TR2 2.669 0.086 31.114 0.000 2.669 2.668
.TR3 2.456 0.093 26.427 0.000 2.456 2.266
.ADT1 5.176 0.078 66.004 0.000 5.176 5.660
.ADT2 5.125 0.083 61.879 0.000 5.125 5.306
.ADT3 5.088 0.087 58.707 0.000 5.088 5.034
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.258 0.109 2.379 0.017 0.258 0.208
.IM2 0.431 0.108 3.992 0.000 0.431 0.599
.IM3 0.489 0.233 2.096 0.036 0.489 0.527
.EEF1 0.304 0.076 4.005 0.000 0.304 0.193
.EEF2 0.182 0.043 4.208 0.000 0.182 0.130
.EEF3 0.212 0.071 2.962 0.003 0.212 0.149
.EEC1 1.001 0.144 6.972 0.000 1.001 0.483
.EEC2 0.430 0.130 3.316 0.001 0.430 0.200
.EEC3 0.118 0.053 2.221 0.026 0.118 0.058
.TR1 0.396 0.088 4.522 0.000 0.396 0.379
.TR2 0.363 0.100 3.627 0.000 0.363 0.363
.TR3 0.420 0.132 3.179 0.001 0.420 0.358
.ADT1 0.367 0.088 4.182 0.000 0.367 0.439
.ADT2 0.219 0.077 2.856 0.004 0.219 0.235
.ADT3 0.253 0.068 3.740 0.000 0.253 0.247
IM 0.985 0.202 4.871 0.000 1.000 1.000
EEF 1.268 0.242 5.236 0.000 1.000 1.000
EEC 1.071 0.223 4.811 0.000 1.000 1.000
TR 0.650 0.107 6.052 0.000 1.000 1.000
ADT 0.470 0.111 4.233 0.000 1.000 1.000
Chi-Squared Difference Test
Df AIC BIC Chisq Chisq diff RMSEA Df diff Pr(>Chisq)
fit_config 158 8545.8 8937.1 249.17
fit_metric 168 8545.9 8902.2 269.25 20.0748 0.091061 10 0.02855 *
fit_scalar 178 8534.0 8855.4 277.33 8.0854 0.000000 10 0.62049
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 config metric scalar
chisq 249.17083609 269.24564087 277.33107758
df 158.00000000 168.00000000 178.00000000
cfi 0.96090766 0.95658777 0.95740870
rmsea 0.06891461 0.07042801 0.06777108
srmr 0.05592058 0.06097899 0.06275468<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 12.479 0.235 0.235 0.920 0.920
153 IM =~ ADT2 1 1 1 11.698 -0.212 -0.186 -0.192 -0.192
152 IM =~ ADT1 1 1 1 10.794 0.206 0.180 0.188 0.188No moderation - without PEB control variablelavaan 0.6-21 ended normally after 63 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 50
Number of observations 243
Model Test User Model:
Standard Scaled
Test Statistic 222.978 205.793
Degrees of freedom 145 145
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.084
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2959.261 2338.065
Degrees of freedom 180 180
P-value 0.000 0.000
Scaling correction factor 1.266
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) -4406.442 -4406.442
Scaling correction factor 1.737
for the MLR correction
Loglikelihood unrestricted model (H1) -4294.953 -4294.953
Scaling correction factor 1.251
for the MLR correction
Akaike (AIC) 8912.884 8912.884
Bayesian (BIC) 9087.537 9087.537
Sample-size adjusted Bayesian (SABIC) 8929.044 8929.044
Root Mean Square Error of Approximation:
RMSEA 0.047 0.042
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.059 0.054
P-value H_0: RMSEA <= 0.050 0.645 0.871
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.043
90 Percent confidence interval - lower 0.029
90 Percent confidence interval - upper 0.056
P-value H_0: Robust RMSEA <= 0.050 0.793
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.115 0.115
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 1.311 0.891
TR2 1.084 0.045 24.086 0.000 1.421 0.939
TR3 1.047 0.045 23.077 0.000 1.373 0.921
ADT =~
ADT1 1.000 0.826 0.837
ADT2 1.083 0.080 13.612 0.000 0.894 0.900
ADT3 1.107 0.075 14.706 0.000 0.914 0.863
IM =~
IM1 1.000 0.938 0.897
IM2 0.651 0.106 6.123 0.000 0.611 0.723
IM3 0.722 0.104 6.963 0.000 0.677 0.702
EEF =~
EEF1 1.000 1.080 0.913
EEF2 0.985 0.047 20.835 0.000 1.064 0.915
EEF3 0.939 0.043 21.683 0.000 1.014 0.897
EEC =~
EEC1 1.000 0.979 0.734
EEC2 1.269 0.101 12.617 0.000 1.243 0.877
EEC3 1.328 0.085 15.580 0.000 1.300 0.943
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) -0.077 0.231 -0.331 0.740 -0.082 -0.032
rwrd0_2 (b_02) -0.058 0.234 -0.246 0.805 -0.061 -0.024
rwrd1_2 (b_12) 0.187 0.204 0.917 0.359 0.200 0.079
rwrd0_3 (b_03) 0.074 0.244 0.303 0.762 0.079 0.027
rwrd1_3 (b_13) -0.189 0.220 -0.860 0.390 -0.202 -0.070
EEF ~
rwrd1_1 (c_11) -0.005 0.204 -0.024 0.981 -0.005 -0.002
rwrd0_2 (c_02) -0.023 0.193 -0.122 0.903 -0.022 -0.008
rwrd1_2 (c_12) -0.022 0.175 -0.127 0.899 -0.021 -0.008
rwrd0_3 (c_03) -0.233 0.178 -1.307 0.191 -0.216 -0.073
rwrd1_3 (c_13) 0.012 0.183 0.065 0.948 0.011 0.004
IM (c_IM) 0.740 0.096 7.713 0.000 0.642 0.642
EEC ~
rwrd1_1 (d_11) 0.211 0.197 1.071 0.284 0.216 0.084
rwrd0_2 (d_02) 0.230 0.199 1.158 0.247 0.235 0.091
rwrd1_2 (d_12) 0.235 0.189 1.238 0.216 0.240 0.095
rwrd0_3 (d_03) 0.100 0.190 0.526 0.599 0.102 0.034
rwrd1_3 (d_13) 0.150 0.218 0.686 0.493 0.153 0.053
IM (d_IM) 0.585 0.077 7.627 0.000 0.561 0.561
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.140 0.063 2.218 0.027 0.140 0.349
TR ~~
ADT 0.415 0.086 4.807 0.000 0.383 0.383
.EEF ~~
.EEC 0.285 0.075 3.805 0.000 0.428 0.428
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.448 0.073 6.107 0.000 0.448 0.207
.TR2 0.273 0.065 4.207 0.000 0.273 0.119
.TR3 0.339 0.080 4.256 0.000 0.339 0.153
.ADT1 0.291 0.060 4.856 0.000 0.291 0.299
.ADT2 0.188 0.047 4.045 0.000 0.188 0.191
.ADT3 0.286 0.078 3.646 0.000 0.286 0.255
.IM1 0.214 0.077 2.767 0.006 0.214 0.196
.IM2 0.340 0.078 4.328 0.000 0.340 0.477
.IM3 0.472 0.165 2.859 0.004 0.472 0.507
.EEF1 0.234 0.051 4.621 0.000 0.234 0.167
.EEF2 0.219 0.041 5.292 0.000 0.219 0.162
.EEF3 0.250 0.056 4.468 0.000 0.250 0.196
.EEC1 0.823 0.093 8.825 0.000 0.823 0.462
.EEC2 0.463 0.095 4.888 0.000 0.463 0.231
.EEC3 0.211 0.060 3.523 0.000 0.211 0.111
TR 1.719 0.160 10.747 0.000 1.000 1.000
ADT 0.682 0.089 7.700 0.000 1.000 1.000
.IM 0.866 0.142 6.090 0.000 0.984 0.984
.EEF 0.684 0.123 5.542 0.000 0.586 0.586
.EEC 0.649 0.106 6.122 0.000 0.677 0.677
R-Square:
Estimate
TR1 0.793
TR2 0.881
TR3 0.847
ADT1 0.701
ADT2 0.809
ADT3 0.745
IM1 0.804
IM2 0.523
IM3 0.493
EEF1 0.833
EEF2 0.838
EEF3 0.804
EEC1 0.538
EEC2 0.769
EEC3 0.889
IM 0.016
EEF 0.414
EEC 0.323With 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 243
Model Test User Model:
Standard Scaled
Test Statistic 188.631 174.750
Degrees of freedom 151 151
P-value (Chi-square) 0.020 0.090
Scaling correction factor 1.079
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3015.286 2419.140
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.246
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) 0.991
Robust Tucker-Lewis Index (TLI) 0.988
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4361.256 -4361.256
Scaling correction factor 1.630
for the MLR correction
Loglikelihood unrestricted model (H1) -4266.941 -4266.941
Scaling correction factor 1.234
for the MLR correction
Akaike (AIC) 8840.512 8840.512
Bayesian (BIC) 9046.603 9046.603
Sample-size adjusted Bayesian (SABIC) 8859.581 8859.581
Root Mean Square Error of Approximation:
RMSEA 0.032 0.025
90 Percent confidence interval - lower 0.013 0.000
90 Percent confidence interval - upper 0.046 0.040
P-value H_0: RMSEA <= 0.050 0.987 0.999
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.026
90 Percent confidence interval - lower 0.000
90 Percent confidence interval - upper 0.042
P-value H_0: Robust RMSEA <= 0.050 0.995
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 1.313 0.892
TR2 1.082 0.045 23.871 0.000 1.420 0.938
TR3 1.046 0.046 22.928 0.000 1.373 0.920
ADT =~
ADT1 1.000 0.833 0.844
ADT2 1.064 0.079 13.403 0.000 0.886 0.892
ADT3 1.099 0.076 14.471 0.000 0.915 0.864
IM =~
IM1 1.000 0.910 0.871
IM2 0.687 0.099 6.922 0.000 0.625 0.742
IM3 0.764 0.098 7.799 0.000 0.695 0.722
EEF =~
EEF1 1.000 1.081 0.914
EEF2 0.983 0.047 21.127 0.000 1.062 0.914
EEF3 0.937 0.043 21.800 0.000 1.013 0.896
EEC =~
EEC1 1.000 0.977 0.732
EEC2 1.268 0.100 12.696 0.000 1.238 0.875
EEC3 1.333 0.086 15.522 0.000 1.303 0.946
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.115 0.191 0.605 0.545 0.127 0.049
rwrd0_2 (b_02) 0.035 0.212 0.163 0.870 0.038 0.015
rwrd1_2 (b_12) 0.307 0.176 1.747 0.081 0.337 0.133
rwrd0_3 (b_03) 0.226 0.217 1.045 0.296 0.249 0.084
rwrd1_3 (b_13) -0.053 0.183 -0.290 0.772 -0.058 -0.020
TR (b_TR) 0.071 0.052 1.368 0.171 0.103 0.103
ADT (b_AD) 0.216 0.083 2.596 0.009 0.198 0.198
PEB_yes (b_PE) 0.916 0.126 7.288 0.000 1.007 0.413
EEF ~
rwrd1_1 (c_11) 0.031 0.202 0.155 0.877 0.029 0.011
rwrd0_2 (c_02) -0.057 0.181 -0.315 0.753 -0.053 -0.020
rwrd1_2 (c_12) 0.010 0.169 0.062 0.951 0.010 0.004
rwrd0_3 (c_03) -0.207 0.174 -1.190 0.234 -0.192 -0.065
rwrd1_3 (c_13) 0.015 0.184 0.082 0.934 0.014 0.005
IM (c_IM) 0.653 0.101 6.465 0.000 0.549 0.549
TR (c_TR) -0.006 0.048 -0.119 0.905 -0.007 -0.007
ADT (c_AD) 0.313 0.085 3.664 0.000 0.241 0.241
PEB_yes (c_PE) 0.268 0.178 1.501 0.133 0.248 0.102
EEC ~
rwrd1_1 (d_11) 0.227 0.195 1.162 0.245 0.232 0.090
rwrd0_2 (d_02) 0.207 0.200 1.034 0.301 0.212 0.082
rwrd1_2 (d_12) 0.270 0.179 1.507 0.132 0.276 0.109
rwrd0_3 (d_03) 0.098 0.185 0.532 0.595 0.101 0.034
rwrd1_3 (d_13) 0.155 0.202 0.766 0.444 0.158 0.055
IM (d_IM) 0.512 0.093 5.502 0.000 0.477 0.477
TR (d_TR) 0.071 0.048 1.491 0.136 0.095 0.095
ADT (d_AD) 0.246 0.082 2.996 0.003 0.210 0.210
PEB_yes (d_PE) 0.042 0.163 0.260 0.795 0.043 0.018
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.116 0.056 2.059 0.040 0.116 0.308
TR ~~
ADT 0.422 0.087 4.838 0.000 0.385 0.385
.EEF ~~
.EEC 0.225 0.066 3.429 0.001 0.376 0.376
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.444 0.074 6.013 0.000 0.444 0.205
.TR2 0.275 0.066 4.204 0.000 0.275 0.120
.TR3 0.341 0.080 4.257 0.000 0.341 0.153
.ADT1 0.279 0.060 4.659 0.000 0.279 0.287
.ADT2 0.202 0.048 4.190 0.000 0.202 0.205
.ADT3 0.283 0.075 3.753 0.000 0.283 0.253
.IM1 0.262 0.069 3.814 0.000 0.262 0.241
.IM2 0.319 0.073 4.376 0.000 0.319 0.450
.IM3 0.445 0.162 2.745 0.006 0.445 0.479
.EEF1 0.230 0.051 4.538 0.000 0.230 0.164
.EEF2 0.222 0.041 5.401 0.000 0.222 0.164
.EEF3 0.251 0.056 4.501 0.000 0.251 0.197
.EEC1 0.825 0.093 8.894 0.000 0.825 0.464
.EEC2 0.471 0.095 4.950 0.000 0.471 0.235
.EEC3 0.201 0.060 3.341 0.001 0.201 0.106
TR 1.724 0.160 10.751 0.000 1.000 1.000
ADT 0.694 0.089 7.761 0.000 1.000 1.000
.IM 0.619 0.105 5.886 0.000 0.748 0.748
.EEF 0.606 0.106 5.743 0.000 0.519 0.519
.EEC 0.592 0.097 6.109 0.000 0.620 0.620
R-Square:
Estimate
TR1 0.795
TR2 0.880
TR3 0.847
ADT1 0.713
ADT2 0.795
ADT3 0.747
IM1 0.759
IM2 0.550
IM3 0.521
EEF1 0.836
EEF2 0.836
EEF3 0.803
EEC1 0.536
EEC2 0.765
EEC3 0.894
IM 0.252
EEF 0.481
EEC 0.380
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.115 0.191 0.605 0.545 0.127 0.049
reward2_IM 0.272 0.204 1.332 0.183 0.299 0.119
reward3_IM -0.280 0.221 -1.265 0.206 -0.307 -0.104
reward_vrgd_IM 0.036 0.120 0.301 0.764 0.040 0.021
reward_EEF_ec1 0.031 0.202 0.155 0.877 0.029 0.011
reward_EEF_ec2 0.068 0.190 0.357 0.721 0.063 0.024
reward_EEF_ec3 0.222 0.196 1.135 0.257 0.206 0.070
reward_man_EEF 0.107 0.112 0.957 0.339 0.099 0.035
ind_rwrd_EEF_1 0.075 0.128 0.590 0.555 0.070 0.027
ind_rwrd_EEF_2 0.178 0.131 1.359 0.174 0.164 0.065
ind_rwrd_EEF_3 -0.183 0.147 -1.244 0.213 -0.169 -0.057
ind_rw__IM_EEF 0.023 0.078 0.300 0.764 0.022 0.012
tt_rwrd_mn_EEF 0.131 0.124 1.054 0.292 0.121 0.047
reward_EEC_ec1 0.227 0.195 1.162 0.245 0.232 0.090
reward_EEC_ec2 0.063 0.182 0.346 0.729 0.064 0.028
reward_EEC_ec3 0.056 0.197 0.285 0.775 0.058 0.021
reward_man_EEC 0.115 0.110 1.047 0.295 0.118 0.046
ind_rwrd_EEC_1 0.059 0.099 0.598 0.550 0.060 0.023
ind_rwrd_EEC_2 0.139 0.108 1.295 0.195 0.143 0.056
ind_rwrd_EEC_3 -0.143 0.117 -1.226 0.220 -0.147 -0.050
ind_rw__IM_EEC 0.018 0.061 0.300 0.764 0.019 0.010
tt_rwrd_mn_EEC 0.134 0.116 1.152 0.249 0.137 0.056
eco2_vs_c1_EEF -0.039 0.133 -0.293 0.770 -0.036 -0.014
eco3_vs_c1_EEF -0.112 0.137 -0.814 0.416 -0.103 -0.036
eco1_vs_c2_EEF 0.039 0.133 0.293 0.770 0.036 0.014
eco_main_EEF -0.075 0.116 -0.648 0.517 -0.070 -0.025
eco2_vs_ec1_IM 0.113 0.134 0.842 0.400 0.124 0.049
eco3_vs_ec1_IM 0.029 0.142 0.203 0.839 0.032 0.007
eco1_vs_ec2_IM -0.113 0.134 -0.842 0.400 -0.124 -0.049
in_1__2_IM_EEF -0.074 0.090 -0.816 0.414 -0.068 -0.027
in_2__1_IM_EEF 0.074 0.090 0.816 0.414 0.068 0.027
in_3__1_IM_EEF 0.019 0.093 0.203 0.839 0.017 0.004
ind_c_m_IM_EEF 0.046 0.077 0.600 0.548 0.043 0.016
tt_c1_vs_2_EEF -0.035 0.148 -0.234 0.815 -0.032 -0.013
tt_c2_vs_1_EEF 0.035 0.148 0.234 0.815 0.032 0.013
tt_c3_vs_1_EEF -0.093 0.153 -0.606 0.544 -0.086 -0.032
tot_eco_mn_EEF -0.029 0.129 -0.224 0.823 -0.027 -0.009
eco2_vs_c1_EEC 0.125 0.136 0.917 0.359 0.128 0.050
eco3_vs_c1_EEC 0.013 0.136 0.095 0.924 0.013 -0.001
eco_main_EEC 0.069 0.119 0.578 0.563 0.071 0.025
in_2__1_IM_EEC 0.058 0.070 0.825 0.410 0.059 0.023
in_3__1_IM_EEC 0.015 0.073 0.203 0.839 0.015 0.003
ind_c_m_IM_EEC 0.036 0.060 0.604 0.546 0.037 0.013
tt_c2_vs_1_EEC 0.183 0.149 1.229 0.219 0.187 0.074
tt_c3_vs_1_EEC 0.028 0.134 0.208 0.835 0.028 0.003
tot_eco_mn_EEC 0.105 0.123 0.857 0.391 0.108 0.038
eco_main_IM 0.071 0.116 0.610 0.542 0.078 0.028
eco3_vs_c2_EEF -0.073 0.138 -0.525 0.600 -0.067 -0.022
in_3__2_IM_EEF -0.055 0.099 -0.554 0.580 -0.051 -0.023
tt_c3_vs_2_EEF -0.127 0.154 -0.827 0.408 -0.118 -0.045
eco3_vs_c2_EEC -0.112 0.132 -0.846 0.398 -0.115 -0.051
in_3__2_IM_EEC -0.043 0.077 -0.556 0.578 -0.044 -0.020
tt_c3_vs_2_EEC -0.155 0.140 -1.104 0.270 -0.159 -0.071
reward_IM_eco1 0.115 0.191 0.605 0.545 0.127 0.049
reward_IM_eco2 0.272 0.204 1.332 0.183 0.299 0.119
reward_IM_eco3 -0.280 0.221 -1.265 0.206 -0.307 -0.104
reward_main_IM 0.036 0.120 0.301 0.764 0.040 0.021
r_3_EEF___1_EE -0.016 0.219 -0.074 0.941 -0.015 -0.006
r_2_EEF___1_EE -0.021 0.200 -0.104 0.917 -0.019 -0.007
r_2_EEC___1_EE 0.043 0.180 0.239 0.811 0.044 0.019
r_3_EEC___2_EE -0.115 0.190 -0.607 0.544 -0.118 -0.054
r_3_EEC___1_EE -0.072 0.204 -0.354 0.723 -0.074 -0.035
rw_2_IM___1_IM 0.191 0.173 1.103 0.270 0.210 0.084
rw_3_IM___1_IM -0.169 0.187 -0.899 0.368 -0.185 -0.070
i__2_EEC___1_E 0.098 0.091 1.076 0.282 0.100 0.040
i__3_EEC___1_E -0.086 0.098 -0.883 0.377 -0.088 -0.033
i__3_EEC___2_E -0.184 0.098 -1.872 0.061 -0.189 -0.073
t__2_EEC___1_E 0.141 0.199 0.708 0.479 0.144 0.059
t__3_EEC___1_E -0.159 0.211 -0.753 0.452 -0.162 -0.068
t__3_EEC___2_E -0.300 0.198 -1.516 0.129 -0.307 -0.127
rwrd_c3_dr_EEF 0.222 0.196 1.135 0.257 0.206 0.070
rwrd_3__IM_EEF -0.183 0.147 -1.244 0.213 -0.169 -0.057
rwrd_c3_tt_EEF 0.040 0.220 0.180 0.857 0.037 0.012
rwrd_c3_dr_EEC 0.056 0.197 0.285 0.775 0.058 0.021
rwrd_3__IM_EEC -0.143 0.117 -1.226 0.220 -0.147 -0.050
rwrd_c3_tt_EEC -0.087 0.188 -0.461 0.645 -0.089 -0.029Mediation 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 0.107 0.111 0.961 0.337 -0.121
97 ind_reward_main_IM_EEF 0.023 0.084 0.279 0.780 -0.149
98 tot_reward_main_EEF 0.131 0.127 1.031 0.303 -0.121
102 reward_main_EEC 0.115 0.110 1.051 0.293 -0.077
106 ind_reward_main_IM_EEC 0.018 0.066 0.280 0.779 -0.120
107 tot_reward_main_EEC 0.134 0.117 1.140 0.254 -0.076
109 eco3_vs_eco1_EEF -0.112 0.141 -0.791 0.429 -0.368
110 eco1_vs_eco2_EEF 0.039 0.136 0.287 0.774 -0.244
111 eco_main_EEF -0.075 0.120 -0.626 0.531 -0.293
112 eco2_vs_eco1_IM 0.113 0.143 0.787 0.431 -0.202
113 eco3_vs_eco1_IM 0.029 0.143 0.202 0.840 -0.246
114 eco1_vs_eco2_IM -0.113 0.143 -0.787 0.431 -0.356
115 ind_eco1_vs_eco2_IM_EEF -0.074 0.098 -0.749 0.454 -0.253
117 ind_eco3_vs_eco1_IM_EEF 0.019 0.095 0.198 0.843 -0.162
118 ind_eco_main_IM_EEF 0.046 0.082 0.566 0.572 -0.116
119 tot_eco1_vs_eco2_EEF -0.035 0.151 -0.229 0.819 -0.325
121 tot_eco3_vs_eco1_EEF -0.093 0.150 -0.619 0.536 -0.385
122 tot_eco_main_EEF -0.029 0.130 -0.223 0.823 -0.279
123 eco2_vs_eco1_EEC 0.125 0.143 0.875 0.381 -0.146
124 eco3_vs_eco1_EEC 0.013 0.145 0.090 0.929 -0.271
125 eco_main_EEC 0.069 0.127 0.542 0.588 -0.169
126 ind_eco2_vs_eco1_IM_EEC 0.058 0.077 0.747 0.455 -0.110
127 ind_eco3_vs_eco1_IM_EEC 0.015 0.074 0.199 0.842 -0.116
128 ind_eco_main_IM_EEC 0.036 0.064 0.568 0.570 -0.095
129 tot_eco2_vs_eco1_EEC 0.183 0.156 1.175 0.240 -0.134
130 tot_eco3_vs_eco1_EEC 0.028 0.141 0.197 0.844 -0.243
131 tot_eco_main_EEC 0.105 0.130 0.807 0.420 -0.150
132 eco_main_IM 0.071 0.121 0.585 0.558 -0.189
136 eco3_vs_eco2_EEC -0.112 0.134 -0.839 0.401 -0.367
137 ind_eco3_vs_eco2_IM_EEC -0.043 0.082 -0.527 0.598 -0.213
138 tot_eco3_vs_eco2_EEC -0.155 0.142 -1.094 0.274 -0.427
142 reward_main_IM 0.036 0.127 0.283 0.777 -0.225
143 reward_eco3_EEF_vs_reward_eco1_EEF -0.016 0.219 -0.074 0.941 -0.435
144 reward_eco2_EEF_vs_reward_eco1_EEF -0.021 0.198 -0.105 0.916 -0.379
145 reward_eco2_EEC_vs_reward_eco1_EEC 0.043 0.191 0.226 0.821 -0.338
146 reward_eco3_EEC_vs_reward_eco2_EEC -0.115 0.182 -0.633 0.526 -0.491
148 reward_eco2_IM_vs_reward_eco1_IM 0.191 0.178 1.076 0.282 -0.155
149 reward_eco3_IM_vs_reward_eco1_IM -0.169 0.193 -0.871 0.384 -0.499
150 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.098 0.096 1.017 0.309 -0.076
151 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.086 0.103 -0.841 0.400 -0.275
152 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.184 0.100 -1.842 0.065 -0.360
153 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.141 0.209 0.673 0.501 -0.289
154 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.159 0.214 -0.740 0.460 -0.548
155 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.300 0.198 -1.516 0.129 -0.669
156 reward_eco3_direct_EEF 0.222 0.200 1.111 0.267 -0.187
157 reward_eco3_ind_IM_EEF -0.183 0.162 -1.127 0.260 -0.498
158 reward_eco3_total_EEF 0.040 0.219 0.181 0.856 -0.401
159 reward_eco3_direct_EEC 0.056 0.192 0.294 0.769 -0.299
160 reward_eco3_ind_IM_EEC -0.143 0.120 -1.191 0.234 -0.386
161 reward_eco3_total_EEC -0.087 0.182 -0.477 0.633 -0.425
ci.upper std.lv std.all std.nox
93 0.316 0.099 0.035 0.099
97 0.185 0.022 0.012 0.022
98 0.382 0.121 0.047 0.121
102 0.333 0.118 0.046 0.118
106 0.142 0.019 0.010 0.019
107 0.382 0.137 0.056 0.137
109 0.168 -0.103 -0.036 -0.103
110 0.278 0.036 0.014 0.036
111 0.166 -0.070 -0.025 -0.070
112 0.356 0.124 0.049 0.124
113 0.330 0.032 0.007 0.032
114 0.202 -0.124 -0.049 -0.124
115 0.131 -0.068 -0.027 -0.068
117 0.215 0.017 0.004 0.017
118 0.196 0.043 0.016 0.043
119 0.245 -0.032 -0.013 -0.032
121 0.222 -0.086 -0.032 -0.086
122 0.235 -0.027 -0.009 -0.027
123 0.434 0.128 0.050 0.128
124 0.283 0.013 -0.001 0.013
125 0.339 0.071 0.025 0.071
126 0.205 0.059 0.023 0.059
127 0.165 0.015 0.003 0.015
128 0.167 0.037 0.013 0.037
129 0.492 0.187 0.074 0.187
130 0.323 0.028 0.003 0.028
131 0.352 0.108 0.038 0.108
132 0.301 0.078 0.028 0.078
136 0.156 -0.115 -0.051 -0.115
137 0.128 -0.044 -0.020 -0.044
138 0.125 -0.159 -0.071 -0.159
142 0.285 0.040 0.021 0.040
143 0.446 -0.015 -0.006 -0.015
144 0.417 -0.019 -0.007 -0.019
145 0.436 0.044 0.019 0.044
146 0.236 -0.118 -0.054 -0.118
148 0.548 0.210 0.084 0.210
149 0.241 -0.185 -0.070 -0.185
150 0.299 0.100 0.040 0.100
151 0.124 -0.088 -0.033 -0.088
152 -0.001 -0.189 -0.073 -0.189
153 0.595 0.144 0.059 0.144
154 0.306 -0.162 -0.068 -0.162
155 0.072 -0.307 -0.127 -0.307
156 0.623 0.206 0.070 0.206
157 0.138 -0.169 -0.057 -0.169
158 0.498 0.037 0.012 0.037
159 0.443 0.058 0.021 0.058
160 0.098 -0.147 -0.050 -0.147
161 0.277 -0.089 -0.029 -0.089With control variableslavaan 0.6-21 ended normally after 60 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 49
Number of observations 243
Model Test User Model:
Standard Scaled
Test Statistic 137.542 125.539
Degrees of freedom 101 101
P-value (Chi-square) 0.009 0.049
Scaling correction factor 1.096
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2267.851 1745.341
Degrees of freedom 138 138
P-value 0.000 0.000
Scaling correction factor 1.299
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) -3383.103 -3383.103
Scaling correction factor 1.699
for the MLR correction
Loglikelihood unrestricted model (H1) -3314.332 -3314.332
Scaling correction factor 1.293
for the MLR correction
Akaike (AIC) 6864.207 6864.207
Bayesian (BIC) 7035.367 7035.367
Sample-size adjusted Bayesian (SABIC) 6880.044 6880.044
Root Mean Square Error of Approximation:
RMSEA 0.039 0.032
90 Percent confidence interval - lower 0.020 0.006
90 Percent confidence interval - upper 0.054 0.048
P-value H_0: RMSEA <= 0.050 0.883 0.973
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.033
90 Percent confidence interval - lower 0.002
90 Percent confidence interval - upper 0.051
P-value H_0: Robust RMSEA <= 0.050 0.944
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.035 0.035
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 0.830 0.841
ADT2 1.072 0.081 13.237 0.000 0.889 0.895
ADT3 1.102 0.077 14.325 0.000 0.915 0.864
IM =~
IM1 1.000 0.910 0.870
IM2 0.691 0.098 7.045 0.000 0.629 0.745
IM3 0.768 0.097 7.877 0.000 0.699 0.724
EEF =~
EEF1 1.000 1.083 0.915
EEF2 0.982 0.046 21.170 0.000 1.063 0.914
EEF3 0.937 0.043 21.798 0.000 1.014 0.897
EEC =~
EEC1 1.000 0.979 0.734
EEC2 1.271 0.101 12.589 0.000 1.245 0.878
EEC3 1.327 0.085 15.675 0.000 1.299 0.942
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.112 0.194 0.580 0.562 0.123 0.048
rwrd0_2 (b_02) 0.013 0.216 0.062 0.950 0.015 0.006
rwrd1_2 (b_12) 0.289 0.179 1.621 0.105 0.318 0.126
rwrd0_3 (b_03) 0.219 0.216 1.012 0.311 0.241 0.081
rwrd1_3 (b_13) -0.071 0.185 -0.386 0.699 -0.078 -0.027
ADT (b_AD) 0.258 0.084 3.057 0.002 0.235 0.235
PEB_yes (b_PE) 0.933 0.125 7.476 0.000 1.025 0.420
EEF ~
rwrd1_1 (c_11) 0.029 0.201 0.147 0.883 0.027 0.011
rwrd0_2 (c_02) -0.059 0.182 -0.326 0.745 -0.055 -0.021
rwrd1_2 (c_12) 0.008 0.168 0.049 0.961 0.008 0.003
rwrd0_3 (c_03) -0.208 0.174 -1.199 0.231 -0.192 -0.065
rwrd1_3 (c_13) 0.014 0.186 0.076 0.940 0.013 0.005
IM (c_IM) 0.656 0.100 6.555 0.000 0.551 0.551
ADT (c_AD) 0.310 0.077 4.038 0.000 0.238 0.238
PEB_yes (c_PE) 0.266 0.179 1.488 0.137 0.246 0.101
EEC ~
rwrd1_1 (d_11) 0.219 0.198 1.108 0.268 0.224 0.087
rwrd0_2 (d_02) 0.185 0.202 0.916 0.360 0.189 0.073
rwrd1_2 (d_12) 0.248 0.181 1.366 0.172 0.253 0.100
rwrd0_3 (d_03) 0.092 0.186 0.496 0.620 0.094 0.032
rwrd1_3 (d_13) 0.134 0.208 0.644 0.520 0.137 0.047
IM (d_IM) 0.528 0.092 5.729 0.000 0.491 0.491
ADT (d_AD) 0.289 0.081 3.557 0.000 0.245 0.245
PEB_yes (d_PE) 0.047 0.168 0.281 0.779 0.048 0.020
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.114 0.056 2.037 0.042 0.114 0.304
.EEF ~~
.EEC 0.225 0.066 3.392 0.001 0.375 0.375
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.ADT1 0.284 0.061 4.659 0.000 0.284 0.292
.ADT2 0.197 0.048 4.087 0.000 0.197 0.199
.ADT3 0.284 0.075 3.807 0.000 0.284 0.253
.IM1 0.266 0.068 3.930 0.000 0.266 0.243
.IM2 0.317 0.073 4.370 0.000 0.317 0.445
.IM3 0.443 0.163 2.714 0.007 0.443 0.476
.EEF1 0.229 0.051 4.537 0.000 0.229 0.164
.EEF2 0.222 0.041 5.418 0.000 0.222 0.164
.EEF3 0.251 0.056 4.506 0.000 0.251 0.196
.EEC1 0.823 0.093 8.828 0.000 0.823 0.462
.EEC2 0.459 0.095 4.850 0.000 0.459 0.229
.EEC3 0.214 0.060 3.559 0.000 0.214 0.113
ADT 0.689 0.090 7.655 0.000 1.000 1.000
.IM 0.623 0.106 5.850 0.000 0.752 0.752
.EEF 0.606 0.105 5.760 0.000 0.517 0.517
.EEC 0.598 0.099 6.062 0.000 0.623 0.623
R-Square:
Estimate
ADT1 0.708
ADT2 0.801
ADT3 0.747
IM1 0.757
IM2 0.555
IM3 0.524
EEF1 0.836
EEF2 0.836
EEF3 0.804
EEC1 0.538
EEC2 0.771
EEC3 0.887
IM 0.248
EEF 0.483
EEC 0.377
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.112 0.194 0.580 0.562 0.123 0.048
reward2_IM 0.276 0.204 1.352 0.176 0.303 0.120
reward3_IM -0.290 0.220 -1.320 0.187 -0.319 -0.109
reward_vrgd_IM 0.033 0.120 0.272 0.785 0.036 0.020
reward_EEF_ec1 0.029 0.201 0.147 0.883 0.027 0.011
reward_EEF_ec2 0.068 0.190 0.356 0.722 0.062 0.024
reward_EEF_ec3 0.222 0.197 1.131 0.258 0.205 0.070
reward_man_EEF 0.106 0.112 0.953 0.341 0.098 0.035
ind_rwrd_EEF_1 0.074 0.130 0.566 0.572 0.068 0.026
ind_rwrd_EEF_2 0.181 0.131 1.383 0.167 0.167 0.066
ind_rwrd_EEF_3 -0.190 0.147 -1.298 0.194 -0.176 -0.060
ind_rw__IM_EEF 0.021 0.079 0.272 0.786 0.020 0.011
tt_rwrd_mn_EEF 0.128 0.124 1.032 0.302 0.118 0.046
reward_EEC_ec1 0.219 0.198 1.108 0.268 0.224 0.087
reward_EEC_ec2 0.063 0.182 0.346 0.729 0.064 0.027
reward_EEC_ec3 0.042 0.201 0.208 0.835 0.043 0.016
reward_man_EEC 0.108 0.112 0.968 0.333 0.110 0.043
ind_rwrd_EEC_1 0.059 0.103 0.575 0.565 0.061 0.024
ind_rwrd_EEC_2 0.146 0.111 1.317 0.188 0.149 0.059
ind_rwrd_EEC_3 -0.153 0.120 -1.279 0.201 -0.157 -0.053
ind_rw__IM_EEC 0.017 0.063 0.272 0.786 0.018 0.010
tt_rwrd_mn_EEC 0.125 0.118 1.063 0.288 0.128 0.053
eco2_vs_c1_EEF -0.040 0.134 -0.301 0.764 -0.037 -0.014
eco3_vs_c1_EEF -0.112 0.138 -0.812 0.417 -0.103 -0.036
eco1_vs_c2_EEF 0.040 0.134 0.301 0.764 0.037 0.014
eco_main_EEF -0.076 0.117 -0.651 0.515 -0.070 -0.025
eco2_vs_ec1_IM 0.095 0.137 0.694 0.488 0.105 0.042
eco3_vs_ec1_IM 0.018 0.142 0.124 0.901 0.019 0.003
eco1_vs_ec2_IM -0.095 0.137 -0.694 0.488 -0.105 -0.042
in_1__2_IM_EEF -0.062 0.092 -0.677 0.499 -0.058 -0.023
in_2__1_IM_EEF 0.062 0.092 0.677 0.499 0.058 0.023
in_3__1_IM_EEF 0.012 0.093 0.124 0.901 0.011 0.002
ind_c_m_IM_EEF 0.037 0.078 0.473 0.636 0.034 0.012
tt_c1_vs_2_EEF -0.022 0.151 -0.147 0.883 -0.021 -0.009
tt_c2_vs_1_EEF 0.022 0.151 0.147 0.883 0.021 0.009
tt_c3_vs_1_EEF -0.100 0.154 -0.650 0.516 -0.093 -0.034
tot_eco_mn_EEF -0.039 0.132 -0.296 0.767 -0.036 -0.013
eco2_vs_c1_EEC 0.107 0.136 0.783 0.434 0.109 0.043
eco3_vs_c1_EEC 0.003 0.138 0.025 0.980 0.004 -0.004
eco_main_EEC 0.055 0.120 0.460 0.645 0.056 0.019
in_2__1_IM_EEC 0.050 0.073 0.686 0.493 0.051 0.020
in_3__1_IM_EEC 0.009 0.075 0.124 0.901 0.010 0.002
ind_c_m_IM_EEC 0.030 0.063 0.476 0.634 0.030 0.011
tt_c2_vs_1_EEC 0.157 0.151 1.040 0.298 0.160 0.063
tt_c3_vs_1_EEC 0.013 0.136 0.094 0.925 0.013 -0.002
tot_eco_mn_EEC 0.085 0.125 0.681 0.496 0.087 0.030
eco_main_IM 0.056 0.118 0.479 0.632 0.062 0.022
eco3_vs_c2_EEF -0.072 0.138 -0.518 0.605 -0.066 -0.021
in_3__2_IM_EEF -0.051 0.099 -0.512 0.609 -0.047 -0.021
tt_c3_vs_2_EEF -0.122 0.155 -0.792 0.428 -0.113 -0.042
eco3_vs_c2_EEC -0.103 0.134 -0.770 0.441 -0.105 -0.047
in_3__2_IM_EEC -0.041 0.080 -0.515 0.606 -0.042 -0.019
tt_c3_vs_2_EEC -0.144 0.142 -1.012 0.312 -0.147 -0.066
reward_IM_eco1 0.112 0.194 0.580 0.562 0.123 0.048
reward_IM_eco2 0.276 0.204 1.352 0.176 0.303 0.120
reward_IM_eco3 -0.290 0.220 -1.320 0.187 -0.319 -0.109
reward_main_IM 0.033 0.120 0.272 0.785 0.036 0.020
r_3_EEF___1_EE -0.015 0.219 -0.070 0.944 -0.014 -0.006
r_2_EEF___1_EE -0.021 0.200 -0.106 0.916 -0.020 -0.008
r_2_EEC___1_EE 0.028 0.180 0.158 0.874 0.029 0.013
r_3_EEC___2_EE -0.114 0.194 -0.586 0.558 -0.116 -0.052
r_3_EEC___1_EE -0.085 0.207 -0.411 0.681 -0.087 -0.040
rw_2_IM___1_IM 0.177 0.175 1.011 0.312 0.195 0.078
rw_3_IM___1_IM -0.184 0.187 -0.981 0.327 -0.202 -0.075
i__2_EEC___1_E 0.093 0.094 0.995 0.320 0.095 0.038
i__3_EEC___1_E -0.097 0.101 -0.963 0.335 -0.099 -0.037
i__3_EEC___2_E -0.190 0.100 -1.912 0.056 -0.195 -0.075
t__2_EEC___1_E 0.122 0.201 0.608 0.543 0.124 0.051
t__3_EEC___1_E -0.182 0.216 -0.845 0.398 -0.186 -0.076
t__3_EEC___2_E -0.304 0.202 -1.508 0.131 -0.311 -0.127Mediation 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 0.106 0.106 1.009 0.313 -0.160
86 ind_reward_main_IM_EEF 0.021 0.076 0.283 0.778 -0.114
87 tot_reward_main_EEF 0.128 0.121 1.059 0.290 -0.110
91 reward_main_EEC 0.108 0.125 0.861 0.389 -0.174
95 ind_reward_main_IM_EEC 0.017 0.059 0.290 0.772 -0.118
96 tot_reward_main_EEC 0.125 0.110 1.135 0.257 -0.145
98 eco3_vs_eco1_EEF -0.112 0.110 -1.016 0.310 -0.336
99 eco1_vs_eco2_EEF 0.040 0.117 0.343 0.731 -0.202
100 eco_main_EEF -0.076 0.095 -0.799 0.425 -0.278
101 eco2_vs_eco1_IM 0.095 0.156 0.609 0.542 -0.265
102 eco3_vs_eco1_IM 0.018 0.134 0.131 0.895 -0.309
103 eco1_vs_eco2_IM -0.095 0.156 -0.609 0.542 -0.364
104 ind_eco1_vs_eco2_IM_EEF -0.062 0.113 -0.554 0.579 -0.325
106 ind_eco3_vs_eco1_IM_EEF 0.012 0.089 0.129 0.897 -0.187
107 ind_eco_main_IM_EEF 0.037 0.081 0.458 0.647 -0.124
108 tot_eco1_vs_eco2_EEF -0.022 0.159 -0.140 0.889 -0.321
110 tot_eco3_vs_eco1_EEF -0.100 0.128 -0.786 0.432 -0.405
111 tot_eco_main_EEF -0.039 0.122 -0.320 0.749 -0.350
112 eco2_vs_eco1_EEC 0.107 0.151 0.708 0.479 -0.244
113 eco3_vs_eco1_EEC 0.003 0.160 0.022 0.983 -0.369
114 eco_main_EEC 0.055 0.137 0.401 0.689 -0.217
115 ind_eco2_vs_eco1_IM_EEC 0.050 0.086 0.588 0.557 -0.128
116 ind_eco3_vs_eco1_IM_EEC 0.009 0.073 0.127 0.899 -0.149
117 ind_eco_main_IM_EEC 0.030 0.064 0.466 0.641 -0.109
118 tot_eco2_vs_eco1_EEC 0.157 0.157 1.001 0.317 -0.204
119 tot_eco3_vs_eco1_EEC 0.013 0.156 0.082 0.935 -0.282
120 tot_eco_main_EEC 0.085 0.135 0.627 0.530 -0.222
121 eco_main_IM 0.056 0.116 0.487 0.627 -0.211
125 eco3_vs_eco2_EEC -0.103 0.146 -0.705 0.481 -0.408
126 ind_eco3_vs_eco2_IM_EEC -0.041 0.095 -0.432 0.666 -0.215
127 tot_eco3_vs_eco2_EEC -0.144 0.157 -0.916 0.360 -0.537
131 reward_main_IM 0.033 0.110 0.297 0.767 -0.174
132 reward_eco3_EEF_vs_reward_eco1_EEF -0.015 0.190 -0.081 0.935 -0.424
133 reward_eco2_EEF_vs_reward_eco1_EEF -0.021 0.151 -0.140 0.889 -0.393
134 reward_eco2_EEC_vs_reward_eco1_EEC 0.028 0.182 0.156 0.876 -0.384
135 reward_eco3_EEC_vs_reward_eco2_EEC -0.114 0.213 -0.534 0.593 -0.567
137 reward_eco2_IM_vs_reward_eco1_IM 0.177 0.170 1.042 0.298 -0.260
138 reward_eco3_IM_vs_reward_eco1_IM -0.184 0.161 -1.142 0.253 -0.488
139 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.093 0.096 0.975 0.329 -0.129
140 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.097 0.085 -1.141 0.254 -0.244
141 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.190 0.079 -2.399 0.016 -0.337
142 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.122 0.192 0.636 0.525 -0.343
143 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.182 0.249 -0.733 0.463 -0.716
144 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.304 0.224 -1.357 0.175 -0.789
ci.upper std.lv std.all std.nox
82 0.311 0.098 0.035 0.098
86 0.174 0.020 0.011 0.020
87 0.420 0.118 0.046 0.118
91 0.355 0.110 0.043 0.110
95 0.128 0.018 0.010 0.018
96 0.318 0.128 0.053 0.128
98 0.113 -0.103 -0.036 -0.103
99 0.314 0.037 0.014 0.037
100 0.145 -0.070 -0.025 -0.070
101 0.364 0.105 0.042 0.105
102 0.304 0.019 0.003 0.019
103 0.265 -0.105 -0.042 -0.105
104 0.205 -0.058 -0.023 -0.058
106 0.218 0.011 0.002 0.011
107 0.249 0.034 0.012 0.034
108 0.300 -0.021 -0.009 -0.021
110 0.119 -0.093 -0.034 -0.093
111 0.157 -0.036 -0.013 -0.036
112 0.468 0.109 0.043 0.109
113 0.313 0.004 -0.004 0.004
114 0.380 0.056 0.019 0.056
115 0.235 0.051 0.020 0.051
116 0.189 0.010 0.002 0.010
117 0.168 0.030 0.011 0.030
118 0.458 0.160 0.063 0.160
119 0.318 0.013 -0.002 0.013
120 0.388 0.087 0.030 0.087
121 0.300 0.062 0.022 0.062
125 0.200 -0.105 -0.047 -0.105
126 0.193 -0.042 -0.019 -0.042
127 0.111 -0.147 -0.066 -0.147
131 0.236 0.036 0.020 0.036
132 0.353 -0.014 -0.006 -0.014
133 0.302 -0.020 -0.008 -0.020
134 0.521 0.029 0.013 0.029
135 0.292 -0.116 -0.052 -0.116
137 0.507 0.195 0.078 0.195
138 0.197 -0.202 -0.075 -0.202
139 0.306 0.095 0.038 0.095
140 0.123 -0.099 -0.037 -0.099
141 -0.003 -0.195 -0.075 -0.195
142 0.590 0.124 0.051 0.124
143 0.403 -0.186 -0.076 -0.186
144 0.202 -0.311 -0.127 -0.311With control variableslavaan 0.6-21 ended normally after 63 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 53
Number of observations 243
Model Test User Model:
Standard Scaled
Test Statistic 235.859 218.810
Degrees of freedom 157 157
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.078
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3015.286 2419.140
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.246
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) -4384.870 -4384.870
Scaling correction factor 1.697
for the MLR correction
Loglikelihood unrestricted model (H1) -4266.941 -4266.941
Scaling correction factor 1.234
for the MLR correction
Akaike (AIC) 8875.740 8875.740
Bayesian (BIC) 9060.872 9060.872
Sample-size adjusted Bayesian (SABIC) 8892.870 8892.870
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.033 0.027
90 Percent confidence interval - upper 0.057 0.052
P-value H_0: RMSEA <= 0.050 0.728 0.911
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.054
P-value H_0: Robust RMSEA <= 0.050 0.850
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.110 0.110
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 1.311 0.891
TR2 1.084 0.045 24.086 0.000 1.421 0.939
TR3 1.047 0.045 23.077 0.000 1.373 0.921
ADT =~
ADT1 1.000 0.826 0.837
ADT2 1.083 0.080 13.612 0.000 0.894 0.900
ADT3 1.107 0.075 14.706 0.000 0.914 0.863
IM =~
IM1 1.000 0.910 0.869
IM2 0.692 0.097 7.136 0.000 0.629 0.746
IM3 0.769 0.096 7.971 0.000 0.699 0.725
EEF =~
EEF1 1.000 1.081 0.913
EEF2 0.985 0.046 21.329 0.000 1.064 0.915
EEF3 0.939 0.043 21.858 0.000 1.014 0.897
EEC =~
EEC1 1.000 0.979 0.734
EEC2 1.269 0.101 12.621 0.000 1.243 0.877
EEC3 1.328 0.085 15.614 0.000 1.300 0.943
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.093 0.207 0.451 0.652 0.103 0.040
rwrd0_2 (b_02) 0.045 0.212 0.211 0.833 0.049 0.019
rwrd1_2 (b_12) 0.279 0.181 1.539 0.124 0.307 0.121
rwrd0_3 (b_03) 0.234 0.222 1.052 0.293 0.257 0.087
rwrd1_3 (b_13) -0.068 0.186 -0.367 0.714 -0.075 -0.026
PEB_yes (b_PE) 0.939 0.124 7.588 0.000 1.032 0.423
EEF ~
rwrd1_1 (c_11) -0.002 0.209 -0.011 0.992 -0.002 -0.001
rwrd0_2 (c_02) -0.026 0.187 -0.139 0.889 -0.024 -0.009
rwrd1_2 (c_12) -0.028 0.176 -0.159 0.874 -0.026 -0.010
rwrd0_3 (c_03) -0.210 0.181 -1.161 0.246 -0.194 -0.066
rwrd1_3 (c_13) 0.023 0.190 0.120 0.904 0.021 0.007
IM (c_IM) 0.738 0.102 7.201 0.000 0.621 0.621
PEB_yes (c_PE) 0.195 0.194 1.004 0.315 0.180 0.074
EEC ~
rwrd1_1 (d_11) 0.189 0.203 0.935 0.350 0.193 0.075
rwrd0_2 (d_02) 0.215 0.202 1.063 0.288 0.219 0.085
rwrd1_2 (d_12) 0.214 0.193 1.110 0.267 0.218 0.086
rwrd0_3 (d_03) 0.089 0.192 0.464 0.643 0.091 0.031
rwrd1_3 (d_13) 0.143 0.220 0.647 0.518 0.146 0.051
IM (d_IM) 0.604 0.087 6.921 0.000 0.561 0.561
PEB_yes (d_PE) -0.018 0.177 -0.102 0.919 -0.018 -0.008
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.113 0.055 2.055 0.040 0.113 0.302
TR ~~
ADT 0.415 0.086 4.807 0.000 0.383 0.383
.EEF ~~
.EEC 0.282 0.074 3.804 0.000 0.428 0.428
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.448 0.073 6.107 0.000 0.448 0.207
.TR2 0.273 0.065 4.207 0.000 0.273 0.119
.TR3 0.339 0.080 4.256 0.000 0.339 0.153
.ADT1 0.291 0.060 4.856 0.000 0.291 0.299
.ADT2 0.188 0.047 4.045 0.000 0.188 0.191
.ADT3 0.286 0.078 3.646 0.000 0.286 0.255
.IM1 0.267 0.066 4.079 0.000 0.267 0.244
.IM2 0.316 0.072 4.380 0.000 0.316 0.444
.IM3 0.442 0.163 2.711 0.007 0.442 0.475
.EEF1 0.233 0.050 4.632 0.000 0.233 0.166
.EEF2 0.220 0.041 5.404 0.000 0.220 0.163
.EEF3 0.250 0.056 4.471 0.000 0.250 0.196
.EEC1 0.823 0.093 8.822 0.000 0.823 0.462
.EEC2 0.463 0.095 4.884 0.000 0.463 0.231
.EEC3 0.211 0.060 3.544 0.000 0.211 0.111
TR 1.719 0.160 10.747 0.000 1.000 1.000
ADT 0.682 0.089 7.700 0.000 1.000 1.000
.IM 0.667 0.120 5.569 0.000 0.806 0.806
.EEF 0.665 0.115 5.764 0.000 0.570 0.570
.EEC 0.652 0.109 5.985 0.000 0.680 0.680
R-Square:
Estimate
TR1 0.793
TR2 0.881
TR3 0.847
ADT1 0.701
ADT2 0.809
ADT3 0.745
IM1 0.756
IM2 0.556
IM3 0.525
EEF1 0.834
EEF2 0.837
EEF3 0.804
EEC1 0.538
EEC2 0.769
EEC3 0.889
IM 0.194
EEF 0.430
EEC 0.320###Comparing difference between model fits