Kaiser-Meyer-Olkin factor adequacy
Call: KMO(r = efa_data_good)
Overall MSA = 0.87
MSA for each item =
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2 TR3
0.92 0.82 0.85 0.88 0.90 0.91 0.91 0.85 0.82 0.90 0.82 0.86 0.89 0.78 0.83 Reporting SEM
Factor analyses
KMO
Correlation analysis
Bartlett test
R was not square, finding R from data$chisq
[1] 2719.358
$p.value
[1] 0
$df
[1] 105Correlation matrix
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1
IM1 1.0000000 0.6969983 0.61091907 0.5824033 0.6350963 0.6052710 0.4563083
IM2 0.6969983 1.0000000 0.75692983 0.4093197 0.5105893 0.5006186 0.4079992
IM3 0.6109191 0.7569298 1.00000000 0.3752008 0.4497618 0.4808622 0.4638013
EEF1 0.5824033 0.4093197 0.37520084 1.0000000 0.8613242 0.8385370 0.5232474
EEF2 0.6350963 0.5105893 0.44976178 0.8613242 1.0000000 0.8445245 0.5351014
EEF3 0.6052710 0.5006186 0.48086224 0.8385370 0.8445245 1.0000000 0.5245033
EEC1 0.4563083 0.4079992 0.46380133 0.5232474 0.5351014 0.5245033 1.0000000
EEC2 0.5001540 0.3652403 0.35149398 0.5133985 0.5623703 0.5349152 0.6070937
EEC3 0.4823611 0.3202348 0.34301820 0.5364226 0.5619186 0.5618763 0.7079159
ADT1 0.3816546 0.1941130 0.17459476 0.4151617 0.4090402 0.3711639 0.3336441
ADT2 0.2680701 0.1059908 0.08867374 0.3165750 0.2926516 0.2894485 0.2688103
ADT3 0.3653216 0.2253657 0.19242433 0.4026986 0.3752902 0.3535699 0.3226852
TR1 0.2931848 0.2146986 0.20361287 0.3154258 0.2992275 0.3157273 0.3022975
TR2 0.2481052 0.1222667 0.09833759 0.2296259 0.2201294 0.2569115 0.1686477
TR3 0.2512202 0.1485032 0.14777045 0.3060955 0.2859498 0.3281343 0.2443324
EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2
IM1 0.5001540 0.4823611 0.3816546 0.26807010 0.3653216 0.2931848 0.24810517
IM2 0.3652403 0.3202348 0.1941130 0.10599083 0.2253657 0.2146986 0.12226667
IM3 0.3514940 0.3430182 0.1745948 0.08867374 0.1924243 0.2036129 0.09833759
EEF1 0.5133985 0.5364226 0.4151617 0.31657501 0.4026986 0.3154258 0.22962592
EEF2 0.5623703 0.5619186 0.4090402 0.29265156 0.3752902 0.2992275 0.22012942
EEF3 0.5349152 0.5618763 0.3711639 0.28944846 0.3535699 0.3157273 0.25691153
EEC1 0.6070937 0.7079159 0.3336441 0.26881030 0.3226852 0.3022975 0.16864774
EEC2 1.0000000 0.8337006 0.3489448 0.27488633 0.3485744 0.2994427 0.18894384
EEC3 0.8337006 1.0000000 0.3914160 0.30662715 0.3447812 0.3460236 0.24842704
ADT1 0.3489448 0.3914160 1.0000000 0.79785726 0.7683834 0.4668001 0.42830516
ADT2 0.2748863 0.3066272 0.7978573 1.00000000 0.8040714 0.4398094 0.40774756
ADT3 0.3485744 0.3447812 0.7683834 0.80407142 1.0000000 0.4450446 0.38155849
TR1 0.2994427 0.3460236 0.4668001 0.43980939 0.4450446 1.0000000 0.82902798
TR2 0.1889438 0.2484270 0.4283052 0.40774756 0.3815585 0.8290280 1.00000000
TR3 0.2171397 0.2904057 0.4501215 0.41989134 0.4584716 0.8077895 0.86526367
TR3
IM1 0.2512202
IM2 0.1485032
IM3 0.1477705
EEF1 0.3060955
EEF2 0.2859498
EEF3 0.3281343
EEC1 0.2443324
EEC2 0.2171397
EEC3 0.2904057
ADT1 0.4501215
ADT2 0.4198913
ADT3 0.4584716
TR1 0.8077895
TR2 0.8652637
TR3 1.0000000
Outliers
Loading required namespace: GPArotationThreshold = 0.35
Loadings:
MR1 MR2 MR3 MR5 MR4
IM1 NA NA NA NA 0.551
IM2 NA NA NA NA 0.947
IM3 NA NA NA NA 0.815
EEF1 0.978 NA NA NA NA
EEF2 0.884 NA NA NA NA
EEF3 0.837 NA NA NA NA
EEC1 NA NA NA 0.569 NA
EEC2 NA NA NA 0.771 NA
EEC3 NA NA NA 1.032 NA
ADT1 NA NA 0.822 NA NA
ADT2 NA NA 0.957 NA NA
ADT3 NA NA 0.863 NA NA
TR1 NA 0.835 NA NA NA
TR2 NA 0.979 NA NA NA
TR3 NA 0.899 NA NA NA
MR1 MR2 MR3 MR5 MR4
SS loadings NA NA NA NA NA
Proportion Var NA NA NA NA NA
Cumulative Var NA NA NA NA NA
Factor Correlation Matrix: 1 2 3 4 5
1 1.000 0.311 0.420 0.618 0.556
2 0.311 1.000 0.509 0.297 0.182
3 0.420 0.509 1.000 0.389 0.210
4 0.618 0.297 0.389 1.000 0.427
5 0.556 0.182 0.210 0.427 1.000
1 2 3 4 5
1 1.000 0.312 0.420 0.621 0.557
2 0.312 1.000 0.510 0.299 0.182
3 0.420 0.510 1.000 0.390 0.211
4 0.621 0.299 0.390 1.000 0.428
5 0.557 0.182 0.211 0.428 1.000CFA
Without controls
lavaan 0.6-21 ended normally after 34 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 21
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 76.299 67.596
Degrees of freedom 24 24
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.129
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1289.851 744.144
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.733
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.958 0.938
Tucker-Lewis Index (TLI) 0.937 0.908
Robust Comparative Fit Index (CFI) 0.960
Robust Tucker-Lewis Index (TLI) 0.940
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2118.005 -2118.005
Scaling correction factor 2.270
for the MLR correction
Loglikelihood unrestricted model (H1) -2079.855 -2079.855
Scaling correction factor 1.661
for the MLR correction
Akaike (AIC) 4278.010 4278.010
Bayesian (BIC) 4347.274 4347.274
Sample-size adjusted Bayesian (SABIC) 4280.744 4280.744
Root Mean Square Error of Approximation:
RMSEA 0.104 0.095
90 Percent confidence interval - lower 0.079 0.070
90 Percent confidence interval - upper 0.131 0.121
P-value H_0: RMSEA <= 0.050 0.001 0.002
P-value H_0: RMSEA >= 0.080 0.941 0.852
Robust RMSEA 0.101
90 Percent confidence interval - lower 0.073
90 Percent confidence interval - upper 0.130
P-value H_0: Robust RMSEA <= 0.050 0.002
P-value H_0: Robust RMSEA >= 0.080 0.898
Standardized Root Mean Square Residual:
SRMR 0.060 0.060
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 1.342 0.134 10.027 0.000 1.080 1.604
EEC3 1.413 0.114 12.381 0.000 1.189 1.636
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.038 0.063 16.540 0.000 0.915 1.161
EEF3 0.967 0.051 19.063 0.000 0.868 1.066
IM =~
IM1 1.000 1.000 1.000
IM2 0.849 0.107 7.909 0.000 0.639 1.059
IM3 0.850 0.149 5.706 0.000 0.558 1.142
Std.lv Std.all
0.878 0.698
1.178 0.856
1.240 0.946
0.993 0.898
1.031 0.919
0.961 0.894
0.819 0.832
0.695 0.844
0.696 0.727
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC ~~
EEF 0.521 0.103 5.066 0.000 0.319 0.722
IM 0.311 0.081 3.837 0.000 0.152 0.469
EEF ~~
IM 0.493 0.095 5.185 0.000 0.307 0.679
Std.lv Std.all
0.597 0.597
0.432 0.432
0.606 0.606
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.812 0.097 8.366 0.000 0.622 1.002
.EEC2 0.508 0.113 4.507 0.000 0.287 0.728
.EEC3 0.179 0.066 2.737 0.006 0.051 0.308
.EEF1 0.236 0.046 5.131 0.000 0.146 0.327
.EEF2 0.196 0.046 4.225 0.000 0.105 0.286
.EEF3 0.233 0.065 3.550 0.000 0.104 0.361
.IM1 0.298 0.082 3.620 0.000 0.137 0.459
.IM2 0.195 0.064 3.064 0.002 0.070 0.319
.IM3 0.433 0.220 1.969 0.049 0.002 0.864
EEC 0.771 0.137 5.645 0.000 0.503 1.038
EEF 0.987 0.173 5.691 0.000 0.647 1.327
IM 0.670 0.109 6.132 0.000 0.456 0.884
Std.lv Std.all
0.812 0.513
0.508 0.268
0.179 0.105
0.236 0.193
0.196 0.155
0.233 0.201
0.298 0.308
0.195 0.287
0.433 0.472
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.487
EEC2 0.732
EEC3 0.895
EEF1 0.807
EEF2 0.845
EEF3 0.799
IM1 0.692
IM2 0.713
IM3 0.528Cronbach’s Alpha: EEC EEF IM
0.863 0.930 0.837 Omega: EEC EEF IM
0.888 0.930 0.842 Average Variance Extracted (AVE): EEC EEF IM
0.711 0.817 0.639 Details
Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
28 EEC =~ IM1 10.365 0.224 0.197 0.200 0.200
34 EEF =~ IM1 14.738 0.299 0.297 0.302 0.302
39 IM =~ EEC3 13.169 -0.324 -0.265 -0.202 -0.202
43 EEC1 ~~ EEC2 10.050 -0.254 -0.254 -0.395 -0.395
50 EEC1 ~~ IM3 13.840 0.175 0.175 0.296 0.296
78 IM2 ~~ IM3 17.062 0.193 0.193 0.665 0.665Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
43 EEC1 ~~ EEC2 10.050 -0.254 -0.254 -0.395 -0.395
50 EEC1 ~~ IM3 13.840 0.175 0.175 0.296 0.296
78 IM2 ~~ IM3 17.062 0.193 0.193 0.665 0.665$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.082 0.000
EEC3 0.010 0.008 0.000
EEF1 0.110 -0.015 -0.057 0.000
EEF2 0.117 0.058 -0.022 0.005 0.000
EEF3 0.115 0.033 -0.003 0.010 -0.013 0.000
IM1 0.131 0.161 0.074 0.053 0.102 0.080 0.000
IM2 0.092 -0.005 -0.116 -0.102 -0.004 -0.032 -0.006 0.000
IM3 0.235 0.002 -0.060 -0.107 -0.026 0.004 -0.036 0.037 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -2.284 0.000
EEC3 0.389 0.108 0.000
EEF1 1.338 -0.182 -0.727 0.000
EEF2 1.723 0.773 -0.302 0.077 0.000
EEF3 1.558 0.444 -0.040 0.167 -0.279 0.000
IM1 1.919 2.359 1.509 0.896 1.730 1.396 0.000
IM2 1.709 -0.097 -2.143 -1.650 -0.114 -0.634 -0.233 0.000
IM3 2.236 0.028 -0.854 -1.564 -0.506 0.077 -1.311 1.316 0.000Modified measurement model1
Allowing covariance between IM2 and IM3lavaan 0.6-21 ended normally after 39 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 22
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 59.854 52.380
Degrees of freedom 23 23
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.143
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1289.851 744.144
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.733
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.971 0.959
Tucker-Lewis Index (TLI) 0.954 0.935
Robust Comparative Fit Index (CFI) 0.973
Robust Tucker-Lewis Index (TLI) 0.957
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2109.782 -2109.782
Scaling correction factor 2.203
for the MLR correction
Loglikelihood unrestricted model (H1) -2079.855 -2079.855
Scaling correction factor 1.661
for the MLR correction
Akaike (AIC) 4263.564 4263.564
Bayesian (BIC) 4336.127 4336.127
Sample-size adjusted Bayesian (SABIC) 4266.429 4266.429
Root Mean Square Error of Approximation:
RMSEA 0.090 0.080
90 Percent confidence interval - lower 0.062 0.053
90 Percent confidence interval - upper 0.118 0.107
P-value H_0: RMSEA <= 0.050 0.011 0.035
P-value H_0: RMSEA >= 0.080 0.734 0.524
Robust RMSEA 0.085
90 Percent confidence interval - lower 0.055
90 Percent confidence interval - upper 0.116
P-value H_0: Robust RMSEA <= 0.050 0.031
P-value H_0: Robust RMSEA >= 0.080 0.642
Standardized Root Mean Square Residual:
SRMR 0.051 0.051
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 1.344 0.135 9.959 0.000 1.080 1.609
EEC3 1.416 0.114 12.427 0.000 1.193 1.639
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.034 0.065 15.887 0.000 0.906 1.161
EEF3 0.963 0.051 18.956 0.000 0.864 1.063
IM =~
IM1 1.000 1.000 1.000
IM2 0.647 0.115 5.640 0.000 0.422 0.872
IM3 0.617 0.123 5.029 0.000 0.377 0.858
Std.lv Std.all
0.877 0.697
1.178 0.856
1.241 0.947
0.996 0.901
1.030 0.918
0.960 0.893
0.932 0.947
0.603 0.733
0.575 0.601
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.174 0.071 2.433 0.015 0.034 0.314
EEC ~~
EEF 0.521 0.103 5.077 0.000 0.320 0.722
IM 0.378 0.078 4.842 0.000 0.225 0.531
EEF ~~
IM 0.576 0.095 6.080 0.000 0.390 0.761
Std.lv Std.all
0.174 0.405
0.597 0.597
0.463 0.463
0.620 0.620
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.815 0.098 8.345 0.000 0.623 1.006
.EEC2 0.508 0.114 4.469 0.000 0.285 0.730
.EEC3 0.178 0.066 2.690 0.007 0.048 0.307
.EEF1 0.231 0.046 5.049 0.000 0.141 0.320
.EEF2 0.199 0.047 4.217 0.000 0.106 0.291
.EEF3 0.234 0.065 3.622 0.000 0.108 0.361
.IM1 0.099 0.086 1.153 0.249 -0.069 0.268
.IM2 0.314 0.084 3.717 0.000 0.148 0.479
.IM3 0.586 0.193 3.031 0.002 0.207 0.965
EEC 0.768 0.136 5.641 0.000 0.501 1.035
EEF 0.992 0.175 5.664 0.000 0.649 1.336
IM 0.869 0.149 5.848 0.000 0.578 1.160
Std.lv Std.all
0.815 0.515
0.508 0.268
0.178 0.103
0.231 0.189
0.199 0.158
0.234 0.203
0.099 0.103
0.314 0.463
0.586 0.639
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.485
EEC2 0.732
EEC3 0.897
EEF1 0.811
EEF2 0.842
EEF3 0.797
IM1 0.897
IM2 0.537
IM3 0.361Cronbach’s Alpha: EEC EEF IM
0.863 0.930 0.837 Omega: EEC EEF IM
0.888 0.930 0.768 Average Variance Extracted (AVE): EEC EEF IM
0.711 0.817 0.610 Details
Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 12.195 0.162 0.162 0.235 0.235Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 12.195 0.162 0.162 0.235 0.235$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.080 0.000
EEC3 0.012 0.007 0.000
EEF1 0.110 -0.016 -0.059 0.000
EEF2 0.119 0.060 -0.021 0.003 0.000
EEF3 0.117 0.034 -0.002 0.008 -0.010 0.000
IM1 0.063 0.070 -0.023 -0.030 0.019 0.002 0.000
IM2 0.111 0.019 -0.091 -0.056 0.045 0.014 0.001 0.000
IM3 0.266 0.043 -0.017 -0.043 0.042 0.067 -0.002 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -2.195 0.000
EEC3 0.330 0.359 0.000
EEF1 1.528 -0.330 -1.714 0.000
EEF2 1.751 1.265 -0.598 0.134 0.000
EEF3 1.667 0.758 -0.044 0.347 -0.516 0.000
IM1 0.941 1.579 -1.266 -1.020 0.612 0.076 0.000
IM2 1.970 0.419 -2.109 -1.819 1.320 0.443 0.030 0.000
IM3 2.342 0.575 -0.234 -0.923 0.803 1.728 -0.101 0.000 0.000Modified measurement model2
Allowing 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 200
Model Test User Model:
Standard Scaled
Test Statistic 48.766 42.645
Degrees of freedom 22 22
P-value (Chi-square) 0.001 0.005
Scaling correction factor 1.144
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1289.851 744.144
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.733
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.979 0.971
Tucker-Lewis Index (TLI) 0.965 0.952
Robust Comparative Fit Index (CFI) 0.981
Robust Tucker-Lewis Index (TLI) 0.969
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2104.239 -2104.239
Scaling correction factor 2.156
for the MLR correction
Loglikelihood unrestricted model (H1) -2079.855 -2079.855
Scaling correction factor 1.661
for the MLR correction
Akaike (AIC) 4254.477 4254.477
Bayesian (BIC) 4330.339 4330.339
Sample-size adjusted Bayesian (SABIC) 4257.472 4257.472
Root Mean Square Error of Approximation:
RMSEA 0.078 0.068
90 Percent confidence interval - lower 0.048 0.039
90 Percent confidence interval - upper 0.108 0.097
P-value H_0: RMSEA <= 0.050 0.059 0.137
P-value H_0: RMSEA >= 0.080 0.484 0.273
Robust RMSEA 0.073
90 Percent confidence interval - lower 0.039
90 Percent confidence interval - upper 0.106
P-value H_0: Robust RMSEA <= 0.050 0.117
P-value H_0: Robust RMSEA >= 0.080 0.395
Standardized Root Mean Square Residual:
SRMR 0.039 0.039
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.309 0.127 10.332 0.000 1.061 1.558
EEC3 1.195 0.134 8.939 0.000 0.933 1.457
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.035 0.065 15.979 0.000 0.908 1.162
EEF3 0.963 0.051 18.880 0.000 0.863 1.063
IM =~
IM1 1.000 1.000 1.000
IM2 0.665 0.114 5.842 0.000 0.442 0.888
IM3 0.635 0.124 5.136 0.000 0.393 0.878
Std.lv Std.all
0.966 0.768
1.265 0.919
1.154 0.881
0.996 0.900
1.031 0.919
0.959 0.892
0.920 0.935
0.611 0.742
0.584 0.610
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.164 0.071 2.296 0.022 0.024 0.303
.EEC1 ~~
.EEC2 -0.269 0.089 -3.026 0.002 -0.443 -0.095
EEC ~~
EEF 0.583 0.107 5.464 0.000 0.374 0.792
IM 0.440 0.079 5.564 0.000 0.285 0.594
EEF ~~
IM 0.574 0.095 6.015 0.000 0.387 0.761
Std.lv Std.all
0.164 0.391
-0.269 -0.613
0.606 0.606
0.495 0.495
0.626 0.626
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.650 0.131 4.953 0.000 0.393 0.907
.EEC2 0.296 0.131 2.264 0.024 0.040 0.552
.EEC3 0.385 0.103 3.732 0.000 0.183 0.587
.EEF1 0.231 0.045 5.125 0.000 0.143 0.320
.EEF2 0.197 0.046 4.302 0.000 0.107 0.286
.EEF3 0.236 0.066 3.573 0.000 0.107 0.365
.IM1 0.122 0.079 1.545 0.122 -0.033 0.278
.IM2 0.304 0.084 3.617 0.000 0.139 0.469
.IM3 0.576 0.195 2.947 0.003 0.193 0.958
EEC 0.933 0.164 5.700 0.000 0.612 1.254
EEF 0.992 0.175 5.669 0.000 0.649 1.335
IM 0.846 0.140 6.027 0.000 0.571 1.121
Std.lv Std.all
0.650 0.411
0.296 0.156
0.385 0.224
0.231 0.189
0.197 0.156
0.236 0.204
0.122 0.126
0.304 0.449
0.576 0.628
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.589
EEC2 0.844
EEC3 0.776
EEF1 0.811
EEF2 0.844
EEF3 0.796
IM1 0.874
IM2 0.551
IM3 0.372Cronbach’s Alpha: EEC EEF IM
0.863 0.930 0.837 Omega: EEC EEF IM
0.936 0.930 0.772 Average Variance Extracted (AVE): EEC EEF IM
0.744 0.817 0.609 Details
Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 11.989 0.157 0.157 0.257 0.257Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
51 EEC1 ~~ IM3 11.989 0.157 0.157 0.257 0.257$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.016 0.009 0.000
EEF1 0.048 -0.079 -0.018 0.000
EEF2 0.054 -0.006 0.020 0.002 0.000
EEF3 0.058 -0.026 0.038 0.009 -0.010 0.000
IM1 0.002 0.002 -0.013 -0.028 0.020 0.005 0.000
IM2 0.063 -0.034 -0.093 -0.065 0.036 0.006 0.001 0.000
IM3 0.220 -0.009 -0.020 -0.052 0.032 0.059 -0.004 0.000 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 0.000 0.000
EEC3 -0.482 0.429 0.000
EEF1 0.827 -1.567 -0.547 0.000
EEF2 1.008 -0.148 0.631 0.196 0.000
EEF3 1.010 -0.588 0.899 0.673 -1.015 0.000
IM1 0.026 0.071 -0.405 -1.205 0.627 0.182 0.000
IM2 1.082 -0.786 -2.273 -2.132 1.110 0.198 0.065 0.000
IM3 1.837 -0.119 -0.296 -1.110 0.622 1.548 -0.203 0.000 0.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC
IM "1" "0.63 (0)" "0.49 (0)"
EEF "0.63 (0)" "1" "0.61 (0)"
EEC "0.49 (0)" "0.61 (0)" "1" Discriminant validity check lhs op rhs est.std se z pvalue ci.lower ci.upper
1 EEC =~ EEC1 0.768 0.052 14.709 0 0.665 0.870
2 EEC =~ EEC2 0.919 0.038 24.476 0 0.845 0.992
3 EEC =~ EEC3 0.881 0.037 23.800 0 0.808 0.953
4 EEF =~ EEF1 0.900 0.023 38.459 0 0.855 0.946
5 EEF =~ EEF2 0.919 0.020 44.921 0 0.879 0.959
6 EEF =~ EEF3 0.892 0.036 25.020 0 0.822 0.962
7 IM =~ IM1 0.935 0.046 20.383 0 0.845 1.025
8 IM =~ IM2 0.742 0.081 9.217 0 0.585 0.900
9 IM =~ IM3 0.610 0.113 5.387 0 0.388 0.832AVE (IM, EEF, EEC)[1] 0.5990115[1] 0.8167747[1] 0.7363478Square root of AVE (IM, EEF, EEC)[1] 0.7739583[1] 0.9037559[1] 0.8581071 lhs rhs est.std
24 EEC EEF 0.606
25 EEC IM 0.495
26 EEF IM 0.626Correlations between square root AVE with correlations (sqrt vs. correlations with the other constructsIM[1] 0.7739583[1] 0.6264317[1] 0.4949161EEF[1] 0.9037559[1] 0.6264317[1] 0.6060457EEC[1] 0.8581071[1] 0.4949161[1] 0.6060457With controls
lavaan 0.6-21 ended normally after 48 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 126.752 111.960
Degrees of freedom 79 79
P-value (Chi-square) 0.001 0.009
Scaling correction factor 1.132
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2333.038 1629.863
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.431
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.979 0.978
Tucker-Lewis Index (TLI) 0.972 0.971
Robust Comparative Fit Index (CFI) 0.983
Robust Tucker-Lewis Index (TLI) 0.977
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3570.393 -3570.393
Scaling correction factor 1.897
for the MLR correction
Loglikelihood unrestricted model (H1) -3507.017 -3507.017
Scaling correction factor 1.394
for the MLR correction
Akaike (AIC) 7222.787 7222.787
Bayesian (BIC) 7358.018 7358.018
Sample-size adjusted Bayesian (SABIC) 7228.126 7228.126
Root Mean Square Error of Approximation:
RMSEA 0.055 0.046
90 Percent confidence interval - lower 0.036 0.025
90 Percent confidence interval - upper 0.072 0.063
P-value H_0: RMSEA <= 0.050 0.308 0.638
P-value H_0: RMSEA >= 0.080 0.007 0.000
Robust RMSEA 0.049
90 Percent confidence interval - lower 0.025
90 Percent confidence interval - upper 0.068
P-value H_0: Robust RMSEA <= 0.050 0.526
P-value H_0: Robust RMSEA >= 0.080 0.003
Standardized Root Mean Square Residual:
SRMR 0.046 0.046
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
IM =~
IM1 1.000 1.000 1.000
IM2 0.649 0.120 5.392 0.000 0.413 0.885
IM3 0.619 0.126 4.893 0.000 0.371 0.867
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.031 0.066 15.735 0.000 0.903 1.160
EEF3 0.963 0.051 18.818 0.000 0.863 1.063
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.342 0.134 10.025 0.000 1.079 1.604
EEC3 1.422 0.115 12.337 0.000 1.196 1.648
TR =~
TR1 1.000 1.000 1.000
TR2 1.098 0.052 20.936 0.000 0.995 1.201
TR3 1.061 0.054 19.501 0.000 0.954 1.167
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.030 0.085 12.175 0.000 0.864 1.196
ADT3 1.076 0.080 13.420 0.000 0.919 1.234
Std.lv Std.all
0.931 0.946
0.604 0.734
0.576 0.602
0.997 0.902
1.028 0.917
0.960 0.893
0.876 0.696
1.175 0.853
1.245 0.950
1.287 0.881
1.413 0.942
1.365 0.915
0.851 0.861
0.877 0.890
0.916 0.854
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.173 0.074 2.343 0.019 0.028 0.317
IM ~~
EEF 0.576 0.095 6.049 0.000 0.389 0.763
EEC 0.376 0.079 4.773 0.000 0.221 0.530
TR 0.267 0.103 2.602 0.009 0.066 0.468
ADT 0.152 0.075 2.030 0.042 0.005 0.299
EEF ~~
EEC 0.519 0.103 5.056 0.000 0.318 0.720
TR 0.346 0.109 3.181 0.001 0.133 0.559
ADT 0.244 0.074 3.307 0.001 0.100 0.389
EEC ~~
TR 0.331 0.094 3.522 0.000 0.147 0.515
ADT 0.242 0.069 3.523 0.000 0.107 0.377
TR ~~
ADT 0.523 0.094 5.533 0.000 0.337 0.708
Std.lv Std.all
0.173 0.404
0.621 0.621
0.461 0.461
0.223 0.223
0.192 0.192
0.594 0.594
0.269 0.269
0.288 0.288
0.294 0.294
0.325 0.325
0.477 0.477
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.101 0.093 1.087 0.277 -0.081 0.284
.IM2 0.313 0.087 3.601 0.000 0.143 0.483
.IM3 0.585 0.193 3.024 0.002 0.206 0.964
.EEF1 0.229 0.046 5.009 0.000 0.139 0.319
.EEF2 0.201 0.048 4.190 0.000 0.107 0.296
.EEF3 0.233 0.064 3.622 0.000 0.107 0.360
.EEC1 0.816 0.097 8.389 0.000 0.626 1.007
.EEC2 0.516 0.113 4.553 0.000 0.294 0.738
.EEC3 0.167 0.066 2.539 0.011 0.038 0.297
.TR1 0.477 0.086 5.557 0.000 0.309 0.645
.TR2 0.253 0.064 3.931 0.000 0.127 0.380
.TR3 0.365 0.095 3.856 0.000 0.179 0.550
.ADT1 0.254 0.061 4.166 0.000 0.134 0.373
.ADT2 0.202 0.056 3.621 0.000 0.093 0.311
.ADT3 0.313 0.092 3.392 0.001 0.132 0.493
IM 0.867 0.155 5.586 0.000 0.563 1.171
EEF 0.994 0.175 5.667 0.000 0.650 1.338
EEC 0.767 0.136 5.645 0.000 0.500 1.033
TR 1.657 0.178 9.315 0.000 1.309 2.006
ADT 0.724 0.097 7.450 0.000 0.534 0.915
Std.lv Std.all
0.101 0.105
0.313 0.462
0.585 0.638
0.229 0.187
0.201 0.160
0.233 0.202
0.816 0.516
0.516 0.272
0.167 0.097
0.477 0.223
0.253 0.113
0.365 0.164
0.254 0.259
0.202 0.208
0.313 0.271
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.895
IM2 0.538
IM3 0.362
EEF1 0.813
EEF2 0.840
EEF3 0.798
EEC1 0.484
EEC2 0.728
EEC3 0.903
TR1 0.777
TR2 0.887
TR3 0.836
ADT1 0.741
ADT2 0.792
ADT3 0.729Cronbach’s Alpha: IM EEF EEC TR ADT
0.837 0.930 0.863 0.937 0.900 Omega: IM EEF EEC TR ADT
0.769 0.931 0.887 0.939 0.902 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.610 0.818 0.711 0.834 0.752 $type
[1] "cor.bentler"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.001 0.000
IM3 -0.003 0.000 0.000
EEF1 -0.028 -0.063 -0.041 0.000
EEF2 0.018 0.049 0.039 0.003 0.000
EEF3 0.002 0.014 0.064 0.006 -0.008 0.000
EEC1 0.053 0.108 0.221 0.081 0.087 0.088 0.000
EEC2 0.055 0.019 0.034 -0.008 0.042 0.026 -0.044 0.000
EEC3 -0.017 -0.084 -0.014 -0.041 -0.013 -0.001 0.006 0.004 0.000
TR1 0.018 -0.012 0.042 0.020 -0.006 0.028 0.067 0.038 0.065 0.000
TR2 0.004 -0.035 -0.012 -0.034 -0.053 0.012 -0.048 -0.057 -0.014 0.002
TR3 -0.008 -0.026 0.021 0.033 0.002 0.070 0.016 -0.046 0.010 -0.007
ADT1 0.107 -0.008 0.028 0.084 0.078 0.066 0.053 0.042 0.063 0.047
ADT2 -0.058 -0.146 -0.080 -0.047 -0.085 -0.055 -0.016 -0.047 -0.036 0.007
ADT3 0.013 -0.068 -0.025 0.039 -0.008 -0.010 0.005 0.015 -0.021 0.016
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.002 0.000
ADT1 0.007 0.029 0.000
ADT2 -0.028 -0.015 -0.001 0.000
ADT3 -0.040 0.043 -0.010 0.008 0.000
$cov.z
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.019 0.000
IM3 -0.060 0.000 0.000
EEF1 -0.659 -1.387 -0.827 0.000
EEF2 0.472 1.046 0.717 0.077 0.000
EEF3 0.046 0.329 1.514 0.172 -0.242 0.000
EEC1 0.882 1.912 2.204 1.416 1.641 1.575 0.000
EEC2 1.496 0.407 0.512 -0.198 1.233 0.672 -1.207 0.000
EEC3 -0.525 -1.788 -0.199 -1.220 -0.387 -0.038 0.164 0.113 0.000
TR1 0.433 -0.269 0.507 0.476 -0.160 0.616 1.147 0.808 1.576 0.000
TR2 0.127 -0.765 -0.197 -0.912 -1.632 0.309 -0.868 -1.369 -0.644 0.085
TR3 -0.206 -0.556 0.271 0.914 0.048 1.604 0.291 -1.038 0.356 -0.270
ADT1 2.507 -0.166 0.536 1.862 1.776 1.587 0.977 0.912 2.150 0.988
ADT2 -1.572 -2.719 -1.291 -1.251 -2.166 -1.546 -0.303 -1.078 -1.381 0.180
ADT3 0.356 -1.466 -0.356 0.862 -0.181 -0.236 0.107 0.325 -0.634 0.395
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.075 0.000
ADT1 0.190 0.669 0.000
ADT2 -0.942 -0.433 -0.026 0.000
ADT3 -1.068 1.176 -0.443 0.380 0.000
$summary
cov
srmr 0.046
srmr.se 0.009
srmr.exactfit.z 0.201
srmr.exactfit.pvalue 0.420
usrmr 0.009
usrmr.se 0.011
usrmr.ci.lower -0.008
usrmr.ci.upper 0.027
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -3.758
usrmr.closefit.pvalue 1.000 IM EEF EEC TR ADT
IM 1.000
EEF 0.621 1.000
EEC 0.461 0.594 1.000
TR 0.223 0.269 0.294 1.000
ADT 0.192 0.288 0.325 0.477 1.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC TR ADT
IM "1" "0.62 (0)" "0.46 (0)" "0.22 (0.004)" "0.19 (0.02)"
EEF "0.62 (0)" "1" "0.59 (0)" "0.27 (0)" "0.29 (0)"
EEC "0.46 (0)" "0.59 (0)" "1" "0.29 (0)" "0.32 (0)"
TR "0.22 (0.004)" "0.27 (0)" "0.29 (0)" "1" "0.48 (0)"
ADT "0.19 (0.02)" "0.29 (0)" "0.32 (0)" "0.48 (0)" "1" Details
Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
56 IM =~ ADT1 10.808 0.162 0.151 0.153 0.153
136 IM3 ~~ EEC1 12.161 0.162 0.162 0.234 0.234Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 12.161 0.162 0.162 0.234 0.234$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.001 0.000
IM3 -0.003 0.000 0.000
EEF1 -0.030 -0.057 -0.044 0.000
EEF2 0.020 0.045 0.042 0.003 0.000
EEF3 0.002 0.013 0.066 0.007 -0.010 0.000
EEC1 0.066 0.112 0.267 0.112 0.122 0.119 0.000
EEC2 0.074 0.021 0.045 -0.012 0.066 0.038 -0.076 0.000
EEC3 -0.022 -0.091 -0.017 -0.059 -0.020 -0.002 0.009 0.007 0.000
TR1 0.026 -0.014 0.059 0.033 -0.010 0.045 0.123 0.076 0.125 0.000
TR2 0.006 -0.044 -0.018 -0.056 -0.089 0.020 -0.091 -0.117 -0.028 0.004
TR3 -0.011 -0.032 0.031 0.055 0.003 0.112 0.030 -0.094 0.020 -0.015
ADT1 0.104 -0.007 0.026 0.092 0.087 0.070 0.066 0.058 0.081 0.068
ADT2 -0.056 -0.119 -0.076 -0.052 -0.094 -0.058 -0.020 -0.063 -0.047 0.010
ADT3 0.014 -0.060 -0.026 0.047 -0.010 -0.011 0.007 0.022 -0.030 0.026
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.004 0.000
ADT1 0.011 0.042 0.000
ADT2 -0.041 -0.023 -0.001 0.000
ADT3 -0.065 0.068 -0.011 0.009 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.019 0.000
IM3 -0.060 0.000 0.000
EEF1 -0.659 -1.387 -0.827 0.000
EEF2 0.472 1.046 0.717 0.077 0.000
EEF3 0.046 0.329 1.514 0.172 -0.242 0.000
EEC1 0.882 1.912 2.204 1.416 1.641 1.575 0.000
EEC2 1.496 0.407 0.512 -0.198 1.233 0.672 -1.207 0.000
EEC3 -0.525 -1.788 -0.199 -1.220 -0.387 -0.038 0.164 0.113 0.000
TR1 0.433 -0.269 0.507 0.476 -0.160 0.616 1.147 0.808 1.576 0.000
TR2 0.127 -0.765 -0.197 -0.912 -1.632 0.309 -0.868 -1.369 -0.644 0.085
TR3 -0.206 -0.556 0.271 0.914 0.048 1.604 0.291 -1.038 0.356 -0.270
ADT1 2.507 -0.166 0.536 1.862 1.776 1.587 0.977 0.912 2.150 0.988
ADT2 -1.572 -2.719 -1.291 -1.251 -2.166 -1.546 -0.303 -1.078 -1.381 0.180
ADT3 0.356 -1.466 -0.356 0.862 -0.181 -0.236 0.107 0.325 -0.634 0.395
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.075 0.000
ADT1 0.190 0.669 0.000
ADT2 -0.942 -0.433 -0.026 0.000
ADT3 -1.068 1.176 -0.443 0.380 0.000Modified model with moderation
lavaan 0.6-21 ended normally after 48 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 126.752 111.960
Degrees of freedom 79 79
P-value (Chi-square) 0.001 0.009
Scaling correction factor 1.132
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2333.038 1629.863
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.431
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.979 0.978
Tucker-Lewis Index (TLI) 0.972 0.971
Robust Comparative Fit Index (CFI) 0.983
Robust Tucker-Lewis Index (TLI) 0.977
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3570.393 -3570.393
Scaling correction factor 1.897
for the MLR correction
Loglikelihood unrestricted model (H1) -3507.017 -3507.017
Scaling correction factor 1.394
for the MLR correction
Akaike (AIC) 7222.787 7222.787
Bayesian (BIC) 7358.018 7358.018
Sample-size adjusted Bayesian (SABIC) 7228.126 7228.126
Root Mean Square Error of Approximation:
RMSEA 0.055 0.046
90 Percent confidence interval - lower 0.036 0.025
90 Percent confidence interval - upper 0.072 0.063
P-value H_0: RMSEA <= 0.050 0.308 0.638
P-value H_0: RMSEA >= 0.080 0.007 0.000
Robust RMSEA 0.049
90 Percent confidence interval - lower 0.025
90 Percent confidence interval - upper 0.068
P-value H_0: Robust RMSEA <= 0.050 0.526
P-value H_0: Robust RMSEA >= 0.080 0.003
Standardized Root Mean Square Residual:
SRMR 0.046 0.046
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
IM =~
IM1 1.000 1.000 1.000
IM2 0.649 0.120 5.392 0.000 0.413 0.885
IM3 0.619 0.126 4.893 0.000 0.371 0.867
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.031 0.066 15.735 0.000 0.903 1.160
EEF3 0.963 0.051 18.818 0.000 0.863 1.063
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.342 0.134 10.025 0.000 1.079 1.604
EEC3 1.422 0.115 12.337 0.000 1.196 1.648
TR =~
TR1 1.000 1.000 1.000
TR2 1.098 0.052 20.936 0.000 0.995 1.201
TR3 1.061 0.054 19.501 0.000 0.954 1.167
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.030 0.085 12.175 0.000 0.864 1.196
ADT3 1.076 0.080 13.420 0.000 0.919 1.234
Std.lv Std.all
0.931 0.946
0.604 0.734
0.576 0.602
0.997 0.902
1.028 0.917
0.960 0.893
0.876 0.696
1.175 0.853
1.245 0.950
1.287 0.881
1.413 0.942
1.365 0.915
0.851 0.861
0.877 0.890
0.916 0.854
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM2 ~~
.IM3 0.173 0.074 2.343 0.019 0.028 0.317
IM ~~
EEF 0.576 0.095 6.049 0.000 0.389 0.763
EEC 0.376 0.079 4.773 0.000 0.221 0.530
TR 0.267 0.103 2.602 0.009 0.066 0.468
ADT 0.152 0.075 2.030 0.042 0.005 0.299
EEF ~~
EEC 0.519 0.103 5.056 0.000 0.318 0.720
TR 0.346 0.109 3.181 0.001 0.133 0.559
ADT 0.244 0.074 3.307 0.001 0.100 0.389
EEC ~~
TR 0.331 0.094 3.522 0.000 0.147 0.515
ADT 0.242 0.069 3.523 0.000 0.107 0.377
TR ~~
ADT 0.523 0.094 5.533 0.000 0.337 0.708
Std.lv Std.all
0.173 0.404
0.621 0.621
0.461 0.461
0.223 0.223
0.192 0.192
0.594 0.594
0.269 0.269
0.288 0.288
0.294 0.294
0.325 0.325
0.477 0.477
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.101 0.093 1.087 0.277 -0.081 0.284
.IM2 0.313 0.087 3.601 0.000 0.143 0.483
.IM3 0.585 0.193 3.024 0.002 0.206 0.964
.EEF1 0.229 0.046 5.009 0.000 0.139 0.319
.EEF2 0.201 0.048 4.190 0.000 0.107 0.296
.EEF3 0.233 0.064 3.622 0.000 0.107 0.360
.EEC1 0.816 0.097 8.389 0.000 0.626 1.007
.EEC2 0.516 0.113 4.553 0.000 0.294 0.738
.EEC3 0.167 0.066 2.539 0.011 0.038 0.297
.TR1 0.477 0.086 5.557 0.000 0.309 0.645
.TR2 0.253 0.064 3.931 0.000 0.127 0.380
.TR3 0.365 0.095 3.856 0.000 0.179 0.550
.ADT1 0.254 0.061 4.166 0.000 0.134 0.373
.ADT2 0.202 0.056 3.621 0.000 0.093 0.311
.ADT3 0.313 0.092 3.392 0.001 0.132 0.493
IM 0.867 0.155 5.586 0.000 0.563 1.171
EEF 0.994 0.175 5.667 0.000 0.650 1.338
EEC 0.767 0.136 5.645 0.000 0.500 1.033
TR 1.657 0.178 9.315 0.000 1.309 2.006
ADT 0.724 0.097 7.450 0.000 0.534 0.915
Std.lv Std.all
0.101 0.105
0.313 0.462
0.585 0.638
0.229 0.187
0.201 0.160
0.233 0.202
0.816 0.516
0.516 0.272
0.167 0.097
0.477 0.223
0.253 0.113
0.365 0.164
0.254 0.259
0.202 0.208
0.313 0.271
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.895
IM2 0.538
IM3 0.362
EEF1 0.813
EEF2 0.840
EEF3 0.798
EEC1 0.484
EEC2 0.728
EEC3 0.903
TR1 0.777
TR2 0.887
TR3 0.836
ADT1 0.741
ADT2 0.792
ADT3 0.729Cronbach’s Alpha: IM EEF EEC TR ADT
0.837 0.930 0.863 0.937 0.900 Omega: IM EEF EEC TR ADT
0.769 0.931 0.887 0.939 0.902 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.610 0.818 0.711 0.834 0.752 Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
56 IM =~ ADT1 10.808 0.162 0.151 0.153 0.153
136 IM3 ~~ EEC1 12.161 0.162 0.162 0.234 0.234Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
136 IM3 ~~ EEC1 12.161 0.162 0.162 0.234 0.234$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.001 0.000
IM3 -0.003 0.000 0.000
EEF1 -0.030 -0.057 -0.044 0.000
EEF2 0.020 0.045 0.042 0.003 0.000
EEF3 0.002 0.013 0.066 0.007 -0.010 0.000
EEC1 0.066 0.112 0.267 0.112 0.122 0.119 0.000
EEC2 0.074 0.021 0.045 -0.012 0.066 0.038 -0.076 0.000
EEC3 -0.022 -0.091 -0.017 -0.059 -0.020 -0.002 0.009 0.007 0.000
TR1 0.026 -0.014 0.059 0.033 -0.010 0.045 0.123 0.076 0.125 0.000
TR2 0.006 -0.044 -0.018 -0.056 -0.089 0.020 -0.091 -0.117 -0.028 0.004
TR3 -0.011 -0.032 0.031 0.055 0.003 0.112 0.030 -0.094 0.020 -0.015
ADT1 0.104 -0.007 0.026 0.092 0.087 0.070 0.066 0.058 0.081 0.068
ADT2 -0.056 -0.119 -0.076 -0.052 -0.094 -0.058 -0.020 -0.063 -0.047 0.010
ADT3 0.014 -0.060 -0.026 0.047 -0.010 -0.011 0.007 0.022 -0.030 0.026
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.004 0.000
ADT1 0.011 0.042 0.000
ADT2 -0.041 -0.023 -0.001 0.000
ADT3 -0.065 0.068 -0.011 0.009 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 0.019 0.000
IM3 -0.060 0.000 0.000
EEF1 -0.659 -1.387 -0.827 0.000
EEF2 0.472 1.046 0.717 0.077 0.000
EEF3 0.046 0.329 1.514 0.172 -0.242 0.000
EEC1 0.882 1.912 2.204 1.416 1.641 1.575 0.000
EEC2 1.496 0.407 0.512 -0.198 1.233 0.672 -1.207 0.000
EEC3 -0.525 -1.788 -0.199 -1.220 -0.387 -0.038 0.164 0.113 0.000
TR1 0.433 -0.269 0.507 0.476 -0.160 0.616 1.147 0.808 1.576 0.000
TR2 0.127 -0.765 -0.197 -0.912 -1.632 0.309 -0.868 -1.369 -0.644 0.085
TR3 -0.206 -0.556 0.271 0.914 0.048 1.604 0.291 -1.038 0.356 -0.270
ADT1 2.507 -0.166 0.536 1.862 1.776 1.587 0.977 0.912 2.150 0.988
ADT2 -1.572 -2.719 -1.291 -1.251 -2.166 -1.546 -0.303 -1.078 -1.381 0.180
ADT3 0.356 -1.466 -0.356 0.862 -0.181 -0.236 0.107 0.325 -0.634 0.395
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.075 0.000
ADT1 0.190 0.669 0.000
ADT2 -0.942 -0.433 -0.026 0.000
ADT3 -1.068 1.176 -0.443 0.380 0.000ADT group
lavaan 0.6-21 ended normally after 84 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 108
0 92
Model Test User Model:
Standard Scaled
Test Statistic 236.062 243.417
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.000
Scaling correction factor 0.970
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 116.631 116.631
0 126.786 126.786
Model Test Baseline Model:
Test statistic 2091.765 1665.496
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.256
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.959 0.941
Tucker-Lewis Index (TLI) 0.945 0.922
Robust Comparative Fit Index (CFI) 0.955
Robust Tucker-Lewis Index (TLI) 0.940
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3401.549 -3401.549
Scaling correction factor 1.569
for the MLR correction
Loglikelihood unrestricted model (H1) -3283.519 -3283.519
Scaling correction factor 1.218
for the MLR correction
Akaike (AIC) 7027.099 7027.099
Bayesian (BIC) 7396.510 7396.510
Sample-size adjusted Bayesian (SABIC) 7041.683 7041.683
Root Mean Square Error of Approximation:
RMSEA 0.070 0.074
90 Percent confidence interval - lower 0.051 0.054
90 Percent confidence interval - upper 0.088 0.092
P-value H_0: RMSEA <= 0.050 0.044 0.024
P-value H_0: RMSEA >= 0.080 0.197 0.290
Robust RMSEA 0.072
90 Percent confidence interval - lower 0.054
90 Percent confidence interval - upper 0.090
P-value H_0: Robust RMSEA <= 0.050 0.026
P-value H_0: Robust RMSEA >= 0.080 0.248
Standardized Root Mean Square Residual:
SRMR 0.067 0.067
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 0.848 0.905
IM2 0.787 0.095 8.318 0.000 0.667 0.820
IM3 0.653 0.148 4.405 0.000 0.554 0.535
EEF =~
EEF1 1.000 0.880 0.901
EEF2 1.059 0.069 15.370 0.000 0.931 0.912
EEF3 0.942 0.071 13.295 0.000 0.828 0.862
EEC =~
EEC1 1.000 0.956 0.735
EEC2 1.154 0.130 8.883 0.000 1.104 0.834
EEC3 1.260 0.122 10.367 0.000 1.205 0.932
TR =~
TR1 1.000 1.288 0.876
TR2 1.067 0.076 14.125 0.000 1.374 0.928
TR3 1.050 0.079 13.236 0.000 1.352 0.898
ADT =~
ADT1 1.000 0.415 0.702
ADT2 1.295 0.283 4.584 0.000 0.537 0.893
ADT3 1.020 0.248 4.110 0.000 0.423 0.652
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.138 0.060 2.281 0.023 0.138 0.339
IM ~~
EEF 0.472 0.089 5.297 0.000 0.633 0.633
EEC 0.367 0.098 3.739 0.000 0.453 0.453
TR 0.290 0.130 2.231 0.026 0.266 0.266
ADT 0.024 0.048 0.505 0.613 0.069 0.069
EEF ~~
EEC 0.523 0.121 4.312 0.000 0.622 0.622
TR 0.365 0.126 2.901 0.004 0.322 0.322
ADT 0.076 0.051 1.478 0.139 0.208 0.208
EEC ~~
TR 0.418 0.122 3.422 0.001 0.339 0.339
ADT 0.089 0.050 1.782 0.075 0.224 0.224
TR ~~
ADT 0.244 0.076 3.205 0.001 0.457 0.457
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.463 0.090 60.580 0.000 5.463 5.829
.IM2 5.880 0.078 75.131 0.000 5.880 7.229
.IM3 5.676 0.100 57.000 0.000 5.676 5.485
.EEF1 5.639 0.094 60.031 0.000 5.639 5.776
.EEF2 5.778 0.098 58.788 0.000 5.778 5.657
.EEF3 5.824 0.092 63.008 0.000 5.824 6.063
.EEC1 4.565 0.125 36.489 0.000 4.565 3.511
.EEC2 4.731 0.127 37.149 0.000 4.731 3.575
.EEC3 4.778 0.124 38.389 0.000 4.778 3.694
.TR1 4.278 0.142 30.223 0.000 4.278 2.908
.TR2 4.222 0.142 29.641 0.000 4.222 2.852
.TR3 3.972 0.145 27.412 0.000 3.972 2.638
.ADT1 6.148 0.057 108.244 0.000 6.148 10.416
.ADT2 6.093 0.058 105.264 0.000 6.093 10.129
.ADT3 6.120 0.062 98.063 0.000 6.120 9.436
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.160 0.080 1.998 0.046 0.160 0.182
.IM2 0.217 0.057 3.824 0.000 0.217 0.328
.IM3 0.764 0.336 2.275 0.023 0.764 0.713
.EEF1 0.179 0.059 3.047 0.002 0.179 0.188
.EEF2 0.176 0.063 2.791 0.005 0.176 0.168
.EEF3 0.236 0.074 3.193 0.001 0.236 0.256
.EEC1 0.776 0.150 5.161 0.000 0.776 0.459
.EEC2 0.534 0.145 3.690 0.000 0.534 0.305
.EEC3 0.221 0.102 2.177 0.029 0.221 0.132
.TR1 0.505 0.133 3.790 0.000 0.505 0.233
.TR2 0.303 0.094 3.220 0.001 0.303 0.138
.TR3 0.439 0.165 2.658 0.008 0.439 0.194
.ADT1 0.177 0.050 3.539 0.000 0.177 0.507
.ADT2 0.073 0.061 1.207 0.228 0.073 0.203
.ADT3 0.242 0.051 4.748 0.000 0.242 0.575
IM 0.719 0.121 5.940 0.000 1.000 1.000
EEF 0.774 0.163 4.745 0.000 1.000 1.000
EEC 0.914 0.182 5.033 0.000 1.000 1.000
TR 1.659 0.256 6.488 0.000 1.000 1.000
ADT 0.172 0.054 3.174 0.002 1.000 1.000
Group 2 [0]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM =~
IM1 1.000 0.913 0.913
IM2 0.626 0.197 3.180 0.001 0.572 0.689
IM3 0.701 0.228 3.079 0.002 0.640 0.751
EEF =~
EEF1 1.000 1.028 0.883
EEF2 1.032 0.100 10.296 0.000 1.061 0.911
EEF3 0.995 0.084 11.811 0.000 1.023 0.911
EEC =~
EEC1 1.000 0.701 0.610
EEC2 1.583 0.339 4.673 0.000 1.111 0.840
EEC3 1.701 0.281 6.062 0.000 1.193 0.976
TR =~
TR1 1.000 1.087 0.848
TR2 1.222 0.102 11.963 0.000 1.329 0.965
TR3 1.085 0.091 11.927 0.000 1.180 0.906
ADT =~
ADT1 1.000 0.597 0.852
ADT2 0.412 1.548 0.266 0.790 0.246 0.355
ADT3 0.466 1.595 0.292 0.770 0.278 0.373
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.161 0.133 1.215 0.225 0.161 0.477
IM ~~
EEF 0.589 0.150 3.935 0.000 0.628 0.628
EEC 0.273 0.122 2.235 0.025 0.426 0.426
TR 0.059 0.136 0.433 0.665 0.059 0.059
ADT 0.107 0.356 0.299 0.765 0.196 0.196
EEF ~~
EEC 0.342 0.147 2.322 0.020 0.475 0.475
TR 0.040 0.134 0.302 0.763 0.036 0.036
ADT 0.043 0.251 0.170 0.865 0.070 0.070
EEC ~~
TR 0.034 0.097 0.350 0.726 0.045 0.045
ADT 0.079 0.230 0.343 0.731 0.188 0.188
TR ~~
ADT 0.168 0.162 1.039 0.299 0.260 0.260
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.098 0.104 48.865 0.000 5.098 5.095
.IM2 5.750 0.086 66.516 0.000 5.750 6.935
.IM3 5.543 0.089 62.387 0.000 5.543 6.504
.EEF1 5.054 0.121 41.636 0.000 5.054 4.341
.EEF2 5.239 0.121 43.156 0.000 5.239 4.499
.EEF3 5.272 0.117 44.991 0.000 5.272 4.691
.EEC1 4.065 0.120 33.915 0.000 4.065 3.536
.EEC2 3.967 0.138 28.775 0.000 3.967 3.000
.EEC3 4.065 0.128 31.882 0.000 4.065 3.324
.TR1 3.359 0.134 25.132 0.000 3.359 2.620
.TR2 3.337 0.144 23.237 0.000 3.337 2.423
.TR3 3.022 0.136 22.261 0.000 3.022 2.321
.ADT1 4.641 0.073 63.538 0.000 4.641 6.624
.ADT2 4.598 0.072 63.683 0.000 4.598 6.639
.ADT3 4.478 0.078 57.716 0.000 4.478 6.017
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.167 0.151 1.104 0.269 0.167 0.167
.IM2 0.361 0.141 2.555 0.011 0.361 0.525
.IM3 0.317 0.136 2.333 0.020 0.317 0.436
.EEF1 0.298 0.072 4.163 0.000 0.298 0.220
.EEF2 0.230 0.069 3.317 0.001 0.230 0.169
.EEF3 0.216 0.117 1.849 0.064 0.216 0.171
.EEC1 0.830 0.112 7.429 0.000 0.830 0.628
.EEC2 0.515 0.201 2.557 0.011 0.515 0.295
.EEC3 0.072 0.106 0.674 0.500 0.072 0.048
.TR1 0.462 0.096 4.786 0.000 0.462 0.281
.TR2 0.132 0.070 1.888 0.059 0.132 0.070
.TR3 0.304 0.088 3.434 0.001 0.304 0.179
.ADT1 0.135 1.059 0.127 0.899 0.135 0.275
.ADT2 0.419 0.286 1.466 0.143 0.419 0.874
.ADT3 0.477 0.336 1.417 0.156 0.477 0.861
IM 0.834 0.248 3.359 0.001 1.000 1.000
EEF 1.057 0.287 3.689 0.000 1.000 1.000
EEC 0.492 0.189 2.609 0.009 1.000 1.000
TR 1.181 0.215 5.505 0.000 1.000 1.000
ADT 0.356 1.068 0.333 0.739 1.000 1.000Trust group
lavaan 0.6-21 ended normally after 65 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 112
Number of observations per group:
1 89
0 111
Model Test User Model:
Standard Scaled
Test Statistic 254.081 261.482
Degrees of freedom 158 158
P-value (Chi-square) 0.000 0.000
Scaling correction factor 0.972
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
1 156.672 156.672
0 104.810 104.810
Model Test Baseline Model:
Test statistic 2025.174 1609.171
Degrees of freedom 210 210
P-value 0.000 0.000
Scaling correction factor 1.259
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.947 0.926
Tucker-Lewis Index (TLI) 0.930 0.902
Robust Comparative Fit Index (CFI) 0.943
Robust Tucker-Lewis Index (TLI) 0.924
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3385.373 -3385.373
Scaling correction factor 1.573
for the MLR correction
Loglikelihood unrestricted model (H1) -3258.332 -3258.332
Scaling correction factor 1.221
for the MLR correction
Akaike (AIC) 6994.745 6994.745
Bayesian (BIC) 7364.157 7364.157
Sample-size adjusted Bayesian (SABIC) 7009.329 7009.329
Root Mean Square Error of Approximation:
RMSEA 0.078 0.081
90 Percent confidence interval - lower 0.060 0.063
90 Percent confidence interval - upper 0.095 0.098
P-value H_0: RMSEA <= 0.050 0.008 0.004
P-value H_0: RMSEA >= 0.080 0.438 0.547
Robust RMSEA 0.080
90 Percent confidence interval - lower 0.062
90 Percent confidence interval - upper 0.097
P-value H_0: Robust RMSEA <= 0.050 0.004
P-value H_0: Robust RMSEA >= 0.080 0.504
Standardized Root Mean Square Residual:
SRMR 0.068 0.068
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 0.883 0.934
IM2 0.775 0.098 7.876 0.000 0.685 0.833
IM3 0.736 0.124 5.935 0.000 0.650 0.677
EEF =~
EEF1 1.000 0.858 0.897
EEF2 1.034 0.086 11.960 0.000 0.887 0.877
EEF3 0.860 0.099 8.653 0.000 0.738 0.829
EEC =~
EEC1 1.000 0.837 0.727
EEC2 1.295 0.190 6.826 0.000 1.083 0.829
EEC3 1.353 0.168 8.040 0.000 1.133 0.908
TR =~
TR1 1.000 0.297 0.375
TR2 1.429 0.477 2.995 0.003 0.424 0.736
TR3 1.982 0.733 2.704 0.007 0.588 0.808
ADT =~
ADT1 1.000 0.906 0.927
ADT2 0.913 0.091 10.077 0.000 0.828 0.909
ADT3 0.933 0.077 12.121 0.000 0.846 0.814
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.088 0.053 1.658 0.097 0.088 0.276
IM ~~
EEF 0.554 0.091 6.078 0.000 0.731 0.731
EEC 0.337 0.116 2.897 0.004 0.456 0.456
TR 0.017 0.044 0.394 0.693 0.067 0.067
ADT 0.193 0.116 1.666 0.096 0.241 0.241
EEF ~~
EEC 0.400 0.090 4.421 0.000 0.556 0.556
TR 0.042 0.040 1.058 0.290 0.165 0.165
ADT 0.249 0.097 2.560 0.010 0.320 0.320
EEC ~~
TR 0.035 0.044 0.796 0.426 0.142 0.142
ADT 0.269 0.093 2.893 0.004 0.355 0.355
TR ~~
ADT 0.106 0.059 1.789 0.074 0.395 0.395
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.416 0.100 54.018 0.000 5.416 5.726
.IM2 5.899 0.087 67.726 0.000 5.899 7.179
.IM3 5.719 0.102 56.217 0.000 5.719 5.959
.EEF1 5.596 0.101 55.184 0.000 5.596 5.850
.EEF2 5.742 0.107 53.551 0.000 5.742 5.676
.EEF3 5.831 0.094 61.824 0.000 5.831 6.553
.EEC1 4.573 0.122 37.503 0.000 4.573 3.975
.EEC2 4.719 0.139 34.069 0.000 4.719 3.611
.EEC3 4.798 0.132 36.301 0.000 4.798 3.848
.TR1 5.124 0.084 61.132 0.000 5.124 6.480
.TR2 5.225 0.061 85.605 0.000 5.225 9.074
.TR3 4.820 0.077 62.494 0.000 4.820 6.624
.ADT1 5.820 0.104 56.144 0.000 5.820 5.951
.ADT2 5.809 0.096 60.201 0.000 5.809 6.381
.ADT3 5.764 0.110 52.346 0.000 5.764 5.549
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.114 0.080 1.428 0.153 0.114 0.128
.IM2 0.206 0.048 4.283 0.000 0.206 0.306
.IM3 0.499 0.205 2.429 0.015 0.499 0.541
.EEF1 0.178 0.067 2.663 0.008 0.178 0.195
.EEF2 0.236 0.071 3.343 0.001 0.236 0.230
.EEF3 0.247 0.087 2.828 0.005 0.247 0.312
.EEC1 0.623 0.124 5.045 0.000 0.623 0.471
.EEC2 0.534 0.169 3.161 0.002 0.534 0.313
.EEC3 0.272 0.115 2.360 0.018 0.272 0.175
.TR1 0.537 0.134 4.006 0.000 0.537 0.859
.TR2 0.152 0.043 3.497 0.000 0.152 0.458
.TR3 0.184 0.104 1.761 0.078 0.184 0.348
.ADT1 0.135 0.060 2.267 0.023 0.135 0.141
.ADT2 0.143 0.060 2.395 0.017 0.143 0.173
.ADT3 0.364 0.179 2.036 0.042 0.364 0.337
IM 0.780 0.134 5.835 0.000 1.000 1.000
EEF 0.737 0.123 6.003 0.000 1.000 1.000
EEC 0.700 0.160 4.387 0.000 1.000 1.000
TR 0.088 0.065 1.354 0.176 1.000 1.000
ADT 0.822 0.158 5.205 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 0.925 0.923
IM2 0.600 0.178 3.363 0.001 0.555 0.678
IM3 0.573 0.210 2.722 0.006 0.530 0.559
EEF =~
EEF1 1.000 1.057 0.894
EEF2 1.046 0.083 12.551 0.000 1.105 0.939
EEF3 1.011 0.059 17.085 0.000 1.068 0.920
EEC =~
EEC1 1.000 0.862 0.660
EEC2 1.357 0.210 6.465 0.000 1.171 0.854
EEC3 1.461 0.175 8.353 0.000 1.260 0.974
TR =~
TR1 1.000 0.780 0.773
TR2 0.995 0.119 8.335 0.000 0.776 0.809
TR3 1.092 0.135 8.086 0.000 0.852 0.776
ADT =~
ADT1 1.000 0.682 0.761
ADT2 1.132 0.162 6.974 0.000 0.772 0.838
ADT3 1.246 0.170 7.321 0.000 0.850 0.859
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.205 0.109 1.884 0.060 0.205 0.433
IM ~~
EEF 0.553 0.144 3.837 0.000 0.565 0.565
EEC 0.372 0.109 3.422 0.001 0.466 0.466
TR 0.237 0.096 2.462 0.014 0.329 0.329
ADT 0.041 0.077 0.537 0.591 0.066 0.066
EEF ~~
EEC 0.536 0.157 3.412 0.001 0.588 0.588
TR 0.150 0.090 1.665 0.096 0.182 0.182
ADT 0.118 0.083 1.415 0.157 0.163 0.163
EEC ~~
TR 0.090 0.080 1.125 0.260 0.134 0.134
ADT 0.099 0.076 1.292 0.196 0.168 0.168
TR ~~
ADT 0.118 0.066 1.780 0.075 0.222 0.222
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.198 0.095 54.609 0.000 5.198 5.183
.IM2 5.757 0.078 74.066 0.000 5.757 7.030
.IM3 5.532 0.090 61.511 0.000 5.532 5.838
.EEF1 5.189 0.112 46.261 0.000 5.189 4.391
.EEF2 5.360 0.112 48.011 0.000 5.360 4.557
.EEF3 5.360 0.110 48.649 0.000 5.360 4.618
.EEC1 4.144 0.124 33.399 0.000 4.144 3.170
.EEC2 4.108 0.130 31.565 0.000 4.108 2.996
.EEC3 4.171 0.123 33.972 0.000 4.171 3.224
.TR1 2.838 0.096 29.622 0.000 2.838 2.812
.TR2 2.685 0.091 29.512 0.000 2.685 2.801
.TR3 2.505 0.104 24.038 0.000 2.505 2.282
.ADT1 5.162 0.085 60.710 0.000 5.162 5.762
.ADT2 5.081 0.087 58.089 0.000 5.081 5.514
.ADT3 5.045 0.094 53.694 0.000 5.045 5.096
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.150 0.144 1.041 0.298 0.150 0.149
.IM2 0.363 0.126 2.875 0.004 0.363 0.541
.IM3 0.617 0.302 2.045 0.041 0.617 0.687
.EEF1 0.280 0.062 4.478 0.000 0.280 0.200
.EEF2 0.162 0.054 2.996 0.003 0.162 0.117
.EEF3 0.206 0.087 2.367 0.018 0.206 0.153
.EEC1 0.965 0.145 6.658 0.000 0.965 0.565
.EEC2 0.510 0.159 3.208 0.001 0.510 0.271
.EEC3 0.086 0.073 1.183 0.237 0.086 0.051
.TR1 0.411 0.100 4.096 0.000 0.411 0.403
.TR2 0.317 0.088 3.615 0.000 0.317 0.345
.TR3 0.479 0.159 3.023 0.002 0.479 0.398
.ADT1 0.337 0.090 3.751 0.000 0.337 0.420
.ADT2 0.253 0.086 2.928 0.003 0.253 0.298
.ADT3 0.257 0.081 3.196 0.001 0.257 0.263
IM 0.856 0.243 3.523 0.000 1.000 1.000
EEF 1.117 0.268 4.173 0.000 1.000 1.000
EEC 0.744 0.210 3.547 0.000 1.000 1.000
TR 0.608 0.119 5.107 0.000 1.000 1.000
ADT 0.465 0.113 4.134 0.000 1.000 1.000
Chi-Squared Difference Test
Df AIC BIC Chisq Chisq diff RMSEA Df diff Pr(>Chisq)
fit_config 158 6994.7 7364.2 254.08
fit_metric 168 6986.2 7322.6 265.51 11.4338 0.037866 10 0.3247
fit_scalar 178 6973.0 7276.4 272.30 6.7821 0.000000 10 0.7458 config metric scalar
chisq 254.08103369 265.51486855 272.29695138
df 158.00000000 168.00000000 178.00000000
cfi 0.94706787 0.94627796 0.94805074
rmsea 0.07798127 0.07618698 0.07278449
srmr 0.06776584 0.06818623 0.07072353<NA>
NA <NA>
NA <NA>
NA <NA>
NA lhs op rhs block group level mi epc sepc.lv sepc.all sepc.nox
238 IM3 ~~ ADT1 1 1 1 12.049 0.124 0.124 0.435 0.435
276 EEC1 ~~ ADT1 1 1 1 10.967 0.145 0.145 0.459 0.459
146 IM =~ EEC1 1 1 1 10.805 0.361 0.328 0.289 0.289
148 IM =~ EEC3 1 1 1 10.067 -0.336 -0.306 -0.244 -0.244SEM
Without control variables
No moderation - without PEB control variablelavaan 0.6-21 ended normally after 61 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 50
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 212.047 199.525
Degrees of freedom 145 145
P-value (Chi-square) 0.000 0.002
Scaling correction factor 1.063
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2400.847 1928.163
Degrees of freedom 180 180
P-value 0.000 0.000
Scaling correction factor 1.245
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.970 0.969
Tucker-Lewis Index (TLI) 0.963 0.961
Robust Comparative Fit Index (CFI) 0.973
Robust Tucker-Lewis Index (TLI) 0.967
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3579.137 -3579.137
Scaling correction factor 1.739
for the MLR correction
Loglikelihood unrestricted model (H1) -3473.113 -3473.113
Scaling correction factor 1.236
for the MLR correction
Akaike (AIC) 7258.273 7258.273
Bayesian (BIC) 7423.189 7423.189
Sample-size adjusted Bayesian (SABIC) 7264.784 7264.784
Root Mean Square Error of Approximation:
RMSEA 0.048 0.043
90 Percent confidence interval - lower 0.033 0.028
90 Percent confidence interval - upper 0.062 0.057
P-value H_0: RMSEA <= 0.050 0.577 0.775
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.045
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.059
P-value H_0: Robust RMSEA <= 0.050 0.710
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.112 0.112
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR =~
TR1 1.000 1.285 0.880
TR2 1.101 0.053 20.921 0.000 1.416 0.944
TR3 1.061 0.054 19.766 0.000 1.364 0.914
ADT =~
ADT1 1.000 0.845 0.855
ADT2 1.044 0.084 12.438 0.000 0.883 0.896
ADT3 1.084 0.079 13.686 0.000 0.916 0.853
IM =~
IM1 1.000 0.934 0.949
IM2 0.644 0.125 5.157 0.000 0.602 0.731
IM3 0.616 0.135 4.548 0.000 0.575 0.601
EEF =~
EEF1 1.000 0.997 0.901
EEF2 1.034 0.065 15.859 0.000 1.030 0.918
EEF3 0.962 0.051 19.007 0.000 0.959 0.892
EEC =~
EEC1 1.000 0.878 0.698
EEC2 1.347 0.136 9.872 0.000 1.183 0.859
EEC3 1.405 0.113 12.436 0.000 1.235 0.942
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.175 0.232 0.756 0.450 0.188 0.069
rwrd0_2 (b_02) 0.134 0.244 0.549 0.583 0.144 0.055
rwrd1_2 (b_12) 0.180 0.258 0.697 0.486 0.192 0.071
rwrd0_3 (b_03) 0.116 0.250 0.465 0.642 0.124 0.045
rwrd1_3 (b_13) -0.173 0.223 -0.776 0.438 -0.185 -0.068
EEF ~
rwrd1_1 (c_11) 0.230 0.185 1.243 0.214 0.231 0.085
rwrd0_2 (c_02) -0.108 0.209 -0.514 0.607 -0.108 -0.042
rwrd1_2 (c_12) 0.124 0.191 0.649 0.516 0.125 0.046
rwrd0_3 (c_03) -0.234 0.178 -1.317 0.188 -0.235 -0.085
rwrd1_3 (c_13) 0.041 0.185 0.223 0.824 0.041 0.015
IM (c_IM) 0.659 0.089 7.431 0.000 0.617 0.617
EEC ~
rwrd1_1 (d_11) 0.188 0.201 0.936 0.349 0.214 0.079
rwrd0_2 (d_02) 0.169 0.206 0.819 0.413 0.192 0.074
rwrd1_2 (d_12) 0.262 0.201 1.305 0.192 0.299 0.111
rwrd0_3 (d_03) 0.062 0.182 0.339 0.735 0.070 0.025
rwrd1_3 (d_13) 0.060 0.216 0.280 0.780 0.069 0.025
IM (d_IM) 0.429 0.078 5.536 0.000 0.456 0.456
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.175 0.075 2.320 0.020 0.175 0.406
TR ~~
ADT 0.516 0.093 5.521 0.000 0.475 0.475
.EEF ~~
.EEC 0.266 0.077 3.458 0.001 0.448 0.448
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.482 0.085 5.648 0.000 0.482 0.226
.TR2 0.247 0.065 3.812 0.000 0.247 0.110
.TR3 0.367 0.094 3.915 0.000 0.367 0.165
.ADT1 0.264 0.060 4.364 0.000 0.264 0.270
.ADT2 0.192 0.054 3.553 0.000 0.192 0.198
.ADT3 0.313 0.093 3.356 0.001 0.313 0.272
.IM1 0.096 0.102 0.936 0.349 0.096 0.099
.IM2 0.315 0.088 3.585 0.000 0.315 0.466
.IM3 0.586 0.198 2.960 0.003 0.586 0.639
.EEF1 0.230 0.046 5.001 0.000 0.230 0.188
.EEF2 0.198 0.047 4.177 0.000 0.198 0.157
.EEF3 0.236 0.064 3.666 0.000 0.236 0.205
.EEC1 0.811 0.097 8.348 0.000 0.811 0.512
.EEC2 0.495 0.113 4.364 0.000 0.495 0.261
.EEC3 0.193 0.067 2.905 0.004 0.193 0.113
TR 1.652 0.177 9.317 0.000 1.000 1.000
ADT 0.714 0.096 7.413 0.000 1.000 1.000
.IM 0.857 0.170 5.040 0.000 0.983 0.983
.EEF 0.591 0.136 4.332 0.000 0.595 0.595
.EEC 0.596 0.113 5.285 0.000 0.773 0.773
R-Square:
Estimate
TR1 0.774
TR2 0.890
TR3 0.835
ADT1 0.730
ADT2 0.802
ADT3 0.728
IM1 0.901
IM2 0.534
IM3 0.361
EEF1 0.812
EEF2 0.843
EEF3 0.795
EEC1 0.488
EEC2 0.739
EEC3 0.887
IM 0.017
EEF 0.405
EEC 0.227With control variables
All three (TR, ADT, PEB)
With control all three controlslavaan 0.6-21 ended normally after 61 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 59
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 197.139 187.119
Degrees of freedom 151 151
P-value (Chi-square) 0.007 0.024
Scaling correction factor 1.054
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2455.693 2006.578
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.224
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.980 0.980
Tucker-Lewis Index (TLI) 0.974 0.974
Robust Comparative Fit Index (CFI) 0.983
Robust Tucker-Lewis Index (TLI) 0.978
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3544.260 -3544.260
Scaling correction factor 1.635
for the MLR correction
Loglikelihood unrestricted model (H1) -3445.690 -3445.690
Scaling correction factor 1.217
for the MLR correction
Akaike (AIC) 7206.519 7206.519
Bayesian (BIC) 7401.120 7401.120
Sample-size adjusted Bayesian (SABIC) 7214.202 7214.202
Root Mean Square Error of Approximation:
RMSEA 0.039 0.035
90 Percent confidence interval - lower 0.021 0.014
90 Percent confidence interval - upper 0.054 0.049
P-value H_0: RMSEA <= 0.050 0.887 0.956
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.035
90 Percent confidence interval - lower 0.014
90 Percent confidence interval - upper 0.051
P-value H_0: Robust RMSEA <= 0.050 0.935
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.042 0.042
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 1.287 0.881
TR2 1.098 0.053 20.860 0.000 1.414 0.942
TR3 1.060 0.054 19.553 0.000 1.365 0.914
ADT =~
ADT1 1.000 0.852 0.861
ADT2 1.028 0.084 12.211 0.000 0.876 0.889
ADT3 1.076 0.080 13.468 0.000 0.917 0.854
IM =~
IM1 1.000 0.879 0.894
IM2 0.723 0.114 6.350 0.000 0.635 0.772
IM3 0.702 0.133 5.289 0.000 0.617 0.644
EEF =~
EEF1 1.000 0.998 0.902
EEF2 1.031 0.062 16.541 0.000 1.029 0.917
EEF3 0.961 0.050 19.078 0.000 0.959 0.892
EEC =~
EEC1 1.000 0.880 0.699
EEC2 1.343 0.135 9.962 0.000 1.181 0.857
EEC3 1.409 0.114 12.397 0.000 1.239 0.945
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.303 0.190 1.595 0.111 0.345 0.126
rwrd0_2 (b_02) 0.216 0.217 0.994 0.320 0.246 0.095
rwrd1_2 (b_12) 0.353 0.206 1.717 0.086 0.402 0.149
rwrd0_3 (b_03) 0.261 0.226 1.158 0.247 0.297 0.108
rwrd1_3 (b_13) -0.033 0.185 -0.178 0.858 -0.038 -0.014
TR (b_TR) 0.098 0.050 1.943 0.052 0.143 0.143
ADT (b_AD) 0.128 0.092 1.399 0.162 0.124 0.124
PEB_yes (b_PE) 0.903 0.136 6.656 0.000 1.027 0.425
EEF ~
rwrd1_1 (c_11) 0.203 0.186 1.093 0.274 0.204 0.075
rwrd0_2 (c_02) -0.109 0.194 -0.565 0.572 -0.110 -0.042
rwrd1_2 (c_12) 0.132 0.179 0.741 0.459 0.133 0.049
rwrd0_3 (c_03) -0.204 0.171 -1.194 0.233 -0.205 -0.074
rwrd1_3 (c_13) 0.058 0.185 0.316 0.752 0.059 0.021
IM (c_IM) 0.616 0.096 6.438 0.000 0.543 0.543
TR (c_TR) 0.045 0.054 0.844 0.399 0.058 0.058
ADT (c_AD) 0.199 0.084 2.373 0.018 0.170 0.170
PEB_yes (c_PE) 0.266 0.176 1.514 0.130 0.266 0.110
EEC ~
rwrd1_1 (d_11) 0.144 0.202 0.715 0.475 0.164 0.060
rwrd0_2 (d_02) 0.164 0.209 0.784 0.433 0.186 0.072
rwrd1_2 (d_12) 0.279 0.192 1.450 0.147 0.317 0.118
rwrd0_3 (d_03) 0.059 0.178 0.331 0.740 0.067 0.024
rwrd1_3 (d_13) 0.065 0.199 0.329 0.742 0.074 0.027
IM (d_IM) 0.385 0.097 3.945 0.000 0.384 0.384
TR (d_TR) 0.077 0.054 1.418 0.156 0.113 0.113
ADT (d_AD) 0.212 0.084 2.541 0.011 0.206 0.206
PEB_yes (d_PE) 0.052 0.163 0.320 0.749 0.059 0.024
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.128 0.066 1.935 0.053 0.128 0.335
TR ~~
ADT 0.523 0.095 5.535 0.000 0.477 0.477
.EEF ~~
.EEC 0.213 0.066 3.244 0.001 0.398 0.398
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.476 0.086 5.552 0.000 0.476 0.223
.TR2 0.253 0.065 3.885 0.000 0.253 0.112
.TR3 0.366 0.094 3.891 0.000 0.366 0.164
.ADT1 0.252 0.060 4.184 0.000 0.252 0.258
.ADT2 0.204 0.056 3.646 0.000 0.204 0.210
.ADT3 0.312 0.091 3.411 0.001 0.312 0.271
.IM1 0.193 0.072 2.686 0.007 0.193 0.200
.IM2 0.273 0.080 3.432 0.001 0.273 0.404
.IM3 0.535 0.200 2.681 0.007 0.535 0.585
.EEF1 0.228 0.045 5.010 0.000 0.228 0.186
.EEF2 0.200 0.046 4.352 0.000 0.200 0.159
.EEF3 0.235 0.064 3.662 0.000 0.235 0.204
.EEC1 0.811 0.097 8.386 0.000 0.811 0.512
.EEC2 0.503 0.112 4.482 0.000 0.503 0.265
.EEC3 0.185 0.066 2.815 0.005 0.185 0.107
TR 1.658 0.178 9.318 0.000 1.000 1.000
ADT 0.726 0.097 7.494 0.000 1.000 1.000
.IM 0.575 0.128 4.503 0.000 0.744 0.744
.EEF 0.528 0.113 4.680 0.000 0.530 0.530
.EEC 0.540 0.101 5.329 0.000 0.698 0.698
R-Square:
Estimate
TR1 0.777
TR2 0.888
TR3 0.836
ADT1 0.742
ADT2 0.790
ADT3 0.729
IM1 0.800
IM2 0.596
IM3 0.415
EEF1 0.814
EEF2 0.841
EEF3 0.796
EEC1 0.488
EEC2 0.735
EEC3 0.893
IM 0.256
EEF 0.470
EEC 0.302
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.303 0.190 1.595 0.111 0.345 0.126
reward2_IM 0.137 0.229 0.597 0.551 0.156 0.055
reward3_IM -0.294 0.229 -1.285 0.199 -0.335 -0.121
reward_vrgd_IM 0.048 0.133 0.366 0.714 0.055 0.020
reward_EEF_ec1 0.203 0.186 1.093 0.274 0.204 0.075
reward_EEF_ec2 0.242 0.210 1.149 0.251 0.242 0.091
reward_EEF_ec3 0.263 0.195 1.346 0.178 0.263 0.096
reward_man_EEF 0.236 0.114 2.062 0.039 0.237 0.087
ind_rwrd_EEF_1 0.187 0.124 1.505 0.132 0.187 0.069
ind_rwrd_EEF_2 0.084 0.139 0.608 0.543 0.085 0.030
ind_rwrd_EEF_3 -0.181 0.144 -1.259 0.208 -0.182 -0.066
ind_rw__IM_EEF 0.030 0.081 0.367 0.714 0.030 0.011
tt_rwrd_mn_EEF 0.266 0.128 2.072 0.038 0.266 0.098
reward_EEC_ec1 0.144 0.202 0.715 0.475 0.164 0.060
reward_EEC_ec2 0.115 0.197 0.581 0.561 0.130 0.046
reward_EEC_ec3 0.006 0.190 0.034 0.973 0.007 0.003
reward_man_EEC 0.088 0.113 0.786 0.432 0.101 0.036
ind_rwrd_EEC_1 0.116 0.081 1.433 0.152 0.132 0.049
ind_rwrd_EEC_2 0.053 0.088 0.595 0.552 0.060 0.021
ind_rwrd_EEC_3 -0.113 0.093 -1.223 0.221 -0.129 -0.047
ind_rw__IM_EEC 0.019 0.051 0.364 0.716 0.021 0.008
tt_rwrd_mn_EEC 0.107 0.119 0.900 0.368 0.122 0.044
eco2_vs_c1_EEF -0.090 0.142 -0.637 0.524 -0.090 -0.034
eco3_vs_c1_EEF -0.175 0.134 -1.306 0.191 -0.175 -0.064
eco1_vs_c2_EEF 0.090 0.142 0.637 0.524 0.090 0.034
eco_main_EEF -0.132 0.116 -1.138 0.255 -0.133 -0.049
eco2_vs_ec1_IM 0.133 0.143 0.934 0.350 0.152 0.059
eco3_vs_ec1_IM -0.037 0.145 -0.258 0.797 -0.043 -0.016
eco1_vs_ec2_IM -0.133 0.143 -0.934 0.350 -0.152 -0.059
in_1__2_IM_EEF -0.082 0.091 -0.905 0.366 -0.082 -0.032
in_2__1_IM_EEF 0.082 0.091 0.905 0.366 0.082 0.032
in_3__1_IM_EEF -0.023 0.089 -0.258 0.796 -0.023 -0.009
ind_c_m_IM_EEF 0.030 0.075 0.396 0.692 0.030 0.012
tt_c1_vs_2_EEF 0.008 0.152 0.053 0.958 0.008 0.002
tt_c2_vs_1_EEF -0.008 0.152 -0.053 0.958 -0.008 -0.002
tt_c3_vs_1_EEF -0.198 0.151 -1.312 0.190 -0.198 -0.073
tot_eco_mn_EEF -0.103 0.127 -0.810 0.418 -0.103 -0.037
eco2_vs_c1_EEC 0.149 0.146 1.018 0.309 0.170 0.065
eco3_vs_c1_EEC -0.010 0.134 -0.075 0.941 -0.011 -0.004
eco_main_EEC 0.070 0.123 0.567 0.571 0.079 0.030
in_2__1_IM_EEC 0.051 0.056 0.908 0.364 0.058 0.023
in_3__1_IM_EEC -0.014 0.056 -0.257 0.797 -0.016 -0.006
ind_c_m_IM_EEC 0.018 0.046 0.399 0.690 0.021 0.008
tt_c2_vs_1_EEC 0.200 0.156 1.287 0.198 0.228 0.087
tt_c3_vs_1_EEC -0.024 0.133 -0.184 0.854 -0.028 -0.011
tot_eco_mn_EEC 0.088 0.125 0.705 0.481 0.100 0.038
eco_main_IM 0.048 0.120 0.400 0.689 0.055 0.021
eco3_vs_c2_EEF -0.084 0.147 -0.573 0.566 -0.085 -0.030
in_3__2_IM_EEF -0.105 0.101 -1.043 0.297 -0.105 -0.041
tt_c3_vs_2_EEF -0.190 0.166 -1.144 0.252 -0.190 -0.071
eco3_vs_c2_EEC -0.159 0.137 -1.160 0.246 -0.181 -0.069
in_3__2_IM_EEC -0.066 0.064 -1.030 0.303 -0.075 -0.029
tt_c3_vs_2_EEC -0.225 0.146 -1.536 0.125 -0.255 -0.098
reward_IM_eco1 0.303 0.190 1.595 0.111 0.345 0.126
reward_IM_eco2 0.137 0.229 0.597 0.551 0.156 0.055
reward_IM_eco3 -0.294 0.229 -1.285 0.199 -0.335 -0.121
reward_main_IM 0.048 0.133 0.366 0.714 0.055 0.020
r_3_EEF___1_EE -0.145 0.205 -0.705 0.481 -0.145 -0.053
r_2_EEF___1_EE -0.071 0.203 -0.350 0.726 -0.071 -0.025
r_2_EEC___1_EE 0.134 0.198 0.679 0.497 0.153 0.057
r_3_EEC___2_EE -0.213 0.202 -1.055 0.291 -0.242 -0.090
r_3_EEC___1_EE -0.079 0.207 -0.381 0.703 -0.090 -0.033
rw_2_IM___1_IM 0.050 0.182 0.276 0.782 0.057 0.023
rw_3_IM___1_IM -0.336 0.184 -1.824 0.068 -0.382 -0.140
i__2_EEC___1_E 0.019 0.070 0.277 0.781 0.022 0.009
i__3_EEC___1_E -0.129 0.080 -1.622 0.105 -0.147 -0.054
i__3_EEC___2_E -0.149 0.083 -1.799 0.072 -0.169 -0.063
t__2_EEC___1_E 0.153 0.210 0.731 0.465 0.174 0.066
t__3_EEC___1_E -0.208 0.211 -0.988 0.323 -0.237 -0.087
t__3_EEC___2_E -0.362 0.210 -1.726 0.084 -0.411 -0.153
rwrd_c3_dr_EEF 0.263 0.195 1.346 0.178 0.263 0.096
rwrd_3__IM_EEF -0.181 0.144 -1.259 0.208 -0.182 -0.066
rwrd_c3_tt_EEF 0.081 0.227 0.358 0.720 0.082 0.030
rwrd_c3_dr_EEC 0.006 0.190 0.034 0.973 0.007 0.003
rwrd_3__IM_EEC -0.113 0.093 -1.223 0.221 -0.129 -0.047
rwrd_c3_tt_EEC -0.107 0.187 -0.571 0.568 -0.121 -0.044Mediation 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 0.236 0.114 2.061 0.039 0.007
97 ind_reward_main_IM_EEF 0.030 0.080 0.373 0.709 -0.130
98 tot_reward_main_EEF 0.266 0.132 2.017 0.044 -0.033
102 reward_main_EEC 0.088 0.113 0.786 0.432 -0.132
106 ind_reward_main_IM_EEC 0.019 0.051 0.367 0.713 -0.080
107 tot_reward_main_EEC 0.107 0.120 0.895 0.371 -0.121
109 eco3_vs_eco1_EEF -0.175 0.139 -1.257 0.209 -0.453
110 eco1_vs_eco2_EEF 0.090 0.144 0.625 0.532 -0.195
111 eco_main_EEF -0.132 0.119 -1.115 0.265 -0.371
112 eco2_vs_eco1_IM 0.133 0.145 0.916 0.360 -0.173
113 eco3_vs_eco1_IM -0.037 0.147 -0.254 0.799 -0.342
114 eco1_vs_eco2_IM -0.133 0.145 -0.916 0.360 -0.397
115 ind_eco1_vs_eco2_IM_EEF -0.082 0.092 -0.892 0.372 -0.274
117 ind_eco3_vs_eco1_IM_EEF -0.023 0.092 -0.252 0.801 -0.206
118 ind_eco_main_IM_EEF 0.030 0.076 0.389 0.697 -0.118
119 tot_eco1_vs_eco2_EEF 0.008 0.152 0.053 0.958 -0.296
121 tot_eco3_vs_eco1_EEF -0.198 0.156 -1.269 0.204 -0.510
122 tot_eco_main_EEF -0.103 0.127 -0.813 0.416 -0.372
123 eco2_vs_eco1_EEC 0.149 0.152 0.980 0.327 -0.136
124 eco3_vs_eco1_EEC -0.010 0.143 -0.070 0.944 -0.290
125 eco_main_EEC 0.070 0.130 0.534 0.594 -0.182
126 ind_eco2_vs_eco1_IM_EEC 0.051 0.059 0.867 0.386 -0.067
127 ind_eco3_vs_eco1_IM_EEC -0.014 0.059 -0.245 0.806 -0.146
128 ind_eco_main_IM_EEC 0.018 0.048 0.383 0.701 -0.077
129 tot_eco2_vs_eco1_EEC 0.200 0.156 1.287 0.198 -0.089
130 tot_eco3_vs_eco1_EEC -0.024 0.138 -0.177 0.860 -0.289
131 tot_eco_main_EEC 0.088 0.126 0.697 0.486 -0.163
132 eco_main_IM 0.048 0.121 0.397 0.692 -0.194
136 eco3_vs_eco2_EEC -0.159 0.139 -1.149 0.251 -0.443
137 ind_eco3_vs_eco2_IM_EEC -0.066 0.068 -0.968 0.333 -0.205
138 tot_eco3_vs_eco2_EEC -0.225 0.151 -1.491 0.136 -0.537
142 reward_main_IM 0.048 0.131 0.371 0.711 -0.217
143 reward_eco3_EEF_vs_reward_eco1_EEF -0.145 0.221 -0.654 0.513 -0.581
144 reward_eco2_EEF_vs_reward_eco1_EEF -0.071 0.206 -0.345 0.730 -0.476
145 reward_eco2_EEC_vs_reward_eco1_EEC 0.134 0.206 0.652 0.515 -0.274
146 reward_eco3_EEC_vs_reward_eco2_EEC -0.213 0.200 -1.065 0.287 -0.666
148 reward_eco2_IM_vs_reward_eco1_IM 0.050 0.190 0.265 0.791 -0.342
149 reward_eco3_IM_vs_reward_eco1_IM -0.336 0.200 -1.680 0.093 -0.699
150 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.019 0.075 0.258 0.796 -0.140
151 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.129 0.089 -1.458 0.145 -0.314
152 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.149 0.090 -1.644 0.100 -0.357
153 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.153 0.207 0.741 0.459 -0.268
154 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.208 0.214 -0.975 0.330 -0.648
155 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.362 0.203 -1.780 0.075 -0.821
156 reward_eco3_direct_EEF 0.263 0.201 1.306 0.192 -0.117
157 reward_eco3_ind_IM_EEF -0.181 0.147 -1.238 0.216 -0.484
158 reward_eco3_total_EEF 0.081 0.235 0.346 0.729 -0.392
159 reward_eco3_direct_EEC 0.006 0.196 0.033 0.974 -0.334
160 reward_eco3_ind_IM_EEC -0.113 0.098 -1.150 0.250 -0.319
161 reward_eco3_total_EEC -0.107 0.187 -0.572 0.567 -0.493
ci.upper std.lv std.all std.nox
93 0.453 0.237 0.087 0.237
97 0.172 0.030 0.011 0.030
98 0.526 0.266 0.098 0.266
102 0.315 0.101 0.036 0.101
106 0.114 0.021 0.008 0.021
107 0.331 0.122 0.044 0.122
109 0.082 -0.175 -0.064 -0.175
110 0.382 0.090 0.034 0.090
111 0.106 -0.133 -0.049 -0.133
112 0.397 0.152 0.059 0.152
113 0.253 -0.043 -0.016 -0.043
114 0.173 -0.152 -0.059 -0.152
115 0.103 -0.082 -0.032 -0.082
117 0.144 -0.023 -0.009 -0.023
118 0.187 0.030 0.012 0.030
119 0.292 0.008 0.002 0.008
121 0.096 -0.198 -0.073 -0.198
122 0.131 -0.103 -0.037 -0.103
123 0.493 0.170 0.065 0.170
124 0.285 -0.011 -0.004 -0.011
125 0.349 0.079 0.030 0.079
126 0.174 0.058 0.023 0.058
127 0.094 -0.016 -0.006 -0.016
128 0.112 0.021 0.008 0.021
129 0.533 0.228 0.087 0.228
130 0.250 -0.028 -0.011 -0.028
131 0.360 0.100 0.038 0.100
132 0.280 0.055 0.021 0.055
136 0.109 -0.181 -0.069 -0.181
137 0.061 -0.075 -0.029 -0.075
138 0.043 -0.255 -0.098 -0.255
142 0.280 0.055 0.020 0.055
143 0.302 -0.145 -0.053 -0.145
144 0.375 -0.071 -0.025 -0.071
145 0.577 0.153 0.057 0.153
146 0.151 -0.242 -0.090 -0.242
148 0.440 0.057 0.023 0.057
149 0.060 -0.382 -0.140 -0.382
150 0.162 0.022 0.009 0.022
151 0.023 -0.147 -0.054 -0.147
152 0.017 -0.169 -0.063 -0.169
153 0.597 0.174 0.066 0.174
154 0.188 -0.237 -0.087 -0.237
155 0.005 -0.411 -0.153 -0.411
156 0.672 0.263 0.096 0.263
157 0.075 -0.182 -0.066 -0.182
158 0.509 0.082 0.030 0.082
159 0.399 0.007 0.003 0.007
160 0.046 -0.129 -0.047 -0.129
161 0.256 -0.121 -0.044 -0.121ADT, PEB
With control variableslavaan 0.6-21 ended normally after 55 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 49
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 148.973 139.584
Degrees of freedom 101 101
P-value (Chi-square) 0.001 0.007
Scaling correction factor 1.067
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1830.939 1435.408
Degrees of freedom 138 138
P-value 0.000 0.000
Scaling correction factor 1.276
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.972 0.970
Tucker-Lewis Index (TLI) 0.961 0.959
Robust Comparative Fit Index (CFI) 0.975
Robust Tucker-Lewis Index (TLI) 0.966
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2744.119 -2744.119
Scaling correction factor 1.705
for the MLR correction
Loglikelihood unrestricted model (H1) -2669.632 -2669.632
Scaling correction factor 1.276
for the MLR correction
Akaike (AIC) 5586.238 5586.238
Bayesian (BIC) 5747.856 5747.856
Sample-size adjusted Bayesian (SABIC) 5592.619 5592.619
Root Mean Square Error of Approximation:
RMSEA 0.049 0.044
90 Percent confidence interval - lower 0.031 0.025
90 Percent confidence interval - upper 0.065 0.060
P-value H_0: RMSEA <= 0.050 0.534 0.722
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.045
90 Percent confidence interval - lower 0.025
90 Percent confidence interval - upper 0.062
P-value H_0: Robust RMSEA <= 0.050 0.658
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.043 0.043
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 0.850 0.860
ADT2 1.032 0.085 12.163 0.000 0.877 0.890
ADT3 1.079 0.081 13.359 0.000 0.917 0.855
IM =~
IM1 1.000 0.884 0.897
IM2 0.720 0.113 6.387 0.000 0.637 0.772
IM3 0.699 0.133 5.261 0.000 0.617 0.644
EEF =~
EEF1 1.000 1.001 0.903
EEF2 1.032 0.062 16.559 0.000 1.033 0.918
EEF3 0.961 0.050 19.105 0.000 0.962 0.892
EEC =~
EEC1 1.000 0.881 0.700
EEC2 1.345 0.136 9.902 0.000 1.186 0.860
EEC3 1.404 0.113 12.464 0.000 1.238 0.942
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.303 0.190 1.592 0.111 0.343 0.126
rwrd0_2 (b_02) 0.193 0.221 0.875 0.382 0.218 0.084
rwrd1_2 (b_12) 0.333 0.212 1.572 0.116 0.377 0.140
rwrd0_3 (b_03) 0.255 0.223 1.146 0.252 0.289 0.105
rwrd1_3 (b_13) -0.045 0.185 -0.241 0.810 -0.050 -0.018
ADT (b_AD) 0.199 0.091 2.188 0.029 0.192 0.192
PEB_yes (b_PE) 0.924 0.135 6.829 0.000 1.046 0.433
EEF ~
rwrd1_1 (c_11) 0.203 0.187 1.084 0.278 0.202 0.074
rwrd0_2 (c_02) -0.122 0.197 -0.621 0.535 -0.122 -0.047
rwrd1_2 (c_12) 0.121 0.181 0.670 0.503 0.121 0.045
rwrd0_3 (c_03) -0.209 0.171 -1.223 0.221 -0.209 -0.076
rwrd1_3 (c_13) 0.054 0.188 0.289 0.773 0.054 0.020
IM (c_IM) 0.625 0.097 6.462 0.000 0.551 0.551
ADT (c_AD) 0.229 0.072 3.169 0.002 0.195 0.195
PEB_yes (c_PE) 0.270 0.176 1.532 0.126 0.270 0.112
EEC ~
rwrd1_1 (d_11) 0.142 0.206 0.691 0.489 0.162 0.059
rwrd0_2 (d_02) 0.145 0.210 0.690 0.490 0.164 0.063
rwrd1_2 (d_12) 0.262 0.195 1.339 0.181 0.297 0.110
rwrd0_3 (d_03) 0.054 0.180 0.299 0.765 0.061 0.022
rwrd1_3 (d_13) 0.057 0.207 0.275 0.783 0.065 0.024
IM (d_IM) 0.403 0.095 4.230 0.000 0.404 0.404
ADT (d_AD) 0.265 0.081 3.290 0.001 0.256 0.256
PEB_yes (d_PE) 0.056 0.167 0.334 0.738 0.063 0.026
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.130 0.066 1.952 0.051 0.130 0.337
.EEF ~~
.EEC 0.217 0.067 3.228 0.001 0.404 0.404
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.ADT1 0.255 0.060 4.223 0.000 0.255 0.261
.ADT2 0.202 0.056 3.628 0.000 0.202 0.208
.ADT3 0.311 0.090 3.453 0.001 0.311 0.270
.IM1 0.191 0.072 2.657 0.008 0.191 0.196
.IM2 0.274 0.079 3.454 0.001 0.274 0.404
.IM3 0.537 0.201 2.676 0.007 0.537 0.585
.EEF1 0.228 0.045 5.018 0.000 0.228 0.185
.EEF2 0.199 0.046 4.379 0.000 0.199 0.157
.EEF3 0.236 0.064 3.679 0.000 0.236 0.204
.EEC1 0.810 0.097 8.340 0.000 0.810 0.510
.EEC2 0.496 0.112 4.428 0.000 0.496 0.261
.EEC3 0.193 0.066 2.916 0.004 0.193 0.112
ADT 0.723 0.097 7.467 0.000 1.000 1.000
.IM 0.590 0.129 4.560 0.000 0.755 0.755
.EEF 0.530 0.115 4.611 0.000 0.529 0.529
.EEC 0.547 0.103 5.303 0.000 0.704 0.704
R-Square:
Estimate
ADT1 0.739
ADT2 0.792
ADT3 0.730
IM1 0.804
IM2 0.596
IM3 0.415
EEF1 0.815
EEF2 0.843
EEF3 0.796
EEC1 0.490
EEC2 0.739
EEC3 0.888
IM 0.245
EEF 0.471
EEC 0.296
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.303 0.190 1.592 0.111 0.343 0.126
reward2_IM 0.140 0.236 0.592 0.554 0.158 0.056
reward3_IM -0.300 0.227 -1.319 0.187 -0.339 -0.123
reward_vrgd_IM 0.048 0.134 0.357 0.721 0.054 0.020
reward_EEF_ec1 0.203 0.187 1.084 0.278 0.202 0.074
reward_EEF_ec2 0.244 0.211 1.154 0.249 0.243 0.092
reward_EEF_ec3 0.263 0.195 1.352 0.176 0.263 0.095
reward_man_EEF 0.237 0.115 2.058 0.040 0.236 0.087
ind_rwrd_EEF_1 0.189 0.127 1.491 0.136 0.189 0.069
ind_rwrd_EEF_2 0.087 0.145 0.603 0.546 0.087 0.031
ind_rwrd_EEF_3 -0.187 0.145 -1.288 0.198 -0.187 -0.068
ind_rw__IM_EEF 0.030 0.083 0.358 0.721 0.030 0.011
tt_rwrd_mn_EEF 0.266 0.129 2.061 0.039 0.266 0.098
reward_EEC_ec1 0.142 0.206 0.691 0.489 0.162 0.059
reward_EEC_ec2 0.117 0.196 0.598 0.550 0.133 0.047
reward_EEC_ec3 0.003 0.193 0.016 0.987 0.003 0.002
reward_man_EEC 0.088 0.114 0.767 0.443 0.099 0.036
ind_rwrd_EEC_1 0.122 0.085 1.434 0.152 0.138 0.051
ind_rwrd_EEC_2 0.056 0.095 0.590 0.555 0.064 0.023
ind_rwrd_EEC_3 -0.121 0.096 -1.261 0.207 -0.137 -0.050
ind_rw__IM_EEC 0.019 0.054 0.354 0.723 0.022 0.008
tt_rwrd_mn_EEC 0.107 0.121 0.884 0.377 0.121 0.044
eco2_vs_c1_EEF -0.102 0.143 -0.710 0.477 -0.102 -0.038
eco3_vs_c1_EEF -0.179 0.134 -1.332 0.183 -0.179 -0.065
eco1_vs_c2_EEF 0.102 0.143 0.710 0.477 0.102 0.038
eco_main_EEF -0.140 0.117 -1.195 0.232 -0.140 -0.051
eco2_vs_ec1_IM 0.112 0.148 0.756 0.450 0.126 0.049
eco3_vs_ec1_IM -0.046 0.144 -0.320 0.749 -0.052 -0.020
eco1_vs_ec2_IM -0.112 0.148 -0.756 0.450 -0.126 -0.049
in_1__2_IM_EEF -0.070 0.094 -0.738 0.460 -0.070 -0.027
in_2__1_IM_EEF 0.070 0.094 0.738 0.460 0.070 0.027
in_3__1_IM_EEF -0.029 0.090 -0.320 0.749 -0.029 -0.011
ind_c_m_IM_EEF 0.020 0.076 0.268 0.788 0.020 0.008
tt_c1_vs_2_EEF 0.032 0.157 0.204 0.838 0.032 0.011
tt_c2_vs_1_EEF -0.032 0.157 -0.204 0.838 -0.032 -0.011
tt_c3_vs_1_EEF -0.208 0.151 -1.371 0.170 -0.207 -0.076
tot_eco_mn_EEF -0.120 0.129 -0.926 0.354 -0.120 -0.043
eco2_vs_c1_EEC 0.132 0.145 0.907 0.364 0.150 0.057
eco3_vs_c1_EEC -0.016 0.136 -0.116 0.908 -0.018 -0.007
eco_main_EEC 0.058 0.123 0.473 0.636 0.066 0.025
in_2__1_IM_EEC 0.045 0.060 0.745 0.456 0.051 0.020
in_3__1_IM_EEC -0.019 0.058 -0.318 0.750 -0.021 -0.008
ind_c_m_IM_EEC 0.013 0.049 0.270 0.787 0.015 0.006
tt_c2_vs_1_EEC 0.177 0.157 1.126 0.260 0.201 0.077
tt_c3_vs_1_EEC -0.034 0.135 -0.255 0.799 -0.039 -0.015
tot_eco_mn_EEC 0.071 0.126 0.566 0.571 0.081 0.031
eco_main_IM 0.033 0.121 0.270 0.787 0.037 0.015
eco3_vs_c2_EEF -0.077 0.148 -0.521 0.602 -0.077 -0.027
in_3__2_IM_EEF -0.098 0.104 -0.948 0.343 -0.098 -0.038
tt_c3_vs_2_EEF -0.176 0.168 -1.046 0.296 -0.175 -0.065
eco3_vs_c2_EEC -0.148 0.138 -1.068 0.286 -0.168 -0.064
in_3__2_IM_EEC -0.063 0.067 -0.944 0.345 -0.072 -0.028
tt_c3_vs_2_EEC -0.211 0.149 -1.417 0.157 -0.240 -0.092
reward_IM_eco1 0.303 0.190 1.592 0.111 0.343 0.126
reward_IM_eco2 0.140 0.236 0.592 0.554 0.158 0.056
reward_IM_eco3 -0.300 0.227 -1.319 0.187 -0.339 -0.123
reward_main_IM 0.048 0.134 0.357 0.721 0.054 0.020
r_3_EEF___1_EE -0.148 0.206 -0.720 0.472 -0.148 -0.054
r_2_EEF___1_EE -0.081 0.203 -0.400 0.689 -0.081 -0.029
r_2_EEC___1_EE 0.119 0.197 0.607 0.544 0.135 0.051
r_3_EEC___2_EE -0.205 0.206 -0.992 0.321 -0.232 -0.087
r_3_EEC___1_EE -0.085 0.211 -0.405 0.685 -0.097 -0.036
rw_2_IM___1_IM 0.030 0.190 0.158 0.875 0.034 0.014
rw_3_IM___1_IM -0.348 0.185 -1.875 0.061 -0.393 -0.144
i__2_EEC___1_E 0.012 0.076 0.158 0.874 0.014 0.006
i__3_EEC___1_E -0.140 0.084 -1.670 0.095 -0.159 -0.058
i__3_EEC___2_E -0.152 0.087 -1.743 0.081 -0.172 -0.064
t__2_EEC___1_E 0.131 0.213 0.618 0.536 0.149 0.057
t__3_EEC___1_E -0.225 0.216 -1.041 0.298 -0.256 -0.094
t__3_EEC___2_E -0.357 0.218 -1.639 0.101 -0.405 -0.150Mediation 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 0.237 0.117 2.021 0.043 -0.007
86 ind_reward_main_IM_EEF 0.030 0.088 0.337 0.736 -0.109
87 tot_reward_main_EEF 0.266 0.137 1.947 0.052 -0.057
91 reward_main_EEC 0.088 0.127 0.691 0.490 -0.175
95 ind_reward_main_IM_EEC 0.019 0.055 0.348 0.728 -0.075
96 tot_reward_main_EEC 0.107 0.133 0.805 0.421 -0.151
98 eco3_vs_eco1_EEF -0.179 0.136 -1.316 0.188 -0.459
99 eco1_vs_eco2_EEF 0.102 0.138 0.738 0.461 -0.151
100 eco_main_EEF -0.140 0.109 -1.284 0.199 -0.372
101 eco2_vs_eco1_IM 0.112 0.154 0.725 0.469 -0.287
102 eco3_vs_eco1_IM -0.046 0.146 -0.316 0.752 -0.340
103 eco1_vs_eco2_IM -0.112 0.154 -0.725 0.469 -0.386
104 ind_eco1_vs_eco2_IM_EEF -0.070 0.107 -0.650 0.516 -0.324
106 ind_eco3_vs_eco1_IM_EEF -0.029 0.093 -0.309 0.757 -0.202
107 ind_eco_main_IM_EEF 0.020 0.087 0.236 0.814 -0.164
108 tot_eco1_vs_eco2_EEF 0.032 0.136 0.236 0.814 -0.131
110 tot_eco3_vs_eco1_EEF -0.208 0.170 -1.220 0.223 -0.593
111 tot_eco_main_EEF -0.120 0.126 -0.948 0.343 -0.476
112 eco2_vs_eco1_EEC 0.132 0.182 0.725 0.469 -0.341
113 eco3_vs_eco1_EEC -0.016 0.158 -0.100 0.921 -0.521
114 eco_main_EEC 0.058 0.158 0.367 0.714 -0.431
115 ind_eco2_vs_eco1_IM_EEC 0.045 0.068 0.657 0.511 -0.122
116 ind_eco3_vs_eco1_IM_EEC -0.019 0.061 -0.302 0.762 -0.129
117 ind_eco_main_IM_EEC 0.013 0.058 0.226 0.821 -0.123
118 tot_eco2_vs_eco1_EEC 0.177 0.168 1.054 0.292 -0.213
119 tot_eco3_vs_eco1_EEC -0.034 0.148 -0.232 0.816 -0.417
120 tot_eco_main_EEC 0.071 0.146 0.489 0.625 -0.288
121 eco_main_IM 0.033 0.131 0.251 0.802 -0.280
125 eco3_vs_eco2_EEC -0.148 0.126 -1.172 0.241 -0.432
126 ind_eco3_vs_eco2_IM_EEC -0.063 0.058 -1.102 0.270 -0.172
127 tot_eco3_vs_eco2_EEC -0.211 0.122 -1.733 0.083 -0.493
131 reward_main_IM 0.048 0.143 0.334 0.739 -0.179
132 reward_eco3_EEF_vs_reward_eco1_EEF -0.148 0.242 -0.612 0.540 -0.725
133 reward_eco2_EEF_vs_reward_eco1_EEF -0.081 0.173 -0.470 0.638 -0.446
134 reward_eco2_EEC_vs_reward_eco1_EEC 0.119 0.224 0.533 0.594 -0.438
135 reward_eco3_EEC_vs_reward_eco2_EEC -0.205 0.233 -0.878 0.380 -0.580
137 reward_eco2_IM_vs_reward_eco1_IM 0.030 0.178 0.168 0.866 -0.403
138 reward_eco3_IM_vs_reward_eco1_IM -0.348 0.209 -1.661 0.097 -0.762
139 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.012 0.074 0.163 0.871 -0.187
140 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.140 0.092 -1.519 0.129 -0.353
141 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.152 0.079 -1.916 0.055 -0.289
142 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.131 0.228 0.577 0.564 -0.410
143 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.225 0.234 -0.962 0.336 -0.737
144 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.357 0.225 -1.585 0.113 -0.732
ci.upper std.lv std.all std.nox
82 0.501 0.236 0.087 0.236
86 0.235 0.030 0.011 0.030
87 0.537 0.266 0.098 0.266
91 0.316 0.099 0.036 0.099
95 0.132 0.022 0.008 0.022
96 0.363 0.121 0.044 0.121
98 0.035 -0.179 -0.065 -0.179
99 0.403 0.102 0.038 0.102
100 0.090 -0.140 -0.051 -0.140
101 0.386 0.126 0.049 0.126
102 0.355 -0.052 -0.020 -0.052
103 0.287 -0.126 -0.049 -0.126
104 0.171 -0.070 -0.027 -0.070
106 0.252 -0.029 -0.011 -0.029
107 0.240 0.020 0.008 0.020
108 0.414 0.032 0.011 0.032
110 0.107 -0.207 -0.076 -0.207
111 0.083 -0.120 -0.043 -0.120
112 0.606 0.150 0.057 0.150
113 0.345 -0.018 -0.007 -0.018
114 0.475 0.066 0.025 0.066
115 0.171 0.051 0.020 0.051
116 0.182 -0.021 -0.008 -0.021
117 0.172 0.015 0.006 0.015
118 0.599 0.201 0.077 0.201
119 0.373 -0.039 -0.015 -0.039
120 0.477 0.081 0.031 0.081
121 0.338 0.037 0.015 0.037
125 0.078 -0.168 -0.064 -0.168
126 0.065 -0.072 -0.028 -0.072
127 0.000 -0.240 -0.092 -0.240
131 0.389 0.054 0.020 0.054
132 0.279 -0.148 -0.054 -0.148
133 0.323 -0.081 -0.029 -0.081
134 0.652 0.135 0.051 0.135
135 0.292 -0.232 -0.087 -0.232
137 0.376 0.034 0.014 0.034
138 0.260 -0.393 -0.144 -0.393
139 0.158 0.014 0.006 0.014
140 0.115 -0.159 -0.058 -0.159
141 0.054 -0.172 -0.064 -0.172
142 0.640 0.149 0.057 0.149
143 0.265 -0.256 -0.094 -0.256
144 0.131 -0.405 -0.150 -0.405Only PEB)
With control variableslavaan 0.6-21 ended normally after 60 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 53
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 229.990 218.742
Degrees of freedom 157 157
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.051
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2455.693 2006.578
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.224
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.968 0.966
Tucker-Lewis Index (TLI) 0.960 0.958
Robust Comparative Fit Index (CFI) 0.971
Robust Tucker-Lewis Index (TLI) 0.964
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3560.685 -3560.685
Scaling correction factor 1.707
for the MLR correction
Loglikelihood unrestricted model (H1) -3445.690 -3445.690
Scaling correction factor 1.217
for the MLR correction
Akaike (AIC) 7227.371 7227.371
Bayesian (BIC) 7402.182 7402.182
Sample-size adjusted Bayesian (SABIC) 7234.272 7234.272
Root Mean Square Error of Approximation:
RMSEA 0.048 0.044
90 Percent confidence interval - lower 0.034 0.030
90 Percent confidence interval - upper 0.061 0.057
P-value H_0: RMSEA <= 0.050 0.575 0.748
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.045
90 Percent confidence interval - lower 0.030
90 Percent confidence interval - upper 0.059
P-value H_0: Robust RMSEA <= 0.050 0.691
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.107 0.107
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 1.285 0.880
TR2 1.101 0.053 20.921 0.000 1.416 0.944
TR3 1.061 0.054 19.766 0.000 1.364 0.914
ADT =~
ADT1 1.000 0.845 0.855
ADT2 1.044 0.084 12.438 0.000 0.883 0.896
ADT3 1.084 0.079 13.686 0.000 0.916 0.853
IM =~
IM1 1.000 0.880 0.895
IM2 0.723 0.111 6.529 0.000 0.636 0.773
IM3 0.701 0.131 5.337 0.000 0.617 0.645
EEF =~
EEF1 1.000 0.996 0.901
EEF2 1.034 0.062 16.656 0.000 1.030 0.918
EEF3 0.962 0.050 19.230 0.000 0.959 0.892
EEC =~
EEC1 1.000 0.879 0.699
EEC2 1.347 0.137 9.867 0.000 1.184 0.860
EEC3 1.404 0.113 12.460 0.000 1.234 0.941
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.330 0.200 1.646 0.100 0.375 0.137
rwrd0_2 (b_02) 0.209 0.220 0.953 0.341 0.238 0.091
rwrd1_2 (b_12) 0.320 0.213 1.498 0.134 0.363 0.135
rwrd0_3 (b_03) 0.265 0.229 1.155 0.248 0.301 0.109
rwrd1_3 (b_13) -0.048 0.188 -0.256 0.798 -0.055 -0.020
PEB_yes (b_PE) 0.910 0.132 6.890 0.000 1.034 0.429
EEF ~
rwrd1_1 (c_11) 0.213 0.189 1.126 0.260 0.214 0.078
rwrd0_2 (c_02) -0.116 0.201 -0.576 0.565 -0.116 -0.045
rwrd1_2 (c_12) 0.085 0.192 0.444 0.657 0.086 0.032
rwrd0_3 (c_03) -0.213 0.179 -1.191 0.234 -0.214 -0.077
rwrd1_3 (c_13) 0.052 0.193 0.267 0.790 0.052 0.019
IM (c_IM) 0.679 0.099 6.881 0.000 0.600 0.600
PEB_yes (c_PE) 0.202 0.189 1.073 0.283 0.203 0.084
EEC ~
rwrd1_1 (d_11) 0.155 0.207 0.749 0.454 0.177 0.065
rwrd0_2 (d_02) 0.152 0.211 0.723 0.470 0.173 0.067
rwrd1_2 (d_12) 0.221 0.208 1.063 0.288 0.251 0.093
rwrd0_3 (d_03) 0.050 0.186 0.270 0.787 0.057 0.021
rwrd1_3 (d_13) 0.053 0.219 0.243 0.808 0.061 0.022
IM (d_IM) 0.465 0.090 5.193 0.000 0.466 0.466
PEB_yes (d_PE) -0.020 0.174 -0.116 0.908 -0.023 -0.009
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM2 ~~
.IM3 0.128 0.065 1.964 0.050 0.128 0.335
TR ~~
ADT 0.516 0.093 5.521 0.000 0.475 0.475
.EEF ~~
.EEC 0.259 0.073 3.561 0.000 0.447 0.447
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.482 0.085 5.648 0.000 0.482 0.226
.TR2 0.247 0.065 3.812 0.000 0.247 0.110
.TR3 0.367 0.094 3.915 0.000 0.367 0.165
.ADT1 0.264 0.060 4.364 0.000 0.264 0.270
.ADT2 0.192 0.054 3.553 0.000 0.192 0.198
.ADT3 0.313 0.093 3.356 0.001 0.313 0.272
.IM1 0.193 0.069 2.818 0.005 0.193 0.200
.IM2 0.273 0.078 3.478 0.001 0.273 0.403
.IM3 0.536 0.201 2.671 0.008 0.536 0.585
.EEF1 0.230 0.046 5.045 0.000 0.230 0.188
.EEF2 0.197 0.045 4.363 0.000 0.197 0.157
.EEF3 0.236 0.064 3.663 0.000 0.236 0.204
.EEC1 0.810 0.097 8.327 0.000 0.810 0.512
.EEC2 0.494 0.113 4.359 0.000 0.494 0.261
.EEC3 0.195 0.066 2.946 0.003 0.195 0.114
TR 1.652 0.177 9.317 0.000 1.000 1.000
ADT 0.714 0.096 7.413 0.000 1.000 1.000
.IM 0.615 0.140 4.402 0.000 0.794 0.794
.EEF 0.564 0.121 4.657 0.000 0.569 0.569
.EEC 0.594 0.114 5.197 0.000 0.769 0.769
R-Square:
Estimate
TR1 0.774
TR2 0.890
TR3 0.835
ADT1 0.730
ADT2 0.802
ADT3 0.728
IM1 0.800
IM2 0.597
IM3 0.415
EEF1 0.812
EEF2 0.843
EEF3 0.796
EEC1 0.488
EEC2 0.739
EEC3 0.886
IM 0.206
EEF 0.431
EEC 0.231###Comparing difference between model fits