$all
[1] 200Reporting SEM_conservative sample
Sample size
Factor analyses
KMOKaiser-Meyer-Olkin factor adequacy
Call: KMO(r = efa_data_good)
Overall MSA = 0.84
MSA for each item =
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2 TR3
0.90 0.84 0.83 0.86 0.89 0.89 0.90 0.83 0.81 0.87 0.78 0.81 0.86 0.76 0.81 Correlation analysis
Bartlett test
R was not square, finding R from data$chisq
[1] 2681.929
$p.value
[1] 0
$df
[1] 105Correlation matrix
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1
IM1 1.0000000 0.64326152 0.61979636 0.4982582 0.5173121 0.5129724 0.4126565
IM2 0.6432615 1.00000000 0.67070298 0.4139217 0.4676608 0.4573846 0.3136449
IM3 0.6197964 0.67070298 1.00000000 0.3426372 0.3894868 0.4338694 0.4159567
EEF1 0.4982582 0.41392173 0.34263720 1.0000000 0.8316756 0.8168640 0.4793843
EEF2 0.5173121 0.46766080 0.38948681 0.8316756 1.0000000 0.8129749 0.4721765
EEF3 0.5129724 0.45738460 0.43386936 0.8168640 0.8129749 1.0000000 0.4628790
EEC1 0.4126565 0.31364493 0.41595667 0.4793843 0.4721765 0.4628790 1.0000000
EEC2 0.4778518 0.32807817 0.32931552 0.4957168 0.5272198 0.5120467 0.5904316
EEC3 0.4663014 0.26966554 0.32382237 0.5245412 0.5114065 0.5316961 0.6909718
ADT1 0.2794156 0.13501374 0.15510711 0.3255508 0.3312074 0.3248718 0.2420757
ADT2 0.1436737 0.03888524 0.06903489 0.2462682 0.2235847 0.2436994 0.1993086
ADT3 0.1812815 0.09549328 0.10554165 0.3094569 0.2692572 0.2543317 0.2038638
TR1 0.2269993 0.12679426 0.16844263 0.2506951 0.1945171 0.2174108 0.2457840
TR2 0.2192631 0.08673667 0.12332224 0.1852857 0.1486312 0.2032614 0.1481077
TR3 0.2101082 0.12041224 0.15370525 0.2512533 0.1947803 0.2523888 0.1981541
EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2
IM1 0.4778518 0.4663014 0.2794156 0.14367369 0.18128154 0.2269993 0.21926306
IM2 0.3280782 0.2696655 0.1350137 0.03888524 0.09549328 0.1267943 0.08673667
IM3 0.3293155 0.3238224 0.1551071 0.06903489 0.10554165 0.1684426 0.12332224
EEF1 0.4957168 0.5245412 0.3255508 0.24626818 0.30945689 0.2506951 0.18528567
EEF2 0.5272198 0.5114065 0.3312074 0.22358466 0.26925724 0.1945171 0.14863117
EEF3 0.5120467 0.5316961 0.3248718 0.24369938 0.25433169 0.2174108 0.20326143
EEC1 0.5904316 0.6909718 0.2420757 0.19930861 0.20386383 0.2457840 0.14810773
EEC2 1.0000000 0.8270083 0.3072727 0.25024427 0.28481147 0.2606290 0.17748546
EEC3 0.8270083 1.0000000 0.3282466 0.25511178 0.25512328 0.3272256 0.26011965
ADT1 0.3072727 0.3282466 1.0000000 0.76093033 0.71536627 0.3396706 0.33413205
ADT2 0.2502443 0.2551118 0.7609303 1.00000000 0.78053629 0.3168064 0.30260667
ADT3 0.2848115 0.2551233 0.7153663 0.78053629 1.00000000 0.3343923 0.29317572
TR1 0.2606290 0.3272256 0.3396706 0.31680643 0.33439226 1.0000000 0.83406679
TR2 0.1774855 0.2601197 0.3341320 0.30260667 0.29317572 0.8340668 1.00000000
TR3 0.1903847 0.2780288 0.3570132 0.31129561 0.36508970 0.8148168 0.86483216
TR3
IM1 0.2101082
IM2 0.1204122
IM3 0.1537052
EEF1 0.2512533
EEF2 0.1947803
EEF3 0.2523888
EEC1 0.1981541
EEC2 0.1903847
EEC3 0.2780288
ADT1 0.3570132
ADT2 0.3112956
ADT3 0.3650897
TR1 0.8148168
TR2 0.8648322
TR3 1.0000000
Outliers
Loading required namespace: GPArotationThreshold = 0.35
Loadings:
MR1 MR2 MR3 MR4 MR5
IM1 NA NA NA NA 0.650
IM2 NA NA NA NA 0.832
IM3 NA NA NA NA 0.838
EEF1 0.943 NA NA NA NA
EEF2 0.894 NA NA NA NA
EEF3 0.837 NA NA NA NA
EEC1 NA NA NA 0.589 NA
EEC2 NA NA NA 0.761 NA
EEC3 NA NA NA 1.019 NA
ADT1 NA NA 0.800 NA NA
ADT2 NA NA 0.942 NA NA
ADT3 NA NA 0.846 NA NA
TR1 NA 0.862 NA NA NA
TR2 NA 0.961 NA NA NA
TR3 NA 0.911 NA NA NA
MR1 MR2 MR3 MR4 MR5
SS loadings NA NA NA NA NA
Proportion Var NA NA NA NA NA
Cumulative Var NA NA NA NA NA
Factor Correlation Matrix: 1 2 3 4 5
1 1.000 0.238 0.340 0.589 0.563
2 0.238 1.000 0.396 0.287 0.174
3 0.340 0.396 1.000 0.322 0.143
4 0.589 0.287 0.322 1.000 0.425
5 0.563 0.174 0.143 0.425 1.000
1 2 3 4 5
1 1.000 0.239 0.339 0.592 0.564
2 0.239 1.000 0.396 0.288 0.174
3 0.339 0.396 1.000 0.322 0.143
4 0.592 0.288 0.322 1.000 0.427
5 0.564 0.174 0.143 0.427 1.000CFA
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 Diagnostics
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 0.000With controls
lavaan 0.6-21 ended normally after 42 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 40
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 142.534 126.065
Degrees of freedom 80 80
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.131
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) 0.972 0.970
Tucker-Lewis Index (TLI) 0.963 0.960
Robust Comparative Fit Index (CFI) 0.976
Robust Tucker-Lewis Index (TLI) 0.969
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3578.284 -3578.284
Scaling correction factor 1.919
for the MLR correction
Loglikelihood unrestricted model (H1) -3507.017 -3507.017
Scaling correction factor 1.394
for the MLR correction
Akaike (AIC) 7236.569 7236.569
Bayesian (BIC) 7368.502 7368.502
Sample-size adjusted Bayesian (SABIC) 7241.778 7241.778
Root Mean Square Error of Approximation:
RMSEA 0.063 0.054
90 Percent confidence interval - lower 0.045 0.036
90 Percent confidence interval - upper 0.079 0.070
P-value H_0: RMSEA <= 0.050 0.108 0.345
P-value H_0: RMSEA >= 0.080 0.040 0.003
Robust RMSEA 0.057
90 Percent confidence interval - lower 0.037
90 Percent confidence interval - upper 0.075
P-value H_0: Robust RMSEA <= 0.050 0.259
P-value H_0: Robust RMSEA >= 0.080 0.019
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
IM =~
IM1 1.000 1.000 1.000
IM2 0.854 0.107 7.979 0.000 0.644 1.064
IM3 0.854 0.147 5.825 0.000 0.567 1.142
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.036 0.063 16.359 0.000 0.912 1.160
EEF3 0.967 0.051 18.936 0.000 0.867 1.067
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.340 0.133 10.081 0.000 1.079 1.600
EEC3 1.418 0.115 12.291 0.000 1.192 1.644
TR =~
TR1 1.000 1.000 1.000
TR2 1.097 0.052 20.943 0.000 0.995 1.200
TR3 1.061 0.054 19.489 0.000 0.954 1.167
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.032 0.084 12.304 0.000 0.868 1.197
ADT3 1.077 0.080 13.532 0.000 0.921 1.233
Std.lv Std.all
0.816 0.829
0.697 0.847
0.697 0.728
0.994 0.899
1.030 0.918
0.961 0.894
0.877 0.697
1.175 0.853
1.244 0.949
1.287 0.881
1.413 0.942
1.366 0.915
0.850 0.860
0.878 0.891
0.916 0.853
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
IM ~~
EEF 0.491 0.095 5.189 0.000 0.305 0.676
EEC 0.306 0.081 3.794 0.000 0.148 0.465
TR 0.214 0.094 2.281 0.023 0.030 0.398
ADT 0.093 0.066 1.409 0.159 -0.036 0.223
EEF ~~
EEC 0.519 0.103 5.045 0.000 0.317 0.721
TR 0.345 0.108 3.187 0.001 0.133 0.557
ADT 0.243 0.073 3.308 0.001 0.099 0.387
EEC ~~
TR 0.332 0.094 3.519 0.000 0.147 0.516
ADT 0.242 0.069 3.524 0.000 0.107 0.377
TR ~~
ADT 0.522 0.094 5.538 0.000 0.337 0.707
Std.lv Std.all
0.605 0.605
0.428 0.428
0.204 0.204
0.134 0.134
0.595 0.595
0.269 0.269
0.287 0.287
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 0.302 0.081 3.724 0.000 0.143 0.461
.IM2 0.192 0.063 3.066 0.002 0.069 0.315
.IM3 0.431 0.217 1.984 0.047 0.005 0.857
.EEF1 0.235 0.046 5.092 0.000 0.144 0.325
.EEF2 0.198 0.047 4.204 0.000 0.106 0.291
.EEF3 0.231 0.065 3.553 0.000 0.104 0.359
.EEC1 0.814 0.097 8.405 0.000 0.624 1.003
.EEC2 0.515 0.112 4.582 0.000 0.295 0.736
.EEC3 0.170 0.066 2.596 0.009 0.042 0.299
.TR1 0.476 0.086 5.551 0.000 0.308 0.645
.TR2 0.254 0.064 3.946 0.000 0.128 0.381
.TR3 0.364 0.095 3.853 0.000 0.179 0.549
.ADT1 0.255 0.061 4.204 0.000 0.136 0.374
.ADT2 0.200 0.055 3.612 0.000 0.092 0.309
.ADT3 0.313 0.092 3.400 0.001 0.132 0.493
IM 0.666 0.108 6.135 0.000 0.453 0.878
EEF 0.989 0.174 5.695 0.000 0.648 1.329
EEC 0.769 0.136 5.647 0.000 0.502 1.036
TR 1.658 0.178 9.315 0.000 1.309 2.006
ADT 0.723 0.097 7.483 0.000 0.534 0.912
Std.lv Std.all
0.302 0.312
0.192 0.283
0.431 0.470
0.235 0.192
0.198 0.158
0.231 0.200
0.814 0.514
0.515 0.272
0.170 0.099
0.476 0.223
0.254 0.113
0.364 0.163
0.255 0.261
0.200 0.206
0.313 0.272
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.688
IM2 0.717
IM3 0.530
EEF1 0.808
EEF2 0.842
EEF3 0.800
EEC1 0.486
EEC2 0.728
EEC3 0.901
TR1 0.777
TR2 0.887
TR3 0.837
ADT1 0.739
ADT2 0.794
ADT3 0.728Cronbach’s Alpha: IM EEF EEC TR ADT
0.837 0.930 0.863 0.937 0.900 Omega: IM EEF EEC TR ADT
0.842 0.930 0.888 0.939 0.901 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.639 0.817 0.712 0.834 0.752 Factor scores$type
[1] "cor.bentler"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.007 0.000
IM3 -0.037 0.045 0.000
EEF1 0.051 -0.112 -0.101 0.000
EEF2 0.096 -0.004 -0.023 0.004 0.000
EEF3 0.078 -0.037 0.004 0.007 -0.010 0.000
EEC1 0.109 0.090 0.197 0.080 0.085 0.087 0.000
EEC2 0.124 -0.002 0.004 -0.007 0.041 0.024 -0.045 0.000
EEC3 0.060 -0.107 -0.046 -0.040 -0.014 -0.002 0.005 0.004 0.000
TR1 0.055 -0.020 0.029 0.021 -0.006 0.028 0.066 0.038 0.065 0.000
TR2 0.044 -0.044 -0.026 -0.033 -0.053 0.012 -0.049 -0.057 -0.014 0.002
TR3 0.031 -0.035 0.008 0.034 0.001 0.069 0.015 -0.046 0.010 -0.007
ADT1 0.167 0.015 0.043 0.086 0.079 0.067 0.053 0.043 0.063 0.048
ADT2 0.004 -0.122 -0.065 -0.046 -0.085 -0.055 -0.017 -0.047 -0.036 0.007
ADT3 0.073 -0.045 -0.010 0.041 -0.008 -0.009 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 0.008 0.029 0.000
ADT2 -0.028 -0.016 -0.001 0.000
ADT3 -0.040 0.043 -0.009 0.008 0.000
$cov.z
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.133 0.000
IM3 -0.771 0.913 0.000
EEF1 0.892 -1.482 -1.382 0.000
EEF2 1.793 -0.077 -0.414 0.061 0.000
EEF3 1.353 -0.567 0.071 0.107 -0.192 0.000
EEC1 1.950 1.704 2.113 1.244 1.615 1.479 0.000
EEC2 2.500 -0.036 0.068 -0.117 0.738 0.419 -1.250 0.000
EEC3 1.490 -1.966 -0.708 -0.603 -0.238 -0.037 0.159 0.077 0.000
TR1 0.884 -0.426 0.402 0.514 -0.158 0.616 1.076 0.797 1.549 0.000
TR2 0.871 -1.049 -0.489 -0.726 -1.245 0.256 -0.839 -1.221 -0.432 0.072
TR3 0.533 -0.739 0.121 0.883 0.034 1.518 0.265 -0.986 0.317 -0.273
ADT1 2.837 0.332 0.839 1.826 1.635 1.496 0.948 0.845 1.716 0.985
ADT2 0.094 -2.884 -1.283 -0.915 -1.823 -1.171 -0.297 -0.944 -0.955 0.163
ADT3 1.324 -1.009 -0.162 0.826 -0.158 -0.208 0.096 0.299 -0.512 0.367
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.069 0.000
ADT1 0.189 0.658 0.000
ADT2 -0.861 -0.418 -0.023 0.000
ADT3 -0.958 1.073 -0.275 0.287 0.000
$summary
cov
srmr 0.051
srmr.se 0.013
srmr.exactfit.z 0.097
srmr.exactfit.pvalue 0.461
usrmr 0.000
usrmr.se 0.016
usrmr.ci.lower -0.027
usrmr.ci.upper 0.027
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -3.099
usrmr.closefit.pvalue 0.999 IM EEF EEC TR ADT
IM 1.000
EEF 0.605 1.000
EEC 0.428 0.595 1.000
TR 0.204 0.269 0.294 1.000
ADT 0.134 0.287 0.325 0.477 1.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC TR ADT
IM "1" "0.6 (0)" "0.43 (0)" "0.2 (0.013)" "0.13 (0.13)"
EEF "0.6 (0)" "1" "0.6 (0)" "0.27 (0)" "0.29 (0)"
EEC "0.43 (0)" "0.6 (0)" "1" "0.29 (0)" "0.32 (0)"
TR "0.2 (0.013)" "0.27 (0)" "0.29 (0)" "1" "0.48 (0)"
ADT "0.13 (0.13)" "0.29 (0)" "0.32 (0)" "0.48 (0)" "1" Diagnostics
Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
49 IM =~ EEC1 10.162 0.320 0.261 0.208 0.208
51 IM =~ EEC3 13.474 -0.325 -0.265 -0.202 -0.202
58 EEF =~ IM1 15.384 0.303 0.301 0.306 0.306
70 EEC =~ IM1 10.854 0.228 0.200 0.203 0.203
120 IM2 ~~ IM3 15.678 0.185 0.185 0.643 0.643
136 IM3 ~~ EEC1 13.805 0.175 0.175 0.295 0.295Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
120 IM2 ~~ IM3 15.678 0.185 0.185 0.643 0.643
136 IM3 ~~ EEC1 13.805 0.175 0.175 0.295 0.295$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.005 0.000
IM3 -0.035 0.035 0.000
EEF1 0.055 -0.102 -0.107 0.000
EEF2 0.106 -0.004 -0.025 0.005 0.000
EEF3 0.083 -0.032 0.004 0.009 -0.012 0.000
EEC1 0.135 0.094 0.237 0.112 0.120 0.117 0.000
EEC2 0.167 -0.002 0.006 -0.011 0.063 0.036 -0.078 0.000
EEC3 0.078 -0.115 -0.058 -0.058 -0.021 -0.003 0.008 0.008 0.000
TR1 0.078 -0.024 0.041 0.034 -0.010 0.044 0.122 0.076 0.125 0.000
TR2 0.064 -0.054 -0.037 -0.055 -0.089 0.020 -0.092 -0.117 -0.028 0.004
TR3 0.045 -0.043 0.012 0.056 0.003 0.111 0.029 -0.094 0.021 -0.015
ADT1 0.163 0.012 0.041 0.094 0.087 0.071 0.066 0.058 0.082 0.069
ADT2 0.004 -0.099 -0.061 -0.051 -0.094 -0.058 -0.021 -0.064 -0.047 0.010
ADT3 0.077 -0.040 -0.010 0.048 -0.009 -0.011 0.007 0.022 -0.029 0.026
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.005 0.000
ADT1 0.011 0.043 0.000
ADT2 -0.041 -0.023 -0.001 0.000
ADT3 -0.065 0.068 -0.010 0.008 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.133 0.000
IM3 -0.771 0.913 0.000
EEF1 0.892 -1.482 -1.382 0.000
EEF2 1.793 -0.077 -0.414 0.061 0.000
EEF3 1.353 -0.567 0.071 0.107 -0.192 0.000
EEC1 1.950 1.704 2.113 1.244 1.615 1.479 0.000
EEC2 2.500 -0.036 0.068 -0.117 0.738 0.419 -1.250 0.000
EEC3 1.490 -1.966 -0.708 -0.603 -0.238 -0.037 0.159 0.077 0.000
TR1 0.884 -0.426 0.402 0.514 -0.158 0.616 1.076 0.797 1.549 0.000
TR2 0.871 -1.049 -0.489 -0.726 -1.245 0.256 -0.839 -1.221 -0.432 0.072
TR3 0.533 -0.739 0.121 0.883 0.034 1.518 0.265 -0.986 0.317 -0.273
ADT1 2.837 0.332 0.839 1.826 1.635 1.496 0.948 0.845 1.716 0.985
ADT2 0.094 -2.884 -1.283 -0.915 -1.823 -1.171 -0.297 -0.944 -0.955 0.163
ADT3 1.324 -1.009 -0.162 0.826 -0.158 -0.208 0.096 0.299 -0.512 0.367
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.069 0.000
ADT1 0.189 0.658 0.000
ADT2 -0.861 -0.418 -0.023 0.000
ADT3 -0.958 1.073 -0.275 0.287 0.000Group analysis
ADT 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
Without control variableslavaan 0.6-21 ended normally after 37 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 25
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 116.853 112.287
Degrees of freedom 65 65
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.041
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1335.626 1012.563
Degrees of freedom 81 81
P-value 0.000 0.000
Scaling correction factor 1.319
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.959 0.949
Tucker-Lewis Index (TLI) 0.948 0.937
Robust Comparative Fit Index (CFI) 0.960
Robust Tucker-Lewis Index (TLI) 0.950
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2115.395 -2115.395
Scaling correction factor 2.062
for the MLR correction
Loglikelihood unrestricted model (H1) -2056.968 -2056.968
Scaling correction factor 1.324
for the MLR correction
Akaike (AIC) 4280.789 4280.789
Bayesian (BIC) 4363.247 4363.247
Sample-size adjusted Bayesian (SABIC) 4284.045 4284.045
Root Mean Square Error of Approximation:
RMSEA 0.063 0.060
90 Percent confidence interval - lower 0.044 0.041
90 Percent confidence interval - upper 0.081 0.078
P-value H_0: RMSEA <= 0.050 0.118 0.173
P-value H_0: RMSEA >= 0.080 0.065 0.036
Robust RMSEA 0.062
90 Percent confidence interval - lower 0.042
90 Percent confidence interval - upper 0.080
P-value H_0: Robust RMSEA <= 0.050 0.157
P-value H_0: Robust RMSEA >= 0.080 0.054
Standardized Root Mean Square Residual:
SRMR 0.055 0.055
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
IM =~
IM1 1.000 0.806 0.819
IM2 0.873 0.098 8.927 0.000 0.704 0.855
IM3 0.869 0.139 6.257 0.000 0.701 0.732
EEF =~
EEF1 1.000 0.992 0.897
EEF2 1.040 0.063 16.568 0.000 1.031 0.919
EEF3 0.969 0.050 19.188 0.000 0.961 0.894
EEC =~
EEC1 1.000 0.875 0.696
EEC2 1.341 0.133 10.109 0.000 1.174 0.853
EEC3 1.423 0.115 12.414 0.000 1.246 0.951
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) 0.097 0.207 0.467 0.640 0.120 0.046
rwrd1_1 (b_11) 0.406 0.215 1.886 0.059 0.504 0.185
rwrd0_2 (b_02) 0.273 0.234 1.167 0.243 0.339 0.130
rwrd1_2 (b_12) 0.452 0.189 2.389 0.017 0.561 0.208
rwrd0_3 (b_03) 0.210 0.244 0.864 0.388 0.261 0.094
EEF ~
IM (c_IM) 0.744 0.086 8.692 0.000 0.605 0.605
EEC ~
EEF (d_EE) 0.528 0.068 7.738 0.000 0.598 0.598
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.318 0.081 3.945 0.000 0.318 0.329
.IM2 0.182 0.056 3.270 0.001 0.182 0.269
.IM3 0.426 0.213 1.996 0.046 0.426 0.465
.EEF1 0.239 0.046 5.182 0.000 0.239 0.196
.EEF2 0.195 0.046 4.258 0.000 0.195 0.155
.EEF3 0.232 0.065 3.554 0.000 0.232 0.201
.EEC1 0.816 0.097 8.425 0.000 0.816 0.516
.EEC2 0.517 0.111 4.650 0.000 0.517 0.273
.EEC3 0.166 0.064 2.584 0.010 0.166 0.097
.IM 0.625 0.102 6.143 0.000 0.961 0.961
.EEF 0.624 0.137 4.548 0.000 0.634 0.634
.EEC 0.492 0.090 5.460 0.000 0.642 0.642
R-Square:
Estimate
IM1 0.671
IM2 0.731
IM3 0.535
EEF1 0.804
EEF2 0.845
EEF3 0.799
EEC1 0.484
EEC2 0.727
EEC3 0.903
IM 0.039
EEF 0.366
EEC 0.358With control variables
With latent variables
With controlslavaan 0.6-21 ended normally after 57 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 205.421 194.226
Degrees of freedom 152 152
P-value (Chi-square) 0.003 0.012
Scaling correction factor 1.058
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) 0.976 0.977
Tucker-Lewis Index (TLI) 0.970 0.970
Robust Comparative Fit Index (CFI) 0.980
Robust Tucker-Lewis Index (TLI) 0.974
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3548.401 -3548.401
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) 7212.802 7212.802
Bayesian (BIC) 7404.104 7404.104
Sample-size adjusted Bayesian (SABIC) 7220.354 7220.354
Root Mean Square Error of Approximation:
RMSEA 0.042 0.037
90 Percent confidence interval - lower 0.026 0.019
90 Percent confidence interval - upper 0.056 0.052
P-value H_0: RMSEA <= 0.050 0.819 0.926
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.038
90 Percent confidence interval - lower 0.019
90 Percent confidence interval - upper 0.053
P-value H_0: Robust RMSEA <= 0.050 0.892
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.045 0.045
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
IM =~
IM1 1.000 0.801 0.816
IM2 0.875 0.091 9.624 0.000 0.701 0.853
IM3 0.882 0.132 6.657 0.000 0.707 0.739
EEF =~
EEF1 1.000 0.996 0.901
EEF2 1.033 0.061 16.826 0.000 1.029 0.917
EEF3 0.963 0.050 19.088 0.000 0.960 0.893
EEC =~
EEC1 1.000 0.880 0.699
EEC2 1.341 0.134 10.017 0.000 1.181 0.857
EEC3 1.408 0.115 12.289 0.000 1.239 0.945
TR =~
TR1 1.000 1.288 0.881
TR2 1.098 0.053 20.858 0.000 1.413 0.942
TR3 1.060 0.054 19.542 0.000 1.365 0.914
ADT =~
ADT1 1.000 0.851 0.861
ADT2 1.029 0.084 12.293 0.000 0.876 0.889
ADT3 1.076 0.080 13.532 0.000 0.916 0.854
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) -0.015 0.172 -0.086 0.932 -0.018 -0.007
rwrd1_1 (b_11) 0.359 0.180 1.995 0.046 0.448 0.164
rwrd0_2 (b_02) 0.238 0.201 1.185 0.236 0.297 0.114
rwrd1_2 (b_12) 0.434 0.161 2.700 0.007 0.542 0.201
rwrd0_3 (b_03) 0.259 0.216 1.200 0.230 0.324 0.117
TR (b_TR) 0.089 0.045 1.966 0.049 0.143 0.143
ADT (b_AD) 0.073 0.079 0.917 0.359 0.077 0.077
PEB_yes (b_PE) 0.871 0.130 6.705 0.000 1.087 0.450
EEF ~
rwrd0_1 (c_01) -0.029 0.188 -0.154 0.877 -0.029 -0.011
rwrd1_1 (c_11) 0.128 0.209 0.614 0.539 0.128 0.047
rwrd0_2 (c_02) -0.162 0.221 -0.732 0.464 -0.163 -0.062
rwrd1_2 (c_12) 0.041 0.216 0.190 0.849 0.041 0.015
rwrd0_3 (c_03) -0.243 0.199 -1.218 0.223 -0.244 -0.088
IM (c_IM) 0.624 0.100 6.254 0.000 0.502 0.502
TR (c_TR) 0.050 0.056 0.899 0.368 0.065 0.065
ADT (c_AD) 0.231 0.080 2.890 0.004 0.198 0.198
PEB_yes (c_PE) 0.277 0.179 1.547 0.122 0.278 0.115
EEC ~
rwrd0_1 (d_01) -0.035 0.192 -0.183 0.855 -0.040 -0.015
rwrd1_1 (d_11) 0.019 0.203 0.095 0.924 0.022 0.008
rwrd0_2 (d_02) 0.174 0.196 0.889 0.374 0.198 0.076
rwrd1_2 (d_12) 0.182 0.190 0.956 0.339 0.206 0.077
rwrd0_3 (d_03) 0.113 0.177 0.639 0.523 0.128 0.046
IM (d_IM) 0.109 0.112 0.968 0.333 0.099 0.099
TR (d_TR) 0.060 0.049 1.234 0.217 0.088 0.088
ADT (d_AD) 0.136 0.077 1.759 0.079 0.131 0.131
PEB_yes (d_PE) -0.045 0.149 -0.303 0.762 -0.051 -0.021
EEF 0.426 0.079 5.396 0.000 0.483 0.483
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.523 0.094 5.539 0.000 0.477 0.477
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.323 0.084 3.865 0.000 0.323 0.335
.IM2 0.184 0.050 3.725 0.000 0.184 0.273
.IM3 0.416 0.207 2.004 0.045 0.416 0.454
.EEF1 0.230 0.046 4.998 0.000 0.230 0.188
.EEF2 0.199 0.046 4.304 0.000 0.199 0.158
.EEF3 0.234 0.065 3.619 0.000 0.234 0.203
.EEC1 0.810 0.096 8.409 0.000 0.810 0.511
.EEC2 0.504 0.112 4.517 0.000 0.504 0.266
.EEC3 0.185 0.066 2.817 0.005 0.185 0.107
.TR1 0.476 0.086 5.547 0.000 0.476 0.223
.TR2 0.253 0.065 3.895 0.000 0.253 0.113
.TR3 0.365 0.094 3.888 0.000 0.365 0.164
.ADT1 0.253 0.060 4.203 0.000 0.253 0.259
.ADT2 0.203 0.056 3.643 0.000 0.203 0.209
.ADT3 0.312 0.091 3.412 0.001 0.312 0.271
.IM 0.465 0.084 5.560 0.000 0.724 0.724
.EEF 0.564 0.128 4.414 0.000 0.568 0.568
.EEC 0.459 0.085 5.406 0.000 0.592 0.592
TR 1.658 0.178 9.317 0.000 1.000 1.000
ADT 0.725 0.096 7.513 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.665
IM2 0.727
IM3 0.546
EEF1 0.812
EEF2 0.842
EEF3 0.797
EEC1 0.489
EEC2 0.734
EEC3 0.893
TR1 0.777
TR2 0.887
TR3 0.836
ADT1 0.741
ADT2 0.791
ADT3 0.729
IM 0.276
EEF 0.432
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.373 0.167 2.241 0.025 0.466 0.171
reward2_IM 0.197 0.182 1.079 0.281 0.245 0.087
reward3_IM -0.259 0.216 -1.200 0.230 -0.324 -0.117
reward_vrgd_IM 0.104 0.111 0.931 0.352 0.129 0.047
reward_EEF_ec1 0.157 0.185 0.850 0.395 0.158 0.058
reward_EEF_ec2 0.203 0.220 0.922 0.357 0.204 0.078
reward_EEF_ec3 0.243 0.199 1.218 0.223 0.244 0.088
reward_man_EEF 0.201 0.118 1.696 0.090 0.202 0.075
ind_rwrd_EEF_1 0.233 0.110 2.124 0.034 0.234 0.086
ind_rwrd_EEF_2 0.123 0.111 1.105 0.269 0.123 0.044
ind_rwrd_EEF_3 -0.162 0.138 -1.171 0.242 -0.162 -0.059
ind_rw__IM_EEF 0.040 0.043 0.934 0.351 0.033 0.012
tt_rwrd_mn_EEF 0.241 0.119 2.020 0.043 0.234 0.087
reward_EEC_ec1 0.054 0.197 0.277 0.782 0.062 0.023
reward_EEC_ec2 0.007 0.173 0.042 0.967 0.008 0.000
reward_EEC_ec3 -0.113 0.177 -0.639 0.523 -0.128 -0.046
reward_man_EEC -0.017 0.103 -0.165 0.869 -0.019 -0.008
ind_rwrd_EEC_1 0.041 0.045 0.911 0.362 0.046 0.017
ind_rwrd_EEC_2 0.021 0.030 0.706 0.480 0.024 0.009
ind_rwrd_EEC_3 -0.028 0.037 -0.758 0.448 -0.032 -0.012
ind_rw__IM_EEC 0.001 0.003 0.430 0.667 0.001 0.000
tt_rwrd_mn_EEC -0.016 0.104 -0.153 0.878 -0.018 -0.007
eco2_vs_c1_EEF -0.110 0.144 -0.762 0.446 -0.110 -0.042
eco3_vs_c1_EEF -0.171 0.136 -1.254 0.210 -0.171 -0.062
eco1_vs_c2_EEF 0.110 0.144 0.762 0.446 0.110 0.042
eco_main_EEF -0.140 0.119 -1.185 0.236 -0.141 -0.052
eco2_vs_ec1_IM 0.164 0.121 1.351 0.177 0.205 0.079
eco3_vs_ec1_IM -0.042 0.136 -0.310 0.756 -0.053 -0.020
eco1_vs_ec2_IM -0.164 0.121 -1.351 0.177 -0.205 -0.079
in_1__2_IM_EEF -0.102 0.080 -1.281 0.200 -0.103 -0.040
in_2__1_IM_EEF 0.102 0.080 1.281 0.200 0.103 0.040
in_3__1_IM_EEF -0.026 0.085 -0.311 0.755 -0.027 -0.010
ind_c_m_IM_EEF 0.038 0.070 0.546 0.585 0.038 0.015
tt_c1_vs_2_EEF 0.008 0.152 0.050 0.960 0.008 0.002
tt_c2_vs_1_EEF -0.008 0.152 -0.050 0.960 -0.008 -0.002
tt_c3_vs_1_EEF -0.197 0.151 -1.311 0.190 -0.198 -0.072
tot_eco_mn_EEF -0.102 0.127 -0.808 0.419 -0.103 -0.037
eco2_vs_c1_EEC 0.186 0.136 1.367 0.172 0.211 0.080
eco3_vs_c1_EEC 0.064 0.130 0.496 0.620 0.073 0.027
eco_main_EEC 0.125 0.117 1.065 0.287 0.142 0.053
in_2__1_IM_EEC 0.018 0.022 0.796 0.426 0.020 0.008
in_3__1_IM_EEC -0.005 0.016 -0.295 0.768 -0.005 -0.002
ind_c_m_IM_EEC 0.007 0.014 0.486 0.627 0.008 0.003
tt_c2_vs_1_EEC 0.204 0.137 1.489 0.136 0.232 0.088
tt_c3_vs_1_EEC 0.060 0.128 0.465 0.642 0.068 0.025
tot_eco_mn_EEC 0.132 0.117 1.124 0.261 0.150 0.056
eco_main_IM 0.061 0.110 0.555 0.579 0.076 0.030
eco3_vs_c2_EEF -0.061 0.150 -0.405 0.685 -0.061 -0.021
in_3__2_IM_EEF -0.129 0.088 -1.455 0.146 -0.129 -0.050
tt_c3_vs_2_EEF -0.190 0.165 -1.146 0.252 -0.190 -0.070
eco3_vs_c2_EEC -0.122 0.124 -0.979 0.328 -0.138 -0.053
in_3__2_IM_EEC -0.022 0.027 -0.819 0.413 -0.025 -0.010
tt_c3_vs_2_EEC -0.144 0.124 -1.158 0.247 -0.164 -0.063
reward_IM_eco1 0.373 0.167 2.241 0.025 0.466 0.171
reward_IM_eco2 0.197 0.182 1.079 0.281 0.245 0.087
reward_IM_eco3 -0.259 0.216 -1.200 0.230 -0.324 -0.117
reward_main_IM 0.104 0.111 0.931 0.352 0.129 0.047
r_3_EEF___1_EE -0.128 0.209 -0.614 0.539 -0.128 -0.047
r_2_EEF___1_EE -0.087 0.213 -0.408 0.683 -0.087 -0.032
r_2_EEC___1_EE 0.162 0.185 0.876 0.381 0.184 0.069
r_3_EEC___2_EE -0.182 0.190 -0.956 0.339 -0.206 -0.077
r_3_EEC___1_EE -0.019 0.203 -0.095 0.924 -0.022 -0.008
rw_2_IM___1_IM 0.076 0.159 0.475 0.635 0.094 0.037
rw_3_IM___1_IM -0.359 0.180 -1.995 0.046 -0.448 -0.164
i__2_EEC___1_E 0.008 0.020 0.420 0.675 0.009 0.004
i__3_EEC___1_E -0.039 0.044 -0.882 0.378 -0.044 -0.016
i__3_EEC___2_E -0.047 0.052 -0.910 0.363 -0.054 -0.020
t__2_EEC___1_E 0.171 0.188 0.909 0.364 0.194 0.072
t__3_EEC___1_E -0.058 0.200 -0.291 0.771 -0.066 -0.024
t__3_EEC___2_E -0.229 0.189 -1.209 0.227 -0.260 -0.097
rwrd_c3_dr_EEF 0.243 0.199 1.218 0.223 0.244 0.088
rwrd_3__IM_EEF -0.162 0.138 -1.171 0.242 -0.162 -0.059
rwrd_c3_tt_EEF 0.081 0.227 0.357 0.721 0.081 0.029
rwrd_c3_dr_EEC -0.113 0.177 -0.639 0.523 -0.128 -0.046
rwrd_3__IM_EEC -0.028 0.037 -0.758 0.448 -0.032 -0.012
rwrd_c3_tt_EEC -0.141 0.170 -0.828 0.408 -0.160 -0.058Mediation analysis
Mediation analysisMediation analysis with bootstrapping=5000 lhs op
92 reward_main_EEF :=
96 ind_reward_main_IM_EEF :=
97 tot_reward_main_EEF :=
101 reward_main_EEC :=
105 ind_reward_main_IM_EEC :=
106 tot_reward_main_EEC :=
108 eco3_vs_eco1_EEF :=
109 eco1_vs_eco2_EEF :=
110 eco_main_EEF :=
111 eco2_vs_eco1_IM :=
112 eco3_vs_eco1_IM :=
113 eco1_vs_eco2_IM :=
114 ind_eco1_vs_eco2_IM_EEF :=
116 ind_eco3_vs_eco1_IM_EEF :=
117 ind_eco_main_IM_EEF :=
118 tot_eco1_vs_eco2_EEF :=
120 tot_eco3_vs_eco1_EEF :=
121 tot_eco_main_EEF :=
122 eco2_vs_eco1_EEC :=
123 eco3_vs_eco1_EEC :=
124 eco_main_EEC :=
125 ind_eco2_vs_eco1_IM_EEC :=
126 ind_eco3_vs_eco1_IM_EEC :=
127 ind_eco_main_IM_EEC :=
128 tot_eco2_vs_eco1_EEC :=
129 tot_eco3_vs_eco1_EEC :=
130 tot_eco_main_EEC :=
131 eco_main_IM :=
135 eco3_vs_eco2_EEC :=
136 ind_eco3_vs_eco2_IM_EEC :=
137 tot_eco3_vs_eco2_EEC :=
141 reward_main_IM :=
142 reward_eco3_EEF_vs_reward_eco1_EEF :=
143 reward_eco2_EEF_vs_reward_eco1_EEF :=
144 reward_eco2_EEC_vs_reward_eco1_EEC :=
145 reward_eco3_EEC_vs_reward_eco2_EEC :=
147 reward_eco2_IM_vs_reward_eco1_IM :=
148 reward_eco3_IM_vs_reward_eco1_IM :=
149 ind_reward_eco2_EEC_vs_reward_eco1_EEC :=
150 ind_reward_eco3_EEC_vs_reward_eco1_EEC :=
151 ind_reward_eco3_EEC_vs_reward_eco2_EEC :=
152 tot_reward_eco2_EEC_vs_reward_eco1_EEC :=
153 tot_reward_eco3_EEC_vs_reward_eco1_EEC :=
154 tot_reward_eco3_EEC_vs_reward_eco2_EEC :=
155 reward_eco3_direct_EEF :=
156 reward_eco3_ind_IM_EEF :=
157 reward_eco3_total_EEF :=
158 reward_eco3_direct_EEC :=
159 reward_eco3_ind_IM_EEC :=
160 reward_eco3_total_EEC :=
rhs
92 (reward_EEF_eco1+reward_EEF_eco2+reward_EEF_eco3)/3
96 (ind_reward_EEF_eco1+ind_reward_EEF_eco2+ind_reward_EEF_eco3)/3*c_IM
97 reward_main_EEF+ind_reward_main_IM_EEF
101 (reward_EEC_eco1+reward_EEC_eco2+reward_EEC_eco3)/3
105 (ind_reward_EEC_eco1+ind_reward_EEC_eco2+ind_reward_EEC_eco3)/3*d_IM
106 reward_main_EEC+ind_reward_main_IM_EEC
108 ((c_r0e3-c_r0e1)+(0-c_r1e1))/2
109 ((c_r0e1-c_r0e2)+(c_r1e1-c_r1e2))/2
110 (eco2_vs_eco1_EEF+eco3_vs_eco1_EEF)/2
111 ((b_r0e2-b_r0e1)+(b_r1e2-b_r1e1))/2
112 ((b_r0e3-b_r0e1)+(0-b_r1e1))/2
113 ((b_r0e1-b_r0e2)+(b_r1e1-b_r1e2))/2
114 eco1_vs_eco2_IM*c_IM
116 eco3_vs_eco1_IM*c_IM
117 (ind_eco2_vs_eco1_IM_EEF+ind_eco3_vs_eco1_IM_EEF)/2
118 eco1_vs_eco2_EEF+ind_eco1_vs_eco2_IM_EEF
120 eco3_vs_eco1_EEF+ind_eco3_vs_eco1_IM_EEF
121 eco_main_EEF+ind_eco_main_IM_EEF
122 ((d_r0e2-d_r0e1)+(d_r1e2-d_r1e1))/2
123 ((d_r0e3-d_r0e1)+(0-d_r1e1))/2
124 (eco2_vs_eco1_EEC+eco3_vs_eco1_EEC)/2
125 eco2_vs_eco1_IM*d_IM
126 eco3_vs_eco1_IM*d_IM
127 (ind_eco2_vs_eco1_IM_EEC+ind_eco3_vs_eco1_IM_EEC)/2
128 eco2_vs_eco1_EEC+ind_eco2_vs_eco1_IM_EEC
129 eco3_vs_eco1_EEC+ind_eco3_vs_eco1_IM_EEC
130 eco_main_EEC+ind_eco_main_IM_EEC
131 (eco2_vs_eco1_IM+eco3_vs_eco1_IM)/2
135 eco3_vs_eco1_EEC-eco2_vs_eco1_EEC
136 ind_eco3_vs_eco1_IM_EEC-ind_eco2_vs_eco1_IM_EEC
137 tot_eco3_vs_eco1_EEC-tot_eco2_vs_eco1_EEC
141 ((b_r1e1-b_r0e1)+(b_r1e2-b_r0e2)+(0-b_r0e3))/3
142 0-c_r1e1
143 c_r1e2-c_r1e1
144 d_r1e2-d_r1e1
145 0-d_r1e2
147 b_r1e2-b_r1e1
148 0-b_r1e1
149 (b_r1e2-b_r1e1)*d_IM
150 (0-b_r1e1)*d_IM
151 (0-b_r1e2)*d_IM
152 (d_r1e2-d_r1e1)+ind_reward_eco2_EEC_vs_reward_eco1_EEC
153 (0-d_r1e1)+ind_reward_eco3_EEC_vs_reward_eco1_EEC
154 (0-d_r1e2)+ind_reward_eco3_EEC_vs_reward_eco2_EEC
155 (0-c_r0e3)
156 (0-b_r0e3)*c_IM
157 reward_eco3_direct_EEF+reward_eco3_ind_IM_EEF
158 (0-d_r0e3)
159 (0-b_r0e3)*d_IM
160 reward_eco3_direct_EEC+reward_eco3_ind_IM_EEC
label est se z pvalue ci.lower
92 reward_main_EEF 0.201 0.135 1.484 0.138 -0.103
96 ind_reward_main_IM_EEF 0.040 0.049 0.818 0.413 -0.058
97 tot_reward_main_EEF 0.241 0.129 1.876 0.061 -0.036
101 reward_main_EEC -0.017 0.100 -0.171 0.864 -0.209
105 ind_reward_main_IM_EEC 0.001 0.010 0.124 0.901 -0.002
106 tot_reward_main_EEC -0.016 0.101 -0.158 0.874 -0.209
108 eco3_vs_eco1_EEF -0.171 0.113 -1.510 0.131 -0.431
109 eco1_vs_eco2_EEF 0.110 0.126 0.872 0.383 -0.267
110 eco_main_EEF -0.140 0.097 -1.448 0.148 -0.312
111 eco2_vs_eco1_IM 0.164 0.099 1.663 0.096 -0.052
112 eco3_vs_eco1_IM -0.042 0.132 -0.321 0.748 -0.313
113 eco1_vs_eco2_IM -0.164 0.099 -1.663 0.096 -0.310
114 ind_eco1_vs_eco2_IM_EEF -0.102 0.068 -1.509 0.131 -0.235
116 ind_eco3_vs_eco1_IM_EEF -0.026 0.081 -0.325 0.745 -0.209
117 ind_eco_main_IM_EEF 0.038 0.062 0.607 0.544 -0.104
118 tot_eco1_vs_eco2_EEF 0.008 0.139 0.055 0.956 -0.330
120 tot_eco3_vs_eco1_EEF -0.197 0.133 -1.487 0.137 -0.532
121 tot_eco_main_EEF -0.102 0.111 -0.925 0.355 -0.343
122 eco2_vs_eco1_EEC 0.186 0.119 1.568 0.117 -0.065
123 eco3_vs_eco1_EEC 0.064 0.131 0.489 0.625 -0.296
124 eco_main_EEC 0.125 0.105 1.194 0.232 -0.099
125 ind_eco2_vs_eco1_IM_EEC 0.018 0.019 0.940 0.347 -0.018
126 ind_eco3_vs_eco1_IM_EEC -0.005 0.021 -0.215 0.830 -0.071
127 ind_eco_main_IM_EEC 0.007 0.016 0.415 0.678 -0.042
128 tot_eco2_vs_eco1_EEC 0.204 0.120 1.698 0.089 -0.065
129 tot_eco3_vs_eco1_EEC 0.060 0.132 0.451 0.652 -0.295
130 tot_eco_main_EEC 0.132 0.104 1.268 0.205 -0.098
131 eco_main_IM 0.061 0.097 0.628 0.530 -0.150
135 eco3_vs_eco2_EEC -0.122 0.137 -0.888 0.374 -0.473
136 ind_eco3_vs_eco2_IM_EEC -0.022 0.025 -0.900 0.368 -0.079
137 tot_eco3_vs_eco2_EEC -0.144 0.144 -1.003 0.316 -0.481
141 reward_main_IM 0.104 0.124 0.837 0.402 -0.111
142 reward_eco3_EEF_vs_reward_eco1_EEF -0.128 0.175 -0.731 0.465 -0.540
143 reward_eco2_EEF_vs_reward_eco1_EEF -0.087 0.200 -0.434 0.664 -0.461
144 reward_eco2_EEC_vs_reward_eco1_EEC 0.162 0.185 0.878 0.380 -0.256
145 reward_eco3_EEC_vs_reward_eco2_EEC -0.182 0.217 -0.837 0.403 -0.576
147 reward_eco2_IM_vs_reward_eco1_IM 0.076 0.152 0.497 0.619 -0.307
148 reward_eco3_IM_vs_reward_eco1_IM -0.359 0.173 -2.075 0.038 -0.806
149 ind_reward_eco2_EEC_vs_reward_eco1_EEC 0.008 0.022 0.382 0.703 -0.035
150 ind_reward_eco3_EEC_vs_reward_eco1_EEC -0.039 0.045 -0.863 0.388 -0.143
151 ind_reward_eco3_EEC_vs_reward_eco2_EEC -0.047 0.050 -0.940 0.347 -0.167
152 tot_reward_eco2_EEC_vs_reward_eco1_EEC 0.171 0.192 0.890 0.373 -0.250
153 tot_reward_eco3_EEC_vs_reward_eco1_EEC -0.058 0.212 -0.276 0.783 -0.453
154 tot_reward_eco3_EEC_vs_reward_eco2_EEC -0.229 0.223 -1.027 0.304 -0.626
155 reward_eco3_direct_EEF 0.243 0.217 1.118 0.264 -0.291
156 reward_eco3_ind_IM_EEF -0.162 0.152 -1.065 0.287 -0.520
157 reward_eco3_total_EEF 0.081 0.244 0.332 0.740 -0.432
158 reward_eco3_direct_EEC -0.113 0.197 -0.573 0.566 -0.598
159 reward_eco3_ind_IM_EEC -0.028 0.048 -0.593 0.553 -0.139
160 reward_eco3_total_EEC -0.141 0.190 -0.741 0.459 -0.564
ci.upper std.lv std.all std.nox
92 0.467 0.202 0.075 0.202
96 0.176 0.033 0.012 0.033
97 0.513 0.234 0.087 0.234
101 0.188 -0.019 -0.008 -0.019
105 0.050 0.001 0.000 0.001
106 0.193 -0.018 -0.007 -0.018
108 0.065 -0.171 -0.062 -0.171
109 0.390 0.110 0.042 0.110
110 0.141 -0.141 -0.052 -0.141
111 0.310 0.205 0.079 0.205
112 0.220 -0.053 -0.020 -0.053
113 0.052 -0.205 -0.079 -0.205
114 0.038 -0.103 -0.040 -0.103
116 0.133 -0.027 -0.010 -0.027
117 0.147 0.038 0.015 0.038
118 0.378 0.008 0.002 0.008
120 0.124 -0.198 -0.072 -0.198
121 0.165 -0.103 -0.037 -0.103
122 0.467 0.211 0.080 0.211
123 0.323 0.073 0.027 0.073
124 0.348 0.142 0.053 0.142
125 0.063 0.020 0.008 0.020
126 0.046 -0.005 -0.002 -0.005
127 0.050 0.008 0.003 0.008
128 0.455 0.232 0.088 0.232
129 0.320 0.068 0.025 0.068
130 0.344 0.150 0.056 0.150
131 0.247 0.076 0.030 0.076
135 0.169 -0.138 -0.053 -0.138
136 0.030 -0.025 -0.010 -0.025
137 0.158 -0.164 -0.063 -0.164
141 0.456 0.129 0.047 0.129
142 0.312 -0.128 -0.047 -0.128
143 0.299 -0.087 -0.032 -0.087
144 0.510 0.184 0.069 0.184
145 0.386 -0.206 -0.077 -0.206
147 0.296 0.094 0.037 0.094
148 -0.049 -0.448 -0.164 -0.448
149 0.066 0.009 0.004 0.009
150 0.069 -0.044 -0.016 -0.044
151 0.067 -0.054 -0.020 -0.054
152 0.560 0.194 0.072 0.194
153 0.351 -0.066 -0.024 -0.066
154 0.360 -0.260 -0.097 -0.260
155 0.686 0.244 0.088 0.244
156 0.153 -0.162 -0.059 -0.162
157 0.647 0.081 0.029 0.081
158 0.211 -0.128 -0.046 -0.128
159 0.094 -0.032 -0.012 -0.032
160 0.194 -0.160 -0.058 -0.160With factor scores
With controls as factor scoreslavaan 0.6-21 ended normally after 51 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 45
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 122.129 117.428
Degrees of freedom 72 72
P-value (Chi-square) 0.000 0.001
Scaling correction factor 1.040
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 1429.901 1148.570
Degrees of freedom 108 108
P-value 0.000 0.000
Scaling correction factor 1.245
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.962 0.956
Tucker-Lewis Index (TLI) 0.943 0.935
Robust Comparative Fit Index (CFI) 0.964
Robust Tucker-Lewis Index (TLI) 0.945
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2070.895 -2070.895
Scaling correction factor 1.598
for the MLR correction
Loglikelihood unrestricted model (H1) -2009.831 -2009.831
Scaling correction factor 1.255
for the MLR correction
Akaike (AIC) 4231.791 4231.791
Bayesian (BIC) 4380.215 4380.215
Sample-size adjusted Bayesian (SABIC) 4237.650 4237.650
Root Mean Square Error of Approximation:
RMSEA 0.059 0.056
90 Percent confidence interval - lower 0.040 0.037
90 Percent confidence interval - upper 0.077 0.074
P-value H_0: RMSEA <= 0.050 0.198 0.274
P-value H_0: RMSEA >= 0.080 0.024 0.012
Robust RMSEA 0.057
90 Percent confidence interval - lower 0.038
90 Percent confidence interval - upper 0.076
P-value H_0: Robust RMSEA <= 0.050 0.251
P-value H_0: Robust RMSEA >= 0.080 0.019
Standardized Root Mean Square Residual:
SRMR 0.040 0.040
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
IM =~
IM1 1.000 0.802 0.816
IM2 0.875 0.091 9.642 0.000 0.703 0.853
IM3 0.882 0.132 6.675 0.000 0.708 0.739
EEF =~
EEF1 1.000 0.997 0.901
EEF2 1.033 0.061 16.820 0.000 1.029 0.917
EEF3 0.963 0.050 19.089 0.000 0.960 0.893
EEC =~
EEC1 1.000 0.879 0.699
EEC2 1.341 0.134 10.024 0.000 1.179 0.857
EEC3 1.408 0.115 12.286 0.000 1.238 0.945
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) -0.015 0.172 -0.089 0.929 -0.019 -0.007
rwrd1_1 (b_11) 0.357 0.179 1.990 0.047 0.445 0.163
rwrd0_2 (b_02) 0.238 0.200 1.189 0.235 0.296 0.114
rwrd1_2 (b_12) 0.433 0.160 2.704 0.007 0.540 0.200
rwrd0_3 (b_03) 0.259 0.216 1.198 0.231 0.322 0.117
TR_FS (b_TR) 0.095 0.046 2.075 0.038 0.119 0.148
ADT_FS (b_AD) 0.069 0.079 0.879 0.379 0.086 0.070
PEB_yes (b_PE) 0.868 0.130 6.677 0.000 1.081 0.448
EEF ~
rwrd0_1 (c_01) -0.029 0.188 -0.154 0.878 -0.029 -0.011
rwrd1_1 (c_11) 0.124 0.208 0.598 0.550 0.125 0.046
rwrd0_2 (c_02) -0.165 0.220 -0.748 0.454 -0.165 -0.064
rwrd1_2 (c_12) 0.040 0.215 0.188 0.851 0.041 0.015
rwrd0_3 (c_03) -0.243 0.198 -1.232 0.218 -0.244 -0.088
IM (c_IM) 0.623 0.099 6.283 0.000 0.502 0.502
TR_FS (c_TR) 0.046 0.055 0.832 0.405 0.046 0.058
ADT_FS (c_AD) 0.256 0.081 3.162 0.002 0.257 0.208
PEB_yes (c_PE) 0.278 0.178 1.560 0.119 0.279 0.115
EEC ~
rwrd0_1 (d_01) -0.035 0.191 -0.185 0.853 -0.040 -0.015
rwrd1_1 (d_11) 0.017 0.202 0.084 0.933 0.019 0.007
rwrd0_2 (d_02) 0.172 0.195 0.880 0.379 0.196 0.075
rwrd1_2 (d_12) 0.182 0.189 0.962 0.336 0.207 0.077
rwrd0_3 (d_03) 0.111 0.176 0.632 0.527 0.127 0.046
IM (d_IM) 0.110 0.112 0.984 0.325 0.100 0.100
TR_FS (d_TR) 0.059 0.048 1.215 0.224 0.067 0.083
ADT_FS (d_AD) 0.153 0.077 1.981 0.048 0.174 0.141
PEB_yes (d_PE) -0.044 0.148 -0.297 0.766 -0.050 -0.021
EEF 0.422 0.079 5.367 0.000 0.478 0.478
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.324 0.084 3.878 0.000 0.324 0.335
.IM2 0.184 0.049 3.721 0.000 0.184 0.272
.IM3 0.416 0.207 2.006 0.045 0.416 0.453
.EEF1 0.230 0.046 4.993 0.000 0.230 0.188
.EEF2 0.200 0.046 4.308 0.000 0.200 0.159
.EEF3 0.234 0.065 3.624 0.000 0.234 0.203
.EEC1 0.810 0.096 8.405 0.000 0.810 0.511
.EEC2 0.505 0.111 4.525 0.000 0.505 0.266
.EEC3 0.185 0.066 2.813 0.005 0.185 0.108
.IM 0.464 0.083 5.560 0.000 0.721 0.721
.EEF 0.561 0.126 4.442 0.000 0.564 0.564
.EEC 0.457 0.084 5.415 0.000 0.591 0.591
R-Square:
Estimate
IM1 0.665
IM2 0.728
IM3 0.547
EEF1 0.812
EEF2 0.841
EEF3 0.797
EEC1 0.489
EEC2 0.734
EEC3 0.892
IM 0.279
EEF 0.436
EEC 0.409
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.372 0.167 2.230 0.026 0.464 0.170
reward2_IM 0.196 0.181 1.081 0.280 0.244 0.087
reward3_IM -0.259 0.216 -1.198 0.231 -0.322 -0.117
reward_vrgd_IM 0.103 0.111 0.929 0.353 0.129 0.047
reward_EEF_ec1 0.153 0.185 0.827 0.408 0.153 0.057
reward_EEF_ec2 0.205 0.219 0.937 0.349 0.206 0.079
reward_EEF_ec3 0.243 0.198 1.232 0.218 0.244 0.088
reward_man_EEF 0.201 0.118 1.701 0.089 0.201 0.075
ind_rwrd_EEF_1 0.232 0.110 2.116 0.034 0.233 0.085
ind_rwrd_EEF_2 0.122 0.110 1.106 0.269 0.122 0.044
ind_rwrd_EEF_3 -0.161 0.138 -1.170 0.242 -0.162 -0.058
ind_rw__IM_EEF 0.040 0.043 0.928 0.353 0.032 0.012
tt_rwrd_mn_EEF 0.241 0.119 2.021 0.043 0.234 0.086
reward_EEC_ec1 0.052 0.196 0.267 0.790 0.059 0.023
reward_EEC_ec2 0.010 0.172 0.056 0.955 0.011 0.002
reward_EEC_ec3 -0.111 0.176 -0.632 0.527 -0.127 -0.046
reward_man_EEC -0.016 0.103 -0.160 0.873 -0.019 -0.007
ind_rwrd_EEC_1 0.041 0.044 0.924 0.356 0.047 0.017
ind_rwrd_EEC_2 0.022 0.030 0.712 0.477 0.025 0.009
ind_rwrd_EEC_3 -0.028 0.037 -0.766 0.443 -0.032 -0.012
ind_rw__IM_EEC 0.001 0.003 0.435 0.664 0.001 0.000
tt_rwrd_mn_EEC -0.015 0.103 -0.147 0.883 -0.017 -0.007
eco2_vs_c1_EEF -0.110 0.144 -0.764 0.445 -0.110 -0.042
eco3_vs_c1_EEF -0.169 0.136 -1.248 0.212 -0.170 -0.061
eco1_vs_c2_EEF 0.110 0.144 0.764 0.445 0.110 0.042
eco_main_EEF -0.140 0.118 -1.182 0.237 -0.140 -0.051
eco2_vs_ec1_IM 0.165 0.121 1.362 0.173 0.205 0.079
eco3_vs_ec1_IM -0.041 0.136 -0.304 0.761 -0.052 -0.020
eco1_vs_ec2_IM -0.165 0.121 -1.362 0.173 -0.205 -0.079
in_1__2_IM_EEF -0.103 0.080 -1.291 0.197 -0.103 -0.040
in_2__1_IM_EEF 0.103 0.080 1.291 0.197 0.103 0.040
in_3__1_IM_EEF -0.026 0.085 -0.305 0.760 -0.026 -0.010
ind_c_m_IM_EEF 0.038 0.069 0.554 0.580 0.039 0.015
tt_c1_vs_2_EEF 0.007 0.151 0.047 0.962 0.007 0.002
tt_c2_vs_1_EEF -0.007 0.151 -0.047 0.962 -0.007 -0.002
tt_c3_vs_1_EEF -0.195 0.149 -1.306 0.192 -0.196 -0.071
tot_eco_mn_EEF -0.101 0.126 -0.803 0.422 -0.102 -0.037
eco2_vs_c1_EEC 0.186 0.136 1.369 0.171 0.211 0.080
eco3_vs_c1_EEC 0.065 0.129 0.500 0.617 0.074 0.027
eco_main_EEC 0.125 0.117 1.069 0.285 0.143 0.054
in_2__1_IM_EEC 0.018 0.022 0.806 0.420 0.021 0.008
in_3__1_IM_EEC -0.005 0.016 -0.290 0.772 -0.005 -0.002
ind_c_m_IM_EEC 0.007 0.014 0.493 0.622 0.008 0.003
tt_c2_vs_1_EEC 0.204 0.137 1.495 0.135 0.232 0.088
tt_c3_vs_1_EEC 0.060 0.128 0.470 0.638 0.068 0.025
tot_eco_mn_EEC 0.132 0.117 1.130 0.258 0.150 0.057
eco_main_IM 0.062 0.109 0.564 0.573 0.077 0.030
eco3_vs_c2_EEF -0.060 0.149 -0.398 0.690 -0.060 -0.020
in_3__2_IM_EEF -0.128 0.088 -1.462 0.144 -0.129 -0.050
tt_c3_vs_2_EEF -0.188 0.164 -1.144 0.253 -0.189 -0.070
eco3_vs_c2_EEC -0.121 0.124 -0.979 0.327 -0.138 -0.053
in_3__2_IM_EEC -0.023 0.027 -0.830 0.406 -0.026 -0.010
tt_c3_vs_2_EEC -0.144 0.124 -1.162 0.245 -0.164 -0.063
reward_IM_eco1 0.372 0.167 2.230 0.026 0.464 0.170
reward_IM_eco2 0.196 0.181 1.081 0.280 0.244 0.087
reward_IM_eco3 -0.259 0.216 -1.198 0.231 -0.322 -0.117
reward_main_IM 0.103 0.111 0.929 0.353 0.129 0.047
r_3_EEF___1_EE -0.124 0.208 -0.598 0.550 -0.125 -0.046
r_2_EEF___1_EE -0.084 0.213 -0.393 0.694 -0.084 -0.031
r_2_EEC___1_EE 0.165 0.185 0.890 0.373 0.187 0.070
r_3_EEC___2_EE -0.182 0.189 -0.962 0.336 -0.207 -0.077
r_3_EEC___1_EE -0.017 0.202 -0.084 0.933 -0.019 -0.007
rw_2_IM___1_IM 0.077 0.158 0.484 0.629 0.096 0.037
rw_3_IM___1_IM -0.357 0.179 -1.990 0.047 -0.445 -0.163
i__2_EEC___1_E 0.008 0.020 0.427 0.670 0.010 0.004
i__3_EEC___1_E -0.039 0.044 -0.895 0.371 -0.045 -0.016
i__3_EEC___2_E -0.048 0.052 -0.924 0.355 -0.054 -0.020
t__2_EEC___1_E 0.173 0.187 0.925 0.355 0.197 0.073
t__3_EEC___1_E -0.056 0.199 -0.283 0.777 -0.064 -0.023
t__3_EEC___2_E -0.229 0.188 -1.220 0.222 -0.261 -0.097
rwrd_c3_dr_EEF 0.243 0.198 1.232 0.218 0.244 0.088
rwrd_3__IM_EEF -0.161 0.138 -1.170 0.242 -0.162 -0.058
rwrd_c3_tt_EEF 0.082 0.225 0.367 0.714 0.083 0.030
rwrd_c3_dr_EEC -0.111 0.176 -0.632 0.527 -0.127 -0.046
rwrd_3__IM_EEC -0.028 0.037 -0.766 0.443 -0.032 -0.012
rwrd_c3_tt_EEC -0.140 0.170 -0.823 0.410 -0.159 -0.058Modified final with latent
Derived modellavaan 0.6-21 ended normally after 44 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 41
Number of observations 200
Model Test User Model:
Standard Scaled
Test Statistic 227.108 215.506
Degrees of freedom 169 169
P-value (Chi-square) 0.002 0.009
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) 0.974 0.974
Tucker-Lewis Index (TLI) 0.970 0.970
Robust Comparative Fit Index (CFI) 0.978
Robust Tucker-Lewis Index (TLI) 0.974
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3559.244 -3559.244
Scaling correction factor 1.889
for the MLR correction
Loglikelihood unrestricted model (H1) -3445.690 -3445.690
Scaling correction factor 1.217
for the MLR correction
Akaike (AIC) 7200.488 7200.488
Bayesian (BIC) 7335.719 7335.719
Sample-size adjusted Bayesian (SABIC) 7205.827 7205.827
Root Mean Square Error of Approximation:
RMSEA 0.041 0.037
90 Percent confidence interval - lower 0.026 0.020
90 Percent confidence interval - upper 0.055 0.051
P-value H_0: RMSEA <= 0.050 0.846 0.939
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.038
90 Percent confidence interval - lower 0.020
90 Percent confidence interval - upper 0.052
P-value H_0: Robust RMSEA <= 0.050 0.910
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.074 0.074
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 1.286 0.880
TR2 1.101 0.053 20.929 0.000 1.415 0.943
TR3 1.061 0.054 19.747 0.000 1.365 0.914
ADT =~
ADT1 1.000 0.850 0.860
ADT2 1.032 0.082 12.601 0.000 0.877 0.890
ADT3 1.077 0.079 13.654 0.000 0.915 0.853
IM =~
IM1 1.000 0.791 0.804
IM2 0.898 0.079 11.307 0.000 0.710 0.862
IM3 0.894 0.125 7.157 0.000 0.707 0.738
EEF =~
EEF1 1.000 0.980 0.895
EEF2 1.038 0.063 16.516 0.000 1.017 0.916
EEF3 0.968 0.051 19.138 0.000 0.948 0.892
EEC =~
EEC1 1.000 0.867 0.692
EEC2 1.340 0.132 10.129 0.000 1.162 0.850
EEC3 1.425 0.115 12.405 0.000 1.235 0.951
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) -0.008 0.168 -0.050 0.960 -0.011 -0.004
rwrd1_1 (b_11) 0.399 0.184 2.172 0.030 0.504 0.185
rwrd0_2 (b_02) 0.215 0.198 1.085 0.278 0.272 0.104
rwrd1_2 (b_12) 0.419 0.160 2.622 0.009 0.530 0.197
rwrd0_3 (b_03) 0.237 0.213 1.114 0.265 0.300 0.108
PEB_yes (b_PE) 0.892 0.121 7.378 0.000 1.127 0.467
EEF ~
IM (c_IM) 0.727 0.088 8.300 0.000 0.587 0.587
ADT (c_AD) 0.272 0.076 3.603 0.000 0.236 0.236
EEC ~
ADT (d_AD) 0.174 0.074 2.341 0.019 0.171 0.171
EEF (d_EE) 0.484 0.069 6.974 0.000 0.547 0.547
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.525 0.094 5.564 0.000 0.480 0.480
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.481 0.085 5.644 0.000 0.481 0.225
.TR2 0.248 0.065 3.821 0.000 0.248 0.110
.TR3 0.367 0.094 3.913 0.000 0.367 0.165
.ADT1 0.255 0.061 4.193 0.000 0.255 0.261
.ADT2 0.201 0.055 3.658 0.000 0.201 0.207
.ADT3 0.314 0.092 3.414 0.001 0.314 0.272
.IM1 0.342 0.081 4.249 0.000 0.342 0.354
.IM2 0.174 0.043 4.082 0.000 0.174 0.256
.IM3 0.417 0.206 2.026 0.043 0.417 0.455
.EEF1 0.237 0.046 5.162 0.000 0.237 0.198
.EEF2 0.197 0.046 4.297 0.000 0.197 0.160
.EEF3 0.232 0.065 3.575 0.000 0.232 0.205
.EEC1 0.817 0.097 8.435 0.000 0.817 0.521
.EEC2 0.520 0.111 4.700 0.000 0.520 0.278
.EEC3 0.163 0.064 2.532 0.011 0.163 0.096
TR 1.653 0.177 9.318 0.000 1.000 1.000
ADT 0.723 0.096 7.531 0.000 1.000 1.000
.IM 0.466 0.080 5.806 0.000 0.745 0.745
.EEF 0.576 0.129 4.458 0.000 0.600 0.600
.EEC 0.472 0.087 5.422 0.000 0.628 0.628
R-Square:
Estimate
TR1 0.775
TR2 0.890
TR3 0.835
ADT1 0.739
ADT2 0.793
ADT3 0.728
IM1 0.646
IM2 0.744
IM3 0.545
EEF1 0.802
EEF2 0.840
EEF3 0.795
EEC1 0.479
EEC2 0.722
EEC3 0.904
IM 0.255
EEF 0.400
EEC 0.372Model fit comparison
Scaled Chi-Squared Difference Test (method = "satorra.bentler.2010")
lavaan->lavTestLRT():
lavaan NOTE: The "Chisq" column contains standard test statistics, not the
robust test that should be reported per model. A robust difference test is
a function of two standard (not robust) statistics.
Df AIC BIC Chisq Chisq diff RMSEA Df diff Pr(>Chisq)
fit_no_control 65 4280.8 4363.2 116.85
fit_with_control 152 7212.8 7404.1 205.42 81.654 0 87 0.6417
Scaled Chi-Squared Difference Test (method = "satorra.bentler.2010")
lavaan->lavTestLRT():
lavaan NOTE: The "Chisq" column contains standard test statistics, not the
robust test that should be reported per model. A robust difference test is
a function of two standard (not robust) statistics.
Df AIC BIC Chisq Chisq diff RMSEA Df diff
fit_with_control 152 7212.8 7404.1 205.42
fit_with_control_derived 169 7200.5 7335.7 227.11 20.534 0.033133 17
Pr(>Chisq)
fit_with_control
fit_with_control_derived 0.2478