$all
[1] 266Step 4. Reporting
Sample size
Descriptive
Reward groups
no_reward performance_reward
127 139 Eco orientation groups
EEC_focus EEF_focus EEFandEEC_focus
98 91 77 # A tibble: 6 × 5
Condition_reward_name Condition_eco_name total_participants failed_eco_check
<chr> <chr> <int> <int>
1 no_reward EEC_focus 47 8
2 no_reward EEF_focus 42 5
3 no_reward EEFandEEC_focus 38 1
4 performance_reward EEC_focus 51 11
5 performance_reward EEF_focus 49 13
6 performance_reward EEFandEEC_focus 39 1
# ℹ 1 more variable: failed_eco_percentage <dbl>Manipulation check
# A tibble: 6 × 10
Condition_reward_name Condition_eco_name n failed_mani mean_EEF sd_EEF
<chr> <chr> <int> <int> <dbl> <dbl>
1 no_reward EEC_focus 47 8 5.22 1.44
2 no_reward EEF_focus 42 5 5.43 0.872
3 no_reward EEFandEEC_focus 38 1 5.14 1.07
4 performance_reward EEC_focus 51 11 5.48 1.25
5 performance_reward EEF_focus 49 13 5.30 1.48
6 performance_reward EEFandEEC_focus 39 1 5.16 1.27
# ℹ 4 more variables: mean_EEC <dbl>, sd_EEC <dbl>, mean_IM <dbl>, sd_IM <dbl># A tibble: 6 × 7
Condition_reward_name n failed_mani measure mean sd se
<chr> <int> <int> <fct> <dbl> <dbl> <dbl>
1 no_reward 127 14 EEF 5.27 1.16 0.103
2 no_reward 127 14 EEC 4.20 1.28 0.113
3 no_reward 127 14 IM 5.34 1.15 0.102
4 performance_reward 139 25 EEF 5.33 1.34 0.113
5 performance_reward 139 25 EEC 4.31 1.38 0.117
6 performance_reward 139 25 IM 5.43 1.05 0.0890
Exclusion reason
Table of why they were excluded from the sample# A tibble: 1 × 2
reason n_excluded_only_for_that_reason
<chr> <int>
1 bot_flag 1Regression analysis
One way ANOVA
Anova Table (Type III tests)
Response: IM_composite_standardized
Sum Sq Df F value Pr(>F)
(Intercept) 0.001 1 0.0006 0.9801
Condition_reward 0.119 1 0.1181 0.7314
Condition_eco 0.404 2 0.1998 0.8190
Condition_reward:Condition_eco 0.958 2 0.4733 0.6235
Residuals 263.043 260 Anova Table (Type III tests)
Response: EEF_composite_standardized
Sum Sq Df F value Pr(>F)
(Intercept) 0.405 1 0.3970 0.5292
Condition_reward 0.243 1 0.2384 0.6258
Condition_eco 1.165 2 0.5709 0.5657
Condition_reward:Condition_eco 1.151 2 0.5643 0.5694
Residuals 265.205 260 Anova Table (Type III tests)
Response: EEC_composite_standardized
Sum Sq Df F value Pr(>F)
(Intercept) 0.571 1 0.5688 0.4514
Condition_reward 0.251 1 0.2502 0.6174
Condition_eco 0.341 2 0.1700 0.8437
Condition_reward:Condition_eco 0.914 2 0.4555 0.6347
Residuals 260.888 260 ANCOVA
Call:
lm(formula = IM_composite_standardized ~ Condition_reward * Condition_eco +
TR_composite_standardized + ADT_composite_standardized +
PEB_yes, data = data_filtered)
Residuals:
Min 1Q Median 3Q Max
-3.1796 -0.4420 0.0412 0.5574 2.0773
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.73332 0.10542 -6.956 2.89e-11 ***
Condition_reward1 -0.07089 0.05124 -1.383 0.168
Condition_eco1 0.01527 0.07204 0.212 0.832
Condition_eco2 0.09223 0.07060 1.306 0.193
TR_composite_standardized 0.08739 0.05752 1.519 0.130
ADT_composite_standardized 0.29694 0.05713 5.198 4.12e-07 ***
PEB_yes 0.93976 0.12153 7.733 2.39e-13 ***
Condition_reward1:Condition_eco1 -0.03740 0.07192 -0.520 0.603
Condition_reward1:Condition_eco2 -0.05095 0.07042 -0.724 0.470
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.8286 on 257 degrees of freedom
Multiple R-squared: 0.3404, Adjusted R-squared: 0.3199
F-statistic: 16.58 on 8 and 257 DF, p-value: < 2.2e-16
Call:
lm(formula = EEF_composite_standardized ~ Condition_reward *
Condition_eco + IM_composite_standardized + TR_composite_standardized +
ADT_composite_standardized + PEB_yes, data = data_filtered)
Residuals:
Min 1Q Median 3Q Max
-2.99781 -0.33075 0.05968 0.48122 1.40552
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.286476 0.097968 -2.924 0.00376 **
Condition_reward1 -0.027685 0.043845 -0.631 0.52832
Condition_eco1 0.013564 0.061423 0.221 0.82540
Condition_eco2 0.002552 0.060388 0.042 0.96632
IM_composite_standardized 0.461209 0.053180 8.673 4.95e-16 ***
TR_composite_standardized 0.026114 0.049258 0.530 0.59647
ADT_composite_standardized 0.283944 0.051202 5.546 7.29e-08 ***
PEB_yes 0.372750 0.115030 3.240 0.00135 **
Condition_reward1:Condition_eco1 0.061600 0.061342 1.004 0.31623
Condition_reward1:Condition_eco2 -0.038715 0.060095 -0.644 0.52001
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7064 on 256 degrees of freedom
Multiple R-squared: 0.5232, Adjusted R-squared: 0.5065
F-statistic: 31.22 on 9 and 256 DF, p-value: < 2.2e-16
Call:
lm(formula = EEC_composite_standardized ~ Condition_reward *
Condition_eco + IM_composite_standardized + TR_composite_standardized +
ADT_composite_standardized + PEB_yes, data = data_filtered)
Residuals:
Min 1Q Median 3Q Max
-2.3034 -0.4484 0.1389 0.5097 2.0208
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.20851 0.10794 -1.932 0.0545 .
Condition_reward1 -0.04106 0.04831 -0.850 0.3962
Condition_eco1 -0.09020 0.06768 -1.333 0.1838
Condition_eco2 0.08795 0.06654 1.322 0.1874
IM_composite_standardized 0.40523 0.05859 6.916 3.70e-11 ***
TR_composite_standardized 0.07814 0.05427 1.440 0.1512
ADT_composite_standardized 0.23460 0.05641 4.159 4.37e-05 ***
PEB_yes 0.26319 0.12674 2.077 0.0388 *
Condition_reward1:Condition_eco1 -0.02470 0.06759 -0.365 0.7151
Condition_reward1:Condition_eco2 -0.02444 0.06621 -0.369 0.7123
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7784 on 256 degrees of freedom
Multiple R-squared: 0.4134, Adjusted R-squared: 0.3928
F-statistic: 20.05 on 9 and 256 DF, p-value: < 2.2e-16Mediation test
Testing mediation for EEFAnalysis of Variance Table
Model 1: EEF_composite_standardized ~ Condition_reward * Condition_eco +
TR_composite_standardized + ADT_composite_standardized +
PEB_yes
Model 2: EEF_composite_standardized ~ Condition_reward * Condition_eco +
IM_composite_standardized + TR_composite_standardized + ADT_composite_standardized +
PEB_yes
Res.Df RSS Df Sum of Sq F Pr(>F)
1 257 165.30
2 256 127.76 1 37.537 75.215 4.947e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Testing mediation for EECAnalysis of Variance Table
Model 1: EEC_composite_standardized ~ Condition_reward * Condition_eco +
TR_composite_standardized + ADT_composite_standardized +
PEB_yes
Model 2: EEC_composite_standardized ~ Condition_reward * Condition_eco +
IM_composite_standardized + TR_composite_standardized + ADT_composite_standardized +
PEB_yes
Res.Df RSS Df Sum of Sq F Pr(>F)
1 257 184.07
2 256 155.09 1 28.978 47.832 3.698e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Contrasts
ConstrastsFactor analyses
KMOKaiser-Meyer-Olkin factor adequacy
Call: KMO(r = efa_data_good)
Overall MSA = 0.89
MSA for each item =
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2 TR3
0.94 0.87 0.87 0.90 0.91 0.93 0.93 0.87 0.85 0.91 0.85 0.88 0.88 0.80 0.84 Correlation analysis
Bartlett test
R was not square, finding R from data$chisq
[1] 3718.78
$p.value
[1] 0
$df
[1] 105Correlation matrix
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1
IM1 1.0000000 0.7217817 0.6962671 0.6075554 0.6324957 0.6294186 0.5223403
IM2 0.7217817 1.0000000 0.7939946 0.5179707 0.5849395 0.5898033 0.4335730
IM3 0.6962671 0.7939946 1.0000000 0.4691675 0.5230588 0.5513410 0.4994753
EEF1 0.6075554 0.5179707 0.4691675 1.0000000 0.8742423 0.8542768 0.5643156
EEF2 0.6324957 0.5849395 0.5230588 0.8742423 1.0000000 0.8589401 0.5630464
EEF3 0.6294186 0.5898033 0.5513410 0.8542768 0.8589401 1.0000000 0.5495830
EEC1 0.5223403 0.4335730 0.4994753 0.5643156 0.5630464 0.5495830 1.0000000
EEC2 0.5643784 0.4322841 0.4415655 0.5840159 0.6118643 0.5855881 0.6603326
EEC3 0.5682110 0.4071085 0.4437562 0.6037538 0.5952946 0.6066945 0.7404311
ADT1 0.4459339 0.3135159 0.2821201 0.4740485 0.4686815 0.4664108 0.3510239
ADT2 0.3611338 0.2589278 0.2268417 0.4110420 0.3999059 0.4048236 0.3288552
ADT3 0.4444151 0.3632114 0.3138286 0.4793883 0.4608873 0.4492669 0.3684941
TR1 0.3278781 0.2479193 0.2438523 0.3211136 0.2825295 0.2972514 0.2969147
TR2 0.2890801 0.1646781 0.1641455 0.2399697 0.2165107 0.2460140 0.1791497
TR3 0.2873708 0.1924011 0.1913394 0.2945104 0.2590557 0.2919822 0.2321004
EEC2 EEC3 ADT1 ADT2 ADT3 TR1 TR2
IM1 0.5643784 0.5682110 0.4459339 0.3611338 0.4444151 0.3278781 0.2890801
IM2 0.4322841 0.4071085 0.3135159 0.2589278 0.3632114 0.2479193 0.1646781
IM3 0.4415655 0.4437562 0.2821201 0.2268417 0.3138286 0.2438523 0.1641455
EEF1 0.5840159 0.6037538 0.4740485 0.4110420 0.4793883 0.3211136 0.2399697
EEF2 0.6118643 0.5952946 0.4686815 0.3999059 0.4608873 0.2825295 0.2165107
EEF3 0.5855881 0.6066945 0.4664108 0.4048236 0.4492669 0.2972514 0.2460140
EEC1 0.6603326 0.7404311 0.3510239 0.3288552 0.3684941 0.2969147 0.1791497
EEC2 1.0000000 0.8554756 0.3967709 0.3665454 0.4183662 0.2986323 0.1966295
EEC3 0.8554756 1.0000000 0.4222773 0.3782225 0.4097636 0.3617996 0.2682294
ADT1 0.3967709 0.4222773 1.0000000 0.8105538 0.7851342 0.4182331 0.3890333
ADT2 0.3665454 0.3782225 0.8105538 1.0000000 0.8295781 0.3988198 0.3508138
ADT3 0.4183662 0.4097636 0.7851342 0.8295781 1.0000000 0.4255631 0.3550665
TR1 0.2986323 0.3617996 0.4182331 0.3988198 0.4255631 1.0000000 0.8384867
TR2 0.1966295 0.2682294 0.3890333 0.3508138 0.3550665 0.8384867 1.0000000
TR3 0.2296590 0.3092069 0.4172898 0.3791618 0.4260404 0.8290251 0.8673624
TR3
IM1 0.2873708
IM2 0.1924011
IM3 0.1913394
EEF1 0.2945104
EEF2 0.2590557
EEF3 0.2919822
EEC1 0.2321004
EEC2 0.2296590
EEC3 0.3092069
ADT1 0.4172898
ADT2 0.3791618
ADT3 0.4260404
TR1 0.8290251
TR2 0.8673624
TR3 1.0000000
Outliers
Loading required namespace: GPArotationThreshold = 0.35
Loadings:
MR1 MR2 MR3 MR5 MR4
IM1 NA NA NA NA 0.590
IM2 NA NA NA NA 0.896
IM3 NA NA NA NA 0.894
EEF1 0.962 NA NA NA NA
EEF2 0.913 NA NA NA NA
EEF3 0.850 NA NA NA NA
EEC1 NA NA NA 0.623 NA
EEC2 NA NA NA 0.793 NA
EEC3 NA NA NA 1.018 NA
ADT1 NA NA 0.824 NA NA
ADT2 NA NA 0.975 NA NA
ADT3 NA NA 0.866 NA NA
TR1 NA 0.860 NA NA NA
TR2 NA 0.967 NA NA NA
TR3 NA 0.915 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 0.300 0.515 0.666 0.636
2 0.300 1.000 0.458 0.310 0.232
3 0.515 0.458 1.000 0.449 0.351
4 0.666 0.310 0.449 1.000 0.514
5 0.636 0.232 0.351 0.514 1.000
1 2 3 4 5
1 1.000 0.302 0.515 0.669 0.639
2 0.302 1.000 0.459 0.313 0.234
3 0.515 0.459 1.000 0.451 0.353
4 0.669 0.313 0.451 1.000 0.516
5 0.639 0.234 0.353 0.516 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 266
Model Test User Model:
Standard Scaled
Test Statistic 88.248 71.193
Degrees of freedom 24 24
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.240
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2226.288 1274.276
Degrees of freedom 36 36
P-value 0.000 0.000
Scaling correction factor 1.747
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.971 0.962
Tucker-Lewis Index (TLI) 0.956 0.943
Robust Comparative Fit Index (CFI) 0.973
Robust Tucker-Lewis Index (TLI) 0.959
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2993.730 -2993.730
Scaling correction factor 2.253
for the MLR correction
Loglikelihood unrestricted model (H1) -2949.606 -2949.606
Scaling correction factor 1.713
for the MLR correction
Akaike (AIC) 6029.459 6029.459
Bayesian (BIC) 6104.713 6104.713
Sample-size adjusted Bayesian (SABIC) 6038.131 6038.131
Root Mean Square Error of Approximation:
RMSEA 0.100 0.086
90 Percent confidence interval - lower 0.078 0.066
90 Percent confidence interval - upper 0.123 0.107
P-value H_0: RMSEA <= 0.050 0.000 0.003
P-value H_0: RMSEA >= 0.080 0.937 0.701
Robust RMSEA 0.096
90 Percent confidence interval - lower 0.071
90 Percent confidence interval - upper 0.122
P-value H_0: Robust RMSEA <= 0.050 0.002
P-value H_0: Robust RMSEA >= 0.080 0.855
Standardized Root Mean Square Residual:
SRMR 0.052 0.052
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 1.222 0.077 15.933 0.000 1.071 1.372
EEC3 1.269 0.067 18.975 0.000 1.138 1.400
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.013 0.033 30.397 0.000 0.947 1.078
EEF3 0.961 0.038 25.402 0.000 0.887 1.035
IM =~
IM1 1.000 1.000 1.000
IM2 0.998 0.102 9.822 0.000 0.799 1.197
IM3 1.007 0.110 9.118 0.000 0.790 1.223
Std.lv Std.all
1.094 0.774
1.336 0.895
1.388 0.951
1.230 0.927
1.246 0.939
1.182 0.921
1.036 0.831
1.034 0.890
1.043 0.862
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC ~~
EEF 0.942 0.142 6.631 0.000 0.663 1.220
IM 0.667 0.140 4.763 0.000 0.392 0.941
EEF ~~
IM 0.893 0.165 5.427 0.000 0.570 1.215
Std.lv Std.all
0.700 0.700
0.588 0.588
0.701 0.701
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.802 0.086 9.290 0.000 0.633 0.971
.EEC2 0.441 0.084 5.266 0.000 0.277 0.606
.EEC3 0.206 0.052 3.955 0.000 0.104 0.308
.EEF1 0.249 0.047 5.270 0.000 0.156 0.341
.EEF2 0.210 0.039 5.391 0.000 0.134 0.286
.EEF3 0.250 0.053 4.677 0.000 0.145 0.355
.IM1 0.482 0.118 4.086 0.000 0.251 0.713
.IM2 0.282 0.065 4.300 0.000 0.153 0.410
.IM3 0.375 0.167 2.239 0.025 0.047 0.703
EEC 1.197 0.158 7.593 0.000 0.888 1.506
EEF 1.513 0.203 7.459 0.000 1.115 1.910
IM 1.074 0.184 5.847 0.000 0.714 1.434
Std.lv Std.all
0.802 0.401
0.441 0.198
0.206 0.096
0.249 0.141
0.210 0.119
0.250 0.152
0.482 0.310
0.282 0.208
0.375 0.256
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.599
EEC2 0.802
EEC3 0.904
EEF1 0.859
EEF2 0.881
EEF3 0.848
IM1 0.690
IM2 0.792
IM3 0.744Cronbach’s Alpha: EEC EEF IM
0.901 0.949 0.893 Omega: EEC EEF IM
0.915 0.950 0.898 Average Variance Extracted (AVE): EEC EEF IM
0.772 0.863 0.740 Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC
IM "1" "0.7 (0)" "0.59 (0)"
EEF "0.7 (0)" "1" "0.7 (0)"
EEC "0.59 (0)" "0.7 (0)" "1" Diagnostics
Only larger ones lhs op rhs mi epc sepc.lv sepc.all sepc.nox
28 EEC =~ IM1 29.368 0.335 0.367 0.294 0.294
29 EEC =~ IM2 16.164 -0.224 -0.245 -0.211 -0.211
34 EEF =~ IM1 21.743 0.305 0.375 0.300 0.300
37 IM =~ EEC1 10.177 0.245 0.254 0.180 0.180
43 EEC1 ~~ EEC2 10.862 -0.210 -0.210 -0.353 -0.353
78 IM2 ~~ IM3 30.468 0.323 0.323 0.993 0.993Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
43 EEC1 ~~ EEC2 10.862 -0.210 -0.210 -0.353 -0.353
78 IM2 ~~ IM3 30.468 0.323 0.323 0.993 0.993$type
[1] "raw"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.069 0.000
EEC3 0.010 0.009 0.000
EEF1 0.117 0.007 -0.024 0.000
EEF2 0.103 0.047 -0.056 0.008 0.000
EEF3 0.092 0.016 -0.011 0.001 -0.009 0.000
IM1 0.254 0.236 0.189 0.113 0.143 0.149 0.000
IM2 0.047 -0.063 -0.153 -0.092 0.000 0.024 -0.025 0.000
IM3 0.183 -0.023 -0.068 -0.146 -0.071 -0.008 -0.031 0.037 0.000Standardized residuals$type
[1] "standardized"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3
EEC1 0.000
EEC2 -0.906 0.000
EEC3 0.130 0.085 0.000
EEF1 1.323 0.067 -0.241 0.000
EEF2 1.296 0.490 -0.588 0.102 0.000
EEF3 1.147 0.186 -0.125 0.019 -0.151 0.000
IM1 2.769 2.444 1.970 1.164 1.485 1.607 0.000
IM2 0.774 -1.295 -2.959 -1.410 -0.002 0.519 -1.181 0.000
IM3 2.195 -0.424 -1.383 -2.357 -1.424 -0.174 -1.111 1.175 0.000Discriminant validity check lhs op rhs est.std se z pvalue ci.lower ci.upper
1 EEC =~ EEC1 0.774 0.030 25.520 0 0.714 0.833
2 EEC =~ EEC2 0.895 0.022 40.039 0 0.852 0.939
3 EEC =~ EEC3 0.951 0.013 70.993 0 0.924 0.977
4 EEF =~ EEF1 0.927 0.015 59.870 0 0.896 0.957
5 EEF =~ EEF2 0.939 0.014 69.381 0 0.912 0.965
6 EEF =~ EEF3 0.921 0.020 45.100 0 0.881 0.961
7 IM =~ IM1 0.831 0.046 17.921 0 0.740 0.922
8 IM =~ IM2 0.890 0.030 29.572 0 0.831 0.949
9 IM =~ IM3 0.862 0.061 14.070 0 0.742 0.983AVE (IM, EEF, EEC)[1] 0.7419108[1] 0.862645[1] 0.7680704Square root of AVE (IM, EEF, EEC)[1] 0.8613424[1] 0.9287868[1] 0.8763963 lhs rhs est.std
22 EEC EEF 0.700
23 EEC IM 0.588
24 EEF IM 0.701Correlations between square root AVE with correlations (sqrt vs. correlations with the other constructsIM[1] 0.8613424[1] 0.7005488[1] 0.588084EEF[1] 0.9287868[1] 0.7005488[1] 0.6996786EEC[1] 0.8763963[1] 0.588084[1] 0.6996786With controls
lavaan 0.6-21 ended normally after 49 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 40
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 168.885 146.241
Degrees of freedom 80 80
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.155
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3816.831 2704.146
Degrees of freedom 105 105
P-value 0.000 0.000
Scaling correction factor 1.411
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.976 0.975
Tucker-Lewis Index (TLI) 0.969 0.967
Robust Comparative Fit Index (CFI) 0.979
Robust Tucker-Lewis Index (TLI) 0.973
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4954.445 -4954.445
Scaling correction factor 1.904
for the MLR correction
Loglikelihood unrestricted model (H1) -4870.002 -4870.002
Scaling correction factor 1.405
for the MLR correction
Akaike (AIC) 9988.889 9988.889
Bayesian (BIC) 10132.229 10132.229
Sample-size adjusted Bayesian (SABIC) 10005.406 10005.406
Root Mean Square Error of Approximation:
RMSEA 0.065 0.056
90 Percent confidence interval - lower 0.051 0.042
90 Percent confidence interval - upper 0.078 0.069
P-value H_0: RMSEA <= 0.050 0.039 0.228
P-value H_0: RMSEA >= 0.080 0.031 0.001
Robust RMSEA 0.060
90 Percent confidence interval - lower 0.044
90 Percent confidence interval - upper 0.075
P-value H_0: Robust RMSEA <= 0.050 0.140
P-value H_0: Robust RMSEA >= 0.080 0.014
Standardized Root Mean Square Residual:
SRMR 0.048 0.048
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 0.994 0.103 9.621 0.000 0.791 1.196
IM3 1.003 0.113 8.878 0.000 0.781 1.224
EEF =~
EEF1 1.000 1.000 1.000
EEF2 1.011 0.034 30.119 0.000 0.945 1.077
EEF3 0.960 0.038 25.031 0.000 0.885 1.036
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.220 0.076 16.003 0.000 1.071 1.370
EEC3 1.273 0.067 18.898 0.000 1.141 1.405
TR =~
TR1 1.000 1.000 1.000
TR2 1.052 0.041 25.858 0.000 0.972 1.132
TR3 1.030 0.041 24.947 0.000 0.949 1.111
ADT =~
ADT1 1.000 1.000 1.000
ADT2 1.046 0.053 19.785 0.000 0.943 1.150
ADT3 1.132 0.061 18.460 0.000 1.012 1.252
Std.lv Std.all
1.039 0.833
1.033 0.889
1.042 0.861
1.231 0.927
1.245 0.938
1.182 0.921
1.093 0.773
1.334 0.894
1.391 0.953
1.357 0.899
1.428 0.931
1.398 0.928
0.987 0.883
1.033 0.912
1.117 0.903
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
IM ~~
EEF 0.897 0.167 5.383 0.000 0.570 1.224
EEC 0.668 0.142 4.719 0.000 0.390 0.945
TR 0.394 0.131 3.001 0.003 0.137 0.651
ADT 0.427 0.135 3.171 0.002 0.163 0.692
EEF ~~
EEC 0.940 0.142 6.615 0.000 0.661 1.218
TR 0.521 0.128 4.054 0.000 0.269 0.773
ADT 0.643 0.137 4.692 0.000 0.374 0.911
EEC ~~
TR 0.490 0.114 4.313 0.000 0.267 0.712
ADT 0.513 0.105 4.905 0.000 0.308 0.718
TR ~~
ADT 0.631 0.112 5.625 0.000 0.411 0.851
Std.lv Std.all
0.701 0.701
0.588 0.588
0.279 0.279
0.417 0.417
0.699 0.699
0.312 0.312
0.529 0.529
0.330 0.330
0.476 0.476
0.471 0.471
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.IM1 0.476 0.121 3.945 0.000 0.240 0.712
.IM2 0.284 0.067 4.241 0.000 0.153 0.416
.IM3 0.378 0.169 2.236 0.025 0.047 0.710
.EEF1 0.246 0.047 5.208 0.000 0.154 0.339
.EEF2 0.212 0.039 5.366 0.000 0.134 0.289
.EEF3 0.251 0.053 4.702 0.000 0.146 0.355
.EEC1 0.804 0.086 9.328 0.000 0.635 0.973
.EEC2 0.448 0.084 5.335 0.000 0.283 0.613
.EEC3 0.197 0.052 3.773 0.000 0.095 0.300
.TR1 0.435 0.070 6.180 0.000 0.297 0.573
.TR2 0.313 0.066 4.773 0.000 0.184 0.441
.TR3 0.314 0.073 4.290 0.000 0.170 0.457
.ADT1 0.274 0.057 4.833 0.000 0.163 0.385
.ADT2 0.214 0.045 4.726 0.000 0.125 0.303
.ADT3 0.283 0.071 3.960 0.000 0.143 0.422
IM 1.080 0.187 5.762 0.000 0.712 1.447
EEF 1.515 0.203 7.450 0.000 1.117 1.914
EEC 1.195 0.157 7.596 0.000 0.887 1.503
TR 1.842 0.155 11.892 0.000 1.539 2.146
ADT 0.974 0.146 6.689 0.000 0.689 1.259
Std.lv Std.all
0.476 0.306
0.284 0.210
0.378 0.258
0.246 0.140
0.212 0.120
0.251 0.152
0.804 0.402
0.448 0.201
0.197 0.093
0.435 0.191
0.313 0.133
0.314 0.138
0.274 0.220
0.214 0.167
0.283 0.185
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
IM1 0.694
IM2 0.790
IM3 0.742
EEF1 0.860
EEF2 0.880
EEF3 0.848
EEC1 0.598
EEC2 0.799
EEC3 0.907
TR1 0.809
TR2 0.867
TR3 0.862
ADT1 0.780
ADT2 0.833
ADT3 0.815Cronbach’s Alpha: IM EEF EEC TR ADT
0.893 0.949 0.901 0.942 0.926 Omega: IM EEF EEC TR ADT
0.898 0.950 0.915 0.943 0.928 Average Variance Extracted (AVE): IM EEF EEC TR ADT
0.740 0.863 0.772 0.846 0.810 Factor scores$type
[1] "cor.bentler"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.018 0.000
IM3 -0.021 0.029 0.000
EEF1 0.066 -0.060 -0.091 0.000
EEF2 0.085 0.000 -0.043 0.004 0.000
EEF3 0.091 0.016 -0.005 0.000 -0.005 0.000
EEC1 0.144 0.030 0.108 0.063 0.056 0.052 0.000
EEC2 0.127 -0.035 -0.011 0.005 0.026 0.011 -0.031 0.000
EEC3 0.102 -0.091 -0.039 -0.013 -0.029 -0.006 0.004 0.004 0.000
TR1 0.119 0.025 0.028 0.061 0.020 0.039 0.067 0.033 0.079 0.000
TR2 0.073 -0.066 -0.060 -0.029 -0.056 -0.021 -0.058 -0.078 -0.024 0.001
TR3 0.071 -0.038 -0.032 0.026 -0.012 0.026 -0.005 -0.044 0.017 -0.006
ADT1 0.139 -0.014 -0.035 0.041 0.030 0.036 0.026 0.021 0.022 0.044
ADT2 0.044 -0.079 -0.101 -0.037 -0.053 -0.040 -0.007 -0.022 -0.035 0.012
ADT3 0.131 0.029 -0.010 0.036 0.013 0.009 0.036 0.034 0.000 0.043
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.003 0.000
ADT1 0.001 0.031 0.000
ADT2 -0.050 -0.020 0.004 0.000
ADT3 -0.041 0.031 -0.013 0.006 0.000
$cov.z
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.586 0.000
IM3 -0.698 0.750 0.000
EEF1 1.039 -1.237 -1.781 0.000
EEF2 1.367 0.012 -0.993 0.079 0.000
EEF3 1.471 0.403 -0.117 0.004 -0.111 0.000
EEC1 2.733 0.689 2.103 1.183 1.190 1.076 0.000
EEC2 2.354 -0.875 -0.263 0.083 0.461 0.198 -0.640 0.000
EEC3 1.841 -2.382 -0.987 -0.225 -0.508 -0.113 0.081 0.066 0.000
TR1 2.063 0.733 0.730 1.498 0.468 0.875 1.281 0.715 1.719 0.000
TR2 1.431 -1.817 -1.705 -0.615 -1.184 -0.435 -1.056 -1.509 -0.501 0.030
TR3 1.307 -1.039 -0.868 0.618 -0.275 0.555 -0.088 -0.892 0.375 -0.180
ADT1 2.203 -0.359 -0.805 0.764 0.546 0.637 0.476 0.349 0.386 0.864
ADT2 0.668 -2.147 -2.575 -0.691 -1.050 -0.720 -0.135 -0.387 -0.655 0.274
ADT3 1.969 0.822 -0.263 0.741 0.252 0.180 0.720 0.621 0.007 0.909
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.076 0.000
ADT1 0.028 0.604 0.000
ADT2 -1.046 -0.433 0.083 0.000
ADT3 -0.807 0.645 -0.225 0.110 0.000
$summary
cov
srmr 0.048
srmr.se 0.020
srmr.exactfit.z 0.132
srmr.exactfit.pvalue 0.447
usrmr 0.000
usrmr.se 0.026
usrmr.ci.lower -0.044
usrmr.ci.upper 0.044
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -1.887
usrmr.closefit.pvalue 0.970 IM EEF EEC TR ADT
IM 1.000
EEF 0.701 1.000
EEC 0.588 0.699 1.000
TR 0.279 0.312 0.330 1.000
ADT 0.417 0.529 0.476 0.471 1.000Correlation matrixLatent factor correlation matrix with p-values: IM EEF EEC TR ADT
IM "1" "0.7 (0)" "0.59 (0)" "0.28 (0)" "0.42 (0)"
EEF "0.7 (0)" "1" "0.7 (0)" "0.31 (0)" "0.53 (0)"
EEC "0.59 (0)" "0.7 (0)" "1" "0.33 (0)" "0.48 (0)"
TR "0.28 (0)" "0.31 (0)" "0.33 (0)" "1" "0.47 (0)"
ADT "0.42 (0)" "0.53 (0)" "0.48 (0)" "0.47 (0)" "1" Diagnostics
Larger modification indices lhs op rhs mi epc sepc.lv sepc.all sepc.nox
49 IM =~ EEC1 10.342 0.247 0.256 0.181 0.181
56 IM =~ ADT2 11.676 -0.143 -0.148 -0.131 -0.131
58 EEF =~ IM1 21.892 0.306 0.376 0.302 0.302
70 EEC =~ IM1 29.628 0.336 0.367 0.294 0.294
71 EEC =~ IM2 16.302 -0.225 -0.246 -0.212 -0.212
76 EEC =~ TR1 10.173 0.150 0.164 0.109 0.109
82 TR =~ IM1 10.735 0.128 0.174 0.140 0.140
94 ADT =~ IM1 18.432 0.251 0.248 0.199 0.199
120 IM2 ~~ IM3 33.394 0.334 0.334 1.018 1.018
209 ADT1 ~~ ADT3 10.141 -0.169 -0.169 -0.609 -0.609Residuals lhs op rhs mi epc sepc.lv sepc.all sepc.nox
120 IM2 ~~ IM3 33.394 0.334 0.334 1.018 1.018
209 ADT1 ~~ ADT3 10.141 -0.169 -0.169 -0.609 -0.609$type
[1] "raw"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.027 0.000
IM3 -0.032 0.040 0.000
EEF1 0.109 -0.092 -0.146 0.000
EEF2 0.140 0.001 -0.070 0.007 0.000
EEF3 0.146 0.024 -0.007 0.000 -0.008 0.000
EEC1 0.253 0.049 0.185 0.119 0.106 0.095 0.000
EEC2 0.236 -0.060 -0.020 0.010 0.052 0.020 -0.065 0.000
EEC3 0.185 -0.154 -0.068 -0.026 -0.056 -0.011 0.008 0.009 0.000
TR1 0.223 0.043 0.050 0.122 0.039 0.076 0.144 0.075 0.174 0.000
TR2 0.139 -0.118 -0.111 -0.059 -0.113 -0.042 -0.127 -0.178 -0.055 0.003
TR3 0.134 -0.066 -0.058 0.052 -0.025 0.049 -0.010 -0.099 0.038 -0.013
ADT1 0.194 -0.018 -0.047 0.060 0.045 0.052 0.041 0.035 0.036 0.074
ADT2 0.062 -0.104 -0.138 -0.055 -0.079 -0.058 -0.011 -0.036 -0.059 0.021
ADT3 0.202 0.041 -0.015 0.060 0.021 0.015 0.063 0.063 0.001 0.080
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.007 0.000
ADT1 0.002 0.052 0.000
ADT2 -0.086 -0.034 0.006 0.000
ADT3 -0.078 0.058 -0.017 0.008 0.000Standardized residuals$type
[1] "standardized"
$cov
IM1 IM2 IM3 EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 TR1
IM1 0.000
IM2 -0.586 0.000
IM3 -0.698 0.750 0.000
EEF1 1.039 -1.237 -1.781 0.000
EEF2 1.367 0.012 -0.993 0.079 0.000
EEF3 1.471 0.403 -0.117 0.004 -0.111 0.000
EEC1 2.733 0.689 2.103 1.183 1.190 1.076 0.000
EEC2 2.354 -0.875 -0.263 0.083 0.461 0.198 -0.640 0.000
EEC3 1.841 -2.382 -0.987 -0.225 -0.508 -0.113 0.081 0.066 0.000
TR1 2.063 0.733 0.730 1.498 0.468 0.875 1.281 0.715 1.719 0.000
TR2 1.431 -1.817 -1.705 -0.615 -1.184 -0.435 -1.056 -1.509 -0.501 0.030
TR3 1.307 -1.039 -0.868 0.618 -0.275 0.555 -0.088 -0.892 0.375 -0.180
ADT1 2.203 -0.359 -0.805 0.764 0.546 0.637 0.476 0.349 0.386 0.864
ADT2 0.668 -2.147 -2.575 -0.691 -1.050 -0.720 -0.135 -0.387 -0.655 0.274
ADT3 1.969 0.822 -0.263 0.741 0.252 0.180 0.720 0.621 0.007 0.909
TR2 TR3 ADT1 ADT2 ADT3
IM1
IM2
IM3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
TR1
TR2 0.000
TR3 0.076 0.000
ADT1 0.028 0.604 0.000
ADT2 -1.046 -0.433 0.083 0.000
ADT3 -0.807 0.645 -0.225 0.110 0.000Discriminant validity check lhs op rhs est.std se z pvalue ci.lower ci.upper
1 IM =~ IM1 0.833 0.048 17.514 0 0.740 0.926
2 IM =~ IM2 0.889 0.031 28.927 0 0.828 0.949
3 IM =~ IM3 0.861 0.062 13.894 0 0.740 0.983
4 EEF =~ EEF1 0.927 0.016 59.642 0 0.897 0.958
5 EEF =~ EEF2 0.938 0.014 68.378 0 0.911 0.965
6 EEF =~ EEF3 0.921 0.020 45.209 0 0.881 0.961
7 EEC =~ EEC1 0.773 0.030 25.538 0 0.714 0.833
8 EEC =~ EEC2 0.894 0.023 39.701 0 0.850 0.938
9 EEC =~ EEC3 0.953 0.013 71.047 0 0.926 0.979
10 TR =~ TR1 0.899 0.018 50.629 0 0.865 0.934
11 TR =~ TR2 0.931 0.015 60.084 0 0.901 0.961
12 TR =~ TR3 0.928 0.018 52.444 0 0.894 0.963
13 ADT =~ ADT1 0.883 0.027 32.320 0 0.830 0.937
14 ADT =~ ADT2 0.912 0.021 44.107 0 0.872 0.953
15 ADT =~ ADT3 0.903 0.026 35.354 0 0.853 0.953AVE (IM, EEF, EEC, TR, ADT)[1] 0.741753[1] 0.8626871[1] 0.7680379[1] 0.8457896[1] 0.8094758Square root of AVE (IM, EEF, EEC)[1] 0.8612508[1] 0.9288095[1] 0.8763777[1] 0.9196682[1] 0.8997087 lhs rhs est.std
36 IM EEF 0.701
37 IM EEC 0.588
38 IM TR 0.279
39 IM ADT 0.417
40 EEF EEC 0.699
41 EEF TR 0.312
42 EEF ADT 0.529
43 EEC TR 0.330
44 EEC ADT 0.476
45 TR ADT 0.471Correlations between square root AVE with correlations (sqrt vs. correlations with the other constructsIM[1] 0.8612508[1] 0.70124[1] 0.587883EEF[1] 0.9288095[1] 0.70124[1] 0.6985059EEC[1] 0.8763777[1] 0.587883[1] 0.6985059TR[1] 0.9196682[1] 0.4712095[1] 0.2791861ADT[1] 0.8997087[1] 0.4712095[1] 0.2791861[1] 0.4168336SEM
Without control variables
Without control variableslavaan 0.6-21 ended normally after 86 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 64
Number of observations 266
Number of missing patterns 1
Model Test User Model:
Standard Scaled
Test Statistic 312.753 288.183
Degrees of freedom 146 146
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.085
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3879.567 3139.657
Degrees of freedom 180 180
P-value 0.000 0.000
Scaling correction factor 1.236
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.955 0.952
Tucker-Lewis Index (TLI) 0.944 0.941
Robust Comparative Fit Index (CFI) 0.961
Robust Tucker-Lewis Index (TLI) 0.951
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4995.011 -4995.011
Scaling correction factor 1.552
for the MLR correction
Loglikelihood unrestricted model (H1) -4838.634 -4838.634
Scaling correction factor 1.227
for the MLR correction
Akaike (AIC) 10118.021 10118.021
Bayesian (BIC) 10347.365 10347.365
Sample-size adjusted Bayesian (SABIC) 10144.449 10144.449
Root Mean Square Error of Approximation:
RMSEA 0.066 0.061
90 Percent confidence interval - lower 0.056 0.051
90 Percent confidence interval - upper 0.076 0.070
P-value H_0: RMSEA <= 0.050 0.006 0.041
P-value H_0: RMSEA >= 0.080 0.008 0.000
Robust RMSEA 0.061
90 Percent confidence interval - lower 0.050
90 Percent confidence interval - upper 0.072
P-value H_0: Robust RMSEA <= 0.050 0.054
P-value H_0: Robust RMSEA >= 0.080 0.002
Standardized Root Mean Square Residual:
SRMR 0.164 0.164
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 1.034 0.829
IM2 1.002 0.102 9.782 0.000 1.036 0.891
IM3 1.010 0.111 9.138 0.000 1.044 0.863
EEF =~
EEF1 1.000 1.230 0.927
EEF2 1.013 0.033 30.514 0.000 1.246 0.939
EEF3 0.961 0.038 25.508 0.000 1.182 0.921
EEC =~
EEC1 1.000 1.094 0.774
EEC2 1.223 0.077 15.873 0.000 1.338 0.897
EEC3 1.267 0.067 18.949 0.000 1.386 0.949
TR =~
TR1 1.000 1.355 0.898
TR2 1.055 0.040 26.180 0.000 1.430 0.932
TR3 1.032 0.041 25.234 0.000 1.398 0.928
ADT =~
ADT1 1.000 0.982 0.879
ADT2 1.061 0.055 19.460 0.000 1.042 0.921
ADT3 1.132 0.060 18.827 0.000 1.112 0.899
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.113 0.214 0.527 0.598 0.109 0.042
rwrd0_2 (b_02) -0.027 0.232 -0.116 0.908 -0.026 -0.010
rwrd1_2 (b_12) 0.206 0.206 0.998 0.318 0.199 0.078
rwrd0_3 (b_03) -0.141 0.251 -0.562 0.574 -0.136 -0.048
rwrd1_3 (b_13) -0.233 0.239 -0.975 0.330 -0.226 -0.080
EEF ~
rwrd1_1 (c_11) -0.225 0.195 -1.157 0.247 -0.183 -0.071
rwrd0_2 (c_02) -0.187 0.179 -1.049 0.294 -0.152 -0.058
rwrd1_2 (c_12) -0.126 0.171 -0.736 0.462 -0.102 -0.040
rwrd0_3 (c_03) -0.176 0.184 -0.957 0.338 -0.143 -0.050
rwrd1_3 (c_13) -0.066 0.203 -0.325 0.745 -0.054 -0.019
IM (c_IM) 0.835 0.071 11.725 0.000 0.702 0.702
EEC ~
rwrd1_1 (d_11) 0.089 0.200 0.444 0.657 0.081 0.031
rwrd0_2 (d_02) 0.120 0.207 0.582 0.561 0.110 0.042
rwrd1_2 (d_12) 0.201 0.189 1.061 0.289 0.183 0.072
rwrd0_3 (d_03) 0.151 0.189 0.797 0.425 0.138 0.048
rwrd1_3 (d_13) 0.102 0.219 0.464 0.643 0.093 0.033
IM (d_IM) 0.620 0.064 9.751 0.000 0.585 0.585
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEF ~~
.EEC 0.392 0.097 4.033 0.000 0.506 0.506
TR ~~
ADT 0.624 0.112 5.587 0.000 0.469 0.469
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 5.108 0.161 31.685 0.000 5.108 4.095
.IM2 5.608 0.161 34.775 0.000 5.608 4.825
.IM3 5.431 0.161 33.795 0.000 5.431 4.490
.EEF1 5.321 0.140 38.016 0.000 5.321 4.009
.EEF2 5.461 0.137 39.970 0.000 5.461 4.115
.EEF3 5.503 0.130 42.434 0.000 5.503 4.287
.EEC1 4.094 0.143 28.675 0.000 4.094 2.896
.EEC2 4.087 0.171 23.961 0.000 4.087 2.739
.EEC3 4.191 0.175 23.885 0.000 4.191 2.870
.TR1 3.718 0.093 40.180 0.000 3.718 2.464
.TR2 3.722 0.094 39.587 0.000 3.722 2.427
.TR3 3.429 0.092 37.135 0.000 3.429 2.277
.ADT1 5.301 0.068 77.391 0.000 5.301 4.745
.ADT2 5.256 0.069 75.749 0.000 5.256 4.644
.ADT3 5.192 0.076 68.435 0.000 5.192 4.196
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.487 0.119 4.098 0.000 0.487 0.313
.IM2 0.278 0.064 4.341 0.000 0.278 0.206
.IM3 0.373 0.166 2.249 0.025 0.373 0.255
.EEF1 0.248 0.048 5.208 0.000 0.248 0.141
.EEF2 0.209 0.039 5.411 0.000 0.209 0.119
.EEF3 0.252 0.054 4.690 0.000 0.252 0.153
.EEC1 0.801 0.086 9.291 0.000 0.801 0.401
.EEC2 0.437 0.084 5.229 0.000 0.437 0.196
.EEC3 0.211 0.052 4.022 0.000 0.211 0.099
.TR1 0.442 0.070 6.318 0.000 0.442 0.194
.TR2 0.308 0.065 4.756 0.000 0.308 0.131
.TR3 0.313 0.073 4.319 0.000 0.313 0.138
.ADT1 0.283 0.056 5.025 0.000 0.283 0.227
.ADT2 0.195 0.043 4.492 0.000 0.195 0.153
.ADT3 0.294 0.073 4.019 0.000 0.294 0.192
.IM 1.047 0.187 5.612 0.000 0.980 0.980
.EEF 0.767 0.135 5.673 0.000 0.507 0.507
.EEC 0.780 0.106 7.341 0.000 0.651 0.651
TR 1.836 0.155 11.881 0.000 1.000 1.000
ADT 0.965 0.145 6.647 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.687
IM2 0.794
IM3 0.745
EEF1 0.859
EEF2 0.881
EEF3 0.847
EEC1 0.599
EEC2 0.804
EEC3 0.901
TR1 0.806
TR2 0.869
TR3 0.862
ADT1 0.773
ADT2 0.847
ADT3 0.808
IM 0.020
EEF 0.493
EEC 0.349With control variables
With controls_r0e1 reference grouplavaan 0.6-21 ended normally after 103 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 73
Number of observations 266
Number of missing patterns 1
Model Test User Model:
Standard Scaled
Test Statistic 235.373 217.311
Degrees of freedom 152 152
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.983
Robust Tucker-Lewis Index (TLI) 0.979
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4915.372 -4915.372
Scaling correction factor 1.492
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.216
for the MLR correction
Akaike (AIC) 9976.744 9976.744
Bayesian (BIC) 10238.339 10238.339
Sample-size adjusted Bayesian (SABIC) 10006.888 10006.888
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.056 0.051
P-value H_0: RMSEA <= 0.050 0.741 0.924
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.039
90 Percent confidence interval - lower 0.024
90 Percent confidence interval - upper 0.052
P-value H_0: Robust RMSEA <= 0.050 0.914
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.054 0.054
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 1.014 0.827
IM2 0.993 0.101 9.881 0.000 1.007 0.883
IM3 1.003 0.110 9.113 0.000 1.017 0.856
EEF =~
EEF1 1.000 1.201 0.925
EEF2 1.010 0.033 30.739 0.000 1.212 0.935
EEF3 0.958 0.038 25.056 0.000 1.150 0.916
EEC =~
EEC1 1.000 1.074 0.768
EEC2 1.220 0.076 15.985 0.000 1.310 0.891
EEC3 1.270 0.067 18.865 0.000 1.364 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.853 0.000 1.428 0.931
TR3 1.030 0.041 24.977 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.047 0.053 19.807 0.000 1.033 0.913
ADT3 1.132 0.061 18.534 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.270 0.172 1.567 0.117 0.266 0.103
rwrd0_2 (b_02) 0.083 0.189 0.439 0.661 0.082 0.031
rwrd1_2 (b_12) 0.350 0.166 2.111 0.035 0.345 0.136
rwrd0_3 (b_03) 0.013 0.214 0.060 0.952 0.013 0.004
rwrd1_3 (b_13) -0.030 0.214 -0.139 0.889 -0.029 -0.010
TR (b_TR) 0.055 0.047 1.181 0.238 0.074 0.074
ADT (b_AD) 0.333 0.101 3.284 0.001 0.324 0.324
PEB_yes (b_PE) 1.027 0.156 6.598 0.000 1.013 0.433
EEF ~
rwrd1_1 (c_11) -0.118 0.187 -0.631 0.528 -0.098 -0.038
rwrd0_2 (c_02) -0.151 0.169 -0.890 0.373 -0.125 -0.048
rwrd1_2 (c_12) -0.004 0.165 -0.023 0.981 -0.003 -0.001
rwrd0_3 (c_03) -0.150 0.173 -0.871 0.384 -0.125 -0.044
rwrd1_3 (c_13) -0.009 0.186 -0.046 0.964 -0.007 -0.003
IM (c_IM) 0.605 0.078 7.749 0.000 0.511 0.511
TR (c_TR) 0.012 0.049 0.236 0.813 0.013 0.013
ADT (c_AD) 0.361 0.079 4.560 0.000 0.297 0.297
PEB_yes (c_PE) 0.398 0.165 2.407 0.016 0.332 0.142
EEC ~
rwrd1_1 (d_11) 0.173 0.193 0.895 0.371 0.161 0.063
rwrd0_2 (d_02) 0.160 0.204 0.785 0.433 0.149 0.057
rwrd1_2 (d_12) 0.312 0.177 1.763 0.078 0.291 0.114
rwrd0_3 (d_03) 0.167 0.177 0.942 0.346 0.155 0.054
rwrd1_3 (d_13) 0.153 0.194 0.791 0.429 0.143 0.051
IM (d_IM) 0.429 0.084 5.100 0.000 0.405 0.405
TR (d_TR) 0.072 0.050 1.454 0.146 0.091 0.091
ADT (d_AD) 0.277 0.078 3.541 0.000 0.255 0.255
PEB_yes (d_PE) 0.254 0.163 1.556 0.120 0.237 0.101
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEF ~~
.EEC 0.283 0.071 3.974 0.000 0.427 0.427
TR ~~
ADT 0.631 0.112 5.627 0.000 0.471 0.471
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 4.201 0.201 20.903 0.000 4.201 3.425
.IM2 4.707 0.198 23.733 0.000 4.707 4.128
.IM3 4.521 0.197 22.980 0.000 4.521 3.805
.EEF1 4.407 0.178 24.738 0.000 4.407 3.397
.EEF2 4.539 0.178 25.538 0.000 4.539 3.500
.EEF3 4.628 0.173 26.721 0.000 4.628 3.686
.EEC1 3.458 0.183 18.945 0.000 3.458 2.474
.EEC2 3.312 0.215 15.387 0.000 3.312 2.253
.EEC3 3.384 0.225 15.054 0.000 3.384 2.357
.TR1 3.718 0.093 40.180 0.000 3.718 2.464
.TR2 3.722 0.094 39.587 0.000 3.722 2.427
.TR3 3.429 0.092 37.135 0.000 3.429 2.277
.ADT1 5.301 0.068 77.391 0.000 5.301 4.745
.ADT2 5.256 0.069 75.749 0.000 5.256 4.644
.ADT3 5.192 0.076 68.435 0.000 5.192 4.196
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.476 0.118 4.018 0.000 0.476 0.316
.IM2 0.286 0.065 4.401 0.000 0.286 0.220
.IM3 0.376 0.168 2.243 0.025 0.376 0.267
.EEF1 0.242 0.048 5.053 0.000 0.242 0.144
.EEF2 0.213 0.039 5.500 0.000 0.213 0.126
.EEF3 0.253 0.054 4.728 0.000 0.253 0.161
.EEC1 0.802 0.086 9.348 0.000 0.802 0.410
.EEC2 0.446 0.083 5.355 0.000 0.446 0.206
.EEC3 0.201 0.053 3.819 0.000 0.201 0.098
.TR1 0.436 0.070 6.186 0.000 0.436 0.191
.TR2 0.311 0.066 4.749 0.000 0.311 0.132
.TR3 0.315 0.073 4.324 0.000 0.315 0.139
.ADT1 0.274 0.056 4.897 0.000 0.274 0.220
.ADT2 0.214 0.045 4.715 0.000 0.214 0.167
.ADT3 0.283 0.071 4.004 0.000 0.283 0.185
.IM 0.679 0.076 8.887 0.000 0.660 0.660
.EEF 0.643 0.105 6.141 0.000 0.446 0.446
.EEC 0.683 0.089 7.706 0.000 0.592 0.592
TR 1.842 0.155 11.886 0.000 1.000 1.000
ADT 0.974 0.145 6.698 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.684
IM2 0.780
IM3 0.733
EEF1 0.856
EEF2 0.874
EEF3 0.839
EEC1 0.590
EEC2 0.794
EEC3 0.902
TR1 0.809
TR2 0.868
TR3 0.861
ADT1 0.780
ADT2 0.833
ADT3 0.815
IM 0.340
EEF 0.554
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.270 0.172 1.567 0.117 0.266 0.103
reward2_IM 0.267 0.176 1.519 0.129 0.263 0.105
reward3_IM -0.043 0.241 -0.177 0.859 -0.042 -0.015
reward_avg_IM 0.165 0.116 1.417 0.156 0.162 0.064
eco2_noRwrd_IM 0.083 0.189 0.439 0.661 0.082 0.031
eco3_noRwrd_IM 0.013 0.214 0.060 0.952 0.013 0.004
eco2_reward_IM 0.080 0.159 0.505 0.614 0.079 0.033
eco3_reward_IM -0.299 0.201 -1.491 0.136 -0.295 -0.113
eco2_IM 0.081 0.122 0.668 0.504 0.080 0.032
eco3_IM -0.143 0.146 -0.983 0.326 -0.141 -0.054
eco_avg_IM -0.031 0.113 -0.274 0.784 -0.030 -0.011
reward1_EEF -0.118 0.187 -0.631 0.528 -0.098 -0.038
reward2_EEF 0.147 0.179 0.821 0.412 0.122 0.047
reward3_EEF 0.142 0.197 0.720 0.472 0.118 0.041
reward_avg_EEF 0.057 0.110 0.519 0.604 0.047 0.017
ind_rewrd1_EEF 0.163 0.103 1.582 0.114 0.136 0.053
ind_rewrd2_EEF 0.161 0.108 1.498 0.134 0.135 0.053
ind_rewrd3_EEF -0.026 0.146 -0.177 0.859 -0.022 -0.008
ind_rwrd_v_EEF 0.100 0.070 1.416 0.157 0.083 0.033
tt_rwrd_vg_EEF 0.157 0.121 1.295 0.195 0.130 0.049
reward1_EEC 0.173 0.193 0.895 0.371 0.161 0.063
reward2_EEC 0.152 0.192 0.794 0.427 0.142 0.058
reward3_EEC -0.013 0.185 -0.071 0.943 -0.012 -0.004
reward_avg_EEC 0.104 0.110 0.949 0.342 0.097 0.039
ind_rewrd1_EEC 0.116 0.077 1.505 0.132 0.108 0.042
ind_rewrd2_EEC 0.114 0.078 1.461 0.144 0.107 0.042
ind_rewrd3_EEC -0.018 0.103 -0.177 0.859 -0.017 -0.006
ind_rwrd_v_EEC 0.071 0.052 1.366 0.172 0.066 0.026
tt_rwrd_vg_EEC 0.175 0.115 1.517 0.129 0.163 0.065
eco2_dirct_EEF -0.018 0.126 -0.146 0.884 -0.015 -0.006
eco3_dirct_EEF -0.021 0.135 -0.153 0.879 -0.017 -0.004
ec_vg_drct_EEF -0.019 0.113 -0.172 0.863 -0.016 -0.005
eco2_IM_effect 0.081 0.122 0.668 0.504 0.080 0.032
eco3_IM_effect -0.143 0.146 -0.983 0.326 -0.141 -0.054
ind_eco2_EEF 0.049 0.074 0.665 0.506 0.041 0.016
ind_eco3_EEF -0.087 0.088 -0.985 0.325 -0.072 -0.028
ind_eco_vg_EEF -0.019 0.068 -0.274 0.784 -0.016 -0.006
tot_eco2_EEF 0.031 0.145 0.213 0.831 0.026 0.011
tot_eco3_EEF -0.107 0.150 -0.717 0.473 -0.089 -0.032
tot_eco_vg_EEF -0.038 0.127 -0.300 0.764 -0.032 -0.011
eco2_dirct_EEC 0.149 0.137 1.091 0.275 0.139 0.054
eco3_dirct_EEC 0.073 0.133 0.553 0.580 0.068 0.021
ec_vg_drct_EEC 0.111 0.118 0.946 0.344 0.104 0.038
ec2_IM_ffc_EEC 0.081 0.122 0.668 0.504 0.080 0.032
ec3_IM_ffc_EEC -0.143 0.146 -0.983 0.326 -0.141 -0.054
ind_eco2_EEC 0.035 0.053 0.662 0.508 0.033 0.013
ind_eco3_EEC -0.061 0.064 -0.967 0.334 -0.057 -0.022
ind_eco_vg_EEC -0.013 0.048 -0.273 0.785 -0.012 -0.005
tot_eco2_EEC 0.184 0.148 1.247 0.212 0.172 0.067
tot_eco3_EEC 0.012 0.135 0.089 0.929 0.011 -0.001
tot_eco_vg_EEC 0.098 0.123 0.797 0.425 0.091 0.033Without mediation
Without IM mediationlavaan 0.6-21 ended normally after 109 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 71
Number of observations 266
Number of missing patterns 1
Model Test User Model:
Standard Scaled
Test Statistic 303.022 279.414
Degrees of freedom 154 154
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.084
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.960 0.959
Tucker-Lewis Index (TLI) 0.950 0.948
Robust Comparative Fit Index (CFI) 0.966
Robust Tucker-Lewis Index (TLI) 0.957
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4949.197 -4949.197
Scaling correction factor 1.501
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.216
for the MLR correction
Akaike (AIC) 10040.394 10040.394
Bayesian (BIC) 10294.822 10294.822
Sample-size adjusted Bayesian (SABIC) 10069.712 10069.712
Root Mean Square Error of Approximation:
RMSEA 0.060 0.055
90 Percent confidence interval - lower 0.050 0.045
90 Percent confidence interval - upper 0.070 0.065
P-value H_0: RMSEA <= 0.050 0.046 0.184
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.056
90 Percent confidence interval - lower 0.044
90 Percent confidence interval - upper 0.067
P-value H_0: Robust RMSEA <= 0.050 0.190
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.090 0.090
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 0.992 0.808
IM2 1.026 0.100 10.279 0.000 1.017 0.893
IM3 1.035 0.109 9.474 0.000 1.027 0.865
EEF =~
EEF1 1.000 1.206 0.931
EEF2 1.002 0.033 30.391 0.000 1.208 0.932
EEF3 0.950 0.039 24.148 0.000 1.146 0.913
EEC =~
EEC1 1.000 1.071 0.766
EEC2 1.221 0.076 16.058 0.000 1.307 0.889
EEC3 1.277 0.068 18.895 0.000 1.368 0.953
TR =~
TR1 1.000 1.358 0.900
TR2 1.052 0.041 25.739 0.000 1.428 0.931
TR3 1.029 0.041 24.917 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.040 0.052 19.853 0.000 1.026 0.907
ADT3 1.135 0.062 18.302 0.000 1.120 0.905
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.274 0.168 1.631 0.103 0.276 0.107
rwrd0_2 (b_02) 0.083 0.184 0.450 0.652 0.084 0.032
rwrd1_2 (b_12) 0.344 0.163 2.110 0.035 0.347 0.137
rwrd0_3 (b_03) 0.014 0.208 0.067 0.947 0.014 0.005
rwrd1_3 (b_13) -0.027 0.214 -0.128 0.898 -0.027 -0.010
TR (b_TR) 0.044 0.047 0.924 0.355 0.060 0.060
ADT (b_AD) 0.348 0.107 3.262 0.001 0.346 0.346
PEB_yes (b_PE) 0.994 0.154 6.435 0.000 1.002 0.428
EEF ~
rwrd1_1 (c_11) 0.041 0.210 0.195 0.846 0.034 0.013
rwrd0_2 (c_02) -0.106 0.203 -0.523 0.601 -0.088 -0.033
rwrd1_2 (c_12) 0.205 0.184 1.117 0.264 0.170 0.067
rwrd0_3 (c_03) -0.147 0.189 -0.774 0.439 -0.122 -0.043
rwrd1_3 (c_13) -0.030 0.206 -0.145 0.885 -0.025 -0.009
IM 0.000 0.000 0.000
TR (c_TR) 0.040 0.057 0.696 0.487 0.045 0.045
ADT (c_AD) 0.587 0.092 6.366 0.000 0.480 0.480
PEB_yes (c_PE) 1.021 0.148 6.900 0.000 0.847 0.362
EEC ~
rwrd1_1 (d_11) 0.286 0.197 1.455 0.146 0.267 0.104
rwrd0_2 (d_02) 0.191 0.220 0.866 0.386 0.178 0.068
rwrd1_2 (d_12) 0.457 0.182 2.506 0.012 0.427 0.168
rwrd0_3 (d_03) 0.167 0.174 0.961 0.337 0.156 0.055
rwrd1_3 (d_13) 0.139 0.195 0.714 0.475 0.130 0.046
IM 0.000 0.000 0.000
TR (d_TR) 0.093 0.054 1.710 0.087 0.118 0.118
ADT (d_AD) 0.431 0.079 5.449 0.000 0.397 0.397
PEB_yes (d_PE) 0.687 0.142 4.821 0.000 0.641 0.274
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEF ~~
.EEC 0.446 0.081 5.532 0.000 0.532 0.532
TR ~~
ADT 0.633 0.112 5.647 0.000 0.472 0.472
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 4.225 0.201 21.049 0.000 4.225 3.444
.IM2 4.703 0.197 23.841 0.000 4.703 4.128
.IM3 4.517 0.197 22.940 0.000 4.517 3.805
.EEF1 4.410 0.179 24.616 0.000 4.410 3.401
.EEF2 4.547 0.178 25.574 0.000 4.547 3.508
.EEF3 4.637 0.173 26.810 0.000 4.637 3.695
.EEC1 3.467 0.182 19.003 0.000 3.467 2.480
.EEC2 3.323 0.216 15.410 0.000 3.323 2.260
.EEC3 3.390 0.225 15.037 0.000 3.390 2.362
.TR1 3.718 0.093 40.180 0.000 3.718 2.464
.TR2 3.722 0.094 39.587 0.000 3.722 2.427
.TR3 3.429 0.092 37.135 0.000 3.429 2.277
.ADT1 5.301 0.068 77.391 0.000 5.301 4.745
.ADT2 5.256 0.069 75.749 0.000 5.256 4.644
.ADT3 5.192 0.076 68.435 0.000 5.192 4.196
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.522 0.127 4.120 0.000 0.522 0.347
.IM2 0.264 0.055 4.827 0.000 0.264 0.203
.IM3 0.355 0.158 2.253 0.024 0.355 0.252
.EEF1 0.225 0.048 4.661 0.000 0.225 0.134
.EEF2 0.220 0.041 5.345 0.000 0.220 0.131
.EEF3 0.263 0.055 4.746 0.000 0.263 0.167
.EEC1 0.808 0.086 9.427 0.000 0.808 0.413
.EEC2 0.453 0.083 5.429 0.000 0.453 0.209
.EEC3 0.190 0.052 3.639 0.000 0.190 0.092
.TR1 0.434 0.071 6.155 0.000 0.434 0.191
.TR2 0.312 0.066 4.739 0.000 0.312 0.133
.TR3 0.315 0.073 4.331 0.000 0.315 0.139
.ADT1 0.274 0.056 4.895 0.000 0.274 0.220
.ADT2 0.227 0.047 4.818 0.000 0.227 0.177
.ADT3 0.276 0.070 3.975 0.000 0.276 0.181
.IM 0.643 0.074 8.711 0.000 0.653 0.653
.EEF 0.882 0.115 7.642 0.000 0.606 0.606
.EEC 0.796 0.106 7.522 0.000 0.694 0.694
TR 1.843 0.155 11.892 0.000 1.000 1.000
ADT 0.974 0.145 6.695 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.653
IM2 0.797
IM3 0.748
EEF1 0.866
EEF2 0.869
EEF3 0.833
EEC1 0.587
EEC2 0.791
EEC3 0.908
TR1 0.809
TR2 0.867
TR3 0.861
ADT1 0.780
ADT2 0.823
ADT3 0.819
IM 0.347
EEF 0.394
EEC 0.306Model fit comparison
No controls vs. With controls
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 Df diff Pr(>Chisq)
fit_no_control 146 10118.0 10347 312.75
fit_with_control 152 9976.7 10238 235.37 -52.873 6 1With controls vs. no mediation
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 Df diff Pr(>Chisq)
fit_with_control 152 9976.7 10238 235.37
fit_no_mediation 154 10040.4 10295 303.02 24.46 2 4.882e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Mediation analysis
Mediation analysis lhs op rhs label
130 tot_reward_avg_EEF := reward_avg_EEF+ind_reward_avg_EEF tot_reward_avg_EEF
139 tot_reward_avg_EEC := reward_avg_EEC+ind_reward_avg_EEC tot_reward_avg_EEC
150 tot_eco_avg_EEF := eco_avg_direct_EEF+ind_eco_avg_EEF tot_eco_avg_EEF
161 tot_eco_avg_EEC := eco_avg_direct_EEC+ind_eco_avg_EEC tot_eco_avg_EEC
est se z pvalue ci.lower ci.upper std.lv std.all std.nox
130 0.157 0.123 1.273 0.203 -0.092 0.400 0.130 0.049 0.130
139 0.175 0.119 1.473 0.141 -0.056 0.408 0.163 0.065 0.163
150 -0.038 0.128 -0.298 0.765 -0.293 0.213 -0.032 -0.011 -0.032
161 0.098 0.124 0.794 0.427 -0.138 0.349 0.091 0.033 0.091Main effect of sustainability focus
1 2 3
-0.5 -0.5 1.0 1 2 3
-1 1 0 [1] -3.5[1] -0.01993667[1] -0.06578947[1] 0.02631579lavaan 0.6-21 ended normally after 89 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 64
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 196.301 176.713
Degrees of freedom 116 116
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.111
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3914.342 3033.774
Degrees of freedom 150 150
P-value 0.000 0.000
Scaling correction factor 1.290
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.979 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.982
Robust Tucker-Lewis Index (TLI) 0.977
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4919.397 -4919.397
Scaling correction factor 1.563
for the MLR correction
Loglikelihood unrestricted model (H1) -4821.247 -4821.247
Scaling correction factor 1.272
for the MLR correction
Akaike (AIC) 9966.794 9966.794
Bayesian (BIC) 10196.138 10196.138
Sample-size adjusted Bayesian (SABIC) 9993.222 9993.222
Root Mean Square Error of Approximation:
RMSEA 0.051 0.044
90 Percent confidence interval - lower 0.038 0.031
90 Percent confidence interval - upper 0.063 0.056
P-value H_0: RMSEA <= 0.050 0.432 0.767
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.047
90 Percent confidence interval - lower 0.032
90 Percent confidence interval - upper 0.060
P-value H_0: Robust RMSEA <= 0.050 0.639
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.061 0.061
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 1.016 0.829
IM2 0.989 0.101 9.801 0.000 1.004 0.881
IM3 1.000 0.111 8.999 0.000 1.016 0.856
EEF =~
EEF1 1.000 1.199 0.925
EEF2 1.009 0.033 30.625 0.000 1.210 0.934
EEF3 0.958 0.038 24.977 0.000 1.149 0.916
EEC =~
EEC1 1.000 1.073 0.768
EEC2 1.219 0.076 16.012 0.000 1.308 0.890
EEC3 1.270 0.067 18.837 0.000 1.363 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.836 0.000 1.428 0.931
TR3 1.030 0.041 24.972 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.046 0.053 19.812 0.000 1.032 0.912
ADT3 1.132 0.061 18.514 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
c1 (IM_V) -0.129 0.088 -1.457 0.145 -0.127 -0.086
c2 (IM_E) 0.038 0.062 0.621 0.535 0.038 0.032
TR (IM_T) 0.055 0.047 1.164 0.245 0.074 0.074
ADT (IM_A) 0.332 0.102 3.268 0.001 0.323 0.323
PEB_ys (IM_P) 1.015 0.158 6.426 0.000 1.000 0.427
EEF ~
c1 (EEF_V) -0.006 0.078 -0.078 0.938 -0.005 -0.003
c2 (EEF_E) -0.005 0.064 -0.085 0.932 -0.005 -0.004
IM (EEF_I) 0.606 0.077 7.825 0.000 0.513 0.513
TR (EEF_T) 0.011 0.049 0.226 0.821 0.013 0.013
ADT (EEF_A) 0.358 0.080 4.477 0.000 0.295 0.295
PEB_ys (EEF_P) 0.404 0.164 2.461 0.014 0.337 0.144
EEC ~
c1 (EEC_V) -0.000 0.070 -0.006 0.995 -0.000 -0.000
c2 (EEC_E) 0.075 0.062 1.198 0.231 0.069 0.059
IM (EEC_I) 0.176 0.093 1.899 0.058 0.167 0.167
TR (EEC_T) 0.066 0.045 1.483 0.138 0.084 0.084
ADT (EEC_A) 0.115 0.071 1.615 0.106 0.106 0.106
PEB_ys (EEC_P) 0.055 0.142 0.387 0.699 0.051 0.022
EEF (EEC__) 0.437 0.073 5.998 0.000 0.488 0.488
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.631 0.112 5.629 0.000 0.471 0.471
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 4.329 0.144 30.083 0.000 4.329 3.532
.IM2 4.837 0.139 34.817 0.000 4.837 4.245
.IM3 4.652 0.138 33.742 0.000 4.652 3.918
.EEF1 4.408 0.137 32.225 0.000 4.408 3.402
.EEF2 4.540 0.141 32.152 0.000 4.540 3.506
.EEF3 4.629 0.140 33.020 0.000 4.629 3.691
.EEC1 3.685 0.133 27.777 0.000 3.685 2.637
.EEC2 3.590 0.151 23.781 0.000 3.590 2.443
.EEC3 3.672 0.154 23.807 0.000 3.672 2.560
.TR1 3.718 0.093 40.180 0.000 3.718 2.464
.TR2 3.722 0.094 39.587 0.000 3.722 2.427
.TR3 3.429 0.092 37.135 0.000 3.429 2.277
.ADT1 5.301 0.068 77.391 0.000 5.301 4.745
.ADT2 5.256 0.069 75.749 0.000 5.256 4.644
.ADT3 5.192 0.076 68.435 0.000 5.192 4.196
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.471 0.119 3.943 0.000 0.471 0.313
.IM2 0.290 0.066 4.357 0.000 0.290 0.223
.IM3 0.378 0.170 2.222 0.026 0.378 0.268
.EEF1 0.242 0.048 5.088 0.000 0.242 0.144
.EEF2 0.213 0.039 5.486 0.000 0.213 0.127
.EEF3 0.252 0.053 4.729 0.000 0.252 0.161
.EEC1 0.801 0.086 9.330 0.000 0.801 0.410
.EEC2 0.448 0.083 5.409 0.000 0.448 0.207
.EEC3 0.200 0.052 3.837 0.000 0.200 0.097
.TR1 0.436 0.070 6.184 0.000 0.436 0.191
.TR2 0.312 0.066 4.752 0.000 0.312 0.133
.TR3 0.315 0.073 4.317 0.000 0.315 0.139
.ADT1 0.274 0.056 4.882 0.000 0.274 0.220
.ADT2 0.215 0.046 4.713 0.000 0.215 0.168
.ADT3 0.282 0.071 3.997 0.000 0.282 0.184
.IM 0.694 0.076 9.075 0.000 0.672 0.672
.EEF 0.647 0.105 6.145 0.000 0.450 0.450
.EEC 0.564 0.078 7.249 0.000 0.490 0.490
TR 1.842 0.155 11.887 0.000 1.000 1.000
ADT 0.974 0.145 6.699 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.687
IM2 0.777
IM3 0.732
EEF1 0.856
EEF2 0.873
EEF3 0.839
EEC1 0.590
EEC2 0.793
EEC3 0.903
TR1 0.809
TR2 0.867
TR3 0.861
ADT1 0.780
ADT2 0.832
ADT3 0.816
IM 0.328
EEF 0.550
EEC 0.510
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
tt_dlVsSngl_IM -0.129 0.088 -1.457 0.145 -0.127 -0.086
tt_EECvsEEF_IM 0.038 0.062 0.621 0.535 0.038 0.032
ind_dVS_EEF_IM -0.078 0.054 -1.454 0.146 -0.065 -0.044
i_EECEEF_EEF_I 0.023 0.037 0.618 0.537 0.019 0.016
tt_dlVsSng_EEF -0.084 0.088 -0.958 0.338 -0.070 -0.048
tt_EECvEEF_EEF 0.018 0.074 0.240 0.810 0.015 0.012
ind_dVS_EEC_IM -0.023 0.019 -1.166 0.244 -0.021 -0.014
i_EECEEF_EEC_I 0.007 0.011 0.587 0.557 0.006 0.005
ind_VS_EEC_EEF -0.003 0.034 -0.078 0.938 -0.002 -0.002
i_EECEEF_EEC_E -0.002 0.028 -0.085 0.932 -0.002 -0.002
i_VS_EEC_IM_EE -0.034 0.025 -1.391 0.164 -0.032 -0.022
i_EECEEF_EEC_I 0.010 0.016 0.621 0.535 0.009 0.008
ind_dlVsS_EEC_ -0.059 0.050 -1.194 0.232 -0.055 -0.038
in_EECEEF_EEC_ 0.014 0.039 0.373 0.709 0.013 0.011
tt_dlVsSng_EEC -0.060 0.078 -0.770 0.441 -0.056 -0.038
tt_EECvEEF_EEC 0.089 0.074 1.197 0.231 0.083 0.070 lhs op
16 IM ~
17 IM ~
18 IM ~
19 IM ~
20 IM ~
21 EEF ~
22 EEF ~
23 EEF ~
24 EEF ~
25 EEF ~
26 EEF ~
27 EEC ~
28 EEC ~
29 EEC ~
30 EEC ~
31 EEC ~
32 EEC ~
33 EEC ~
84 tot_dualVsSingle_IM :=
85 tot_EECvsEEF_IM :=
86 ind_dualVsSingle_EEF_viaIM :=
87 ind_EECvsEEF_EEF_viaIM :=
88 tot_dualVsSingle_EEF :=
89 tot_EECvsEEF_EEF :=
90 ind_dualVsSingle_EEC_viaIM :=
91 ind_EECvsEEF_EEC_viaIM :=
92 ind_dualVsSingle_EEC_viaEEF :=
93 ind_EECvsEEF_EEC_viaEEF :=
94 ind_dualVsSingle_EEC_viaIM_EEF :=
95 ind_EECvsEEF_EEC_viaIM_EEF :=
96 ind_dualVsSingle_EEC_total :=
97 ind_EECvsEEF_EEC_total :=
98 tot_dualVsSingle_EEC :=
99 tot_EECvsEEF_EEC :=
rhs
16 c1
17 c2
18 TR
19 ADT
20 PEB_yes
21 c1
22 c2
23 IM
24 TR
25 ADT
26 PEB_yes
27 c1
28 c2
29 IM
30 TR
31 ADT
32 PEB_yes
33 EEF
84 IM_dualVsSingle
85 IM_EECvsEEF
86 IM_dualVsSingle*EEF_IM
87 IM_EECvsEEF*EEF_IM
88 EEF_dualVsSingle+ind_dualVsSingle_EEF_viaIM
89 EEF_EECvsEEF+ind_EECvsEEF_EEF_viaIM
90 IM_dualVsSingle*EEC_IM
91 IM_EECvsEEF*EEC_IM
92 EEF_dualVsSingle*EEC_from_EEF
93 EEF_EECvsEEF*EEC_from_EEF
94 IM_dualVsSingle*EEF_IM*EEC_from_EEF
95 IM_EECvsEEF*EEF_IM*EEC_from_EEF
96 ind_dualVsSingle_EEC_viaIM+ind_dualVsSingle_EEC_viaEEF+ind_dualVsSingle_EEC_viaIM_EEF
97 ind_EECvsEEF_EEC_viaIM+ind_EECvsEEF_EEC_viaEEF+ind_EECvsEEF_EEC_viaIM_EEF
98 EEC_dualVsSingle+ind_dualVsSingle_EEC_total
99 EEC_EECvsEEF+ind_EECvsEEF_EEC_total
label est
16 IM_dualVsSingle -0.129
17 IM_EECvsEEF 0.038
18 IM_TR 0.055
19 IM_ADT 0.332
20 IM_PEB 1.015
21 EEF_dualVsSingle -0.006
22 EEF_EECvsEEF -0.005
23 EEF_IM 0.606
24 EEF_TR 0.011
25 EEF_ADT 0.358
26 EEF_PEB 0.404
27 EEC_dualVsSingle 0.000
28 EEC_EECvsEEF 0.075
29 EEC_IM 0.176
30 EEC_TR 0.066
31 EEC_ADT 0.115
32 EEC_PEB 0.055
33 EEC_from_EEF 0.437
84 tot_dualVsSingle_IM -0.129
85 tot_EECvsEEF_IM 0.038
86 ind_dualVsSingle_EEF_viaIM -0.078
87 ind_EECvsEEF_EEF_viaIM 0.023
88 tot_dualVsSingle_EEF -0.084
89 tot_EECvsEEF_EEF 0.018
90 ind_dualVsSingle_EEC_viaIM -0.023
91 ind_EECvsEEF_EEC_viaIM 0.007
92 ind_dualVsSingle_EEC_viaEEF -0.003
93 ind_EECvsEEF_EEC_viaEEF -0.002
94 ind_dualVsSingle_EEC_viaIM_EEF -0.034
95 ind_EECvsEEF_EEC_viaIM_EEF 0.010
96 ind_dualVsSingle_EEC_total -0.059
97 ind_EECvsEEF_EEC_total 0.014
98 tot_dualVsSingle_EEC -0.060
99 tot_EECvsEEF_EEC 0.089$stat
[1] 2.51532
$df
[1] 2
$p.value
[1] 0.2843186
$se
[1] "robust.huber.white"$stat
[1] 1.450643
$df
[1] 4
$p.value
[1] 0.8353469
$se
[1] "robust.huber.white"$stat
[1] 3.950032
$df
[1] 6
$p.value
[1] 0.6834385
$se
[1] "robust.huber.white"$stat
[1] 3.937667
$df
[1] 6
$p.value
[1] 0.6851116
$se
[1] "robust.huber.white" [1] lhs op rhs label est se z pvalue
[9] ci.lower ci.upper std.lv std.all std.nox
<0 rows> (or 0-length row.names)Modified final with latent
Derived modellavaan 0.6-21 ended normally after 46 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 39
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 242.590 216.508
Degrees of freedom 126 126
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.120
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3921.988 3031.910
Degrees of freedom 150 150
P-value 0.000 0.000
Scaling correction factor 1.294
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.969 0.969
Tucker-Lewis Index (TLI) 0.963 0.963
Robust Comparative Fit Index (CFI) 0.973
Robust Tucker-Lewis Index (TLI) 0.968
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4938.719 -4938.719
Scaling correction factor 1.877
for the MLR correction
Loglikelihood unrestricted model (H1) -4817.424 -4817.424
Scaling correction factor 1.299
for the MLR correction
Akaike (AIC) 9955.438 9955.438
Bayesian (BIC) 10095.194 10095.194
Sample-size adjusted Bayesian (SABIC) 9971.542 9971.542
Root Mean Square Error of Approximation:
RMSEA 0.059 0.052
90 Percent confidence interval - lower 0.048 0.041
90 Percent confidence interval - upper 0.070 0.063
P-value H_0: RMSEA <= 0.050 0.092 0.373
P-value H_0: RMSEA >= 0.080 0.001 0.000
Robust RMSEA 0.055
90 Percent confidence interval - lower 0.042
90 Percent confidence interval - upper 0.067
P-value H_0: Robust RMSEA <= 0.050 0.245
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.106 0.106
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 1.358 0.900
TR2 1.051 0.041 25.729 0.000 1.427 0.931
TR3 1.029 0.041 25.036 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.985 0.882
ADT2 1.054 0.053 19.748 0.000 1.038 0.918
ADT3 1.129 0.059 18.995 0.000 1.112 0.899
IM =~
IM1 1.000 1.016 0.822
IM2 1.005 0.093 10.807 0.000 1.021 0.888
IM3 1.015 0.104 9.740 0.000 1.030 0.860
EEF =~
EEF1 1.000 1.167 0.919
EEF2 1.012 0.033 30.480 0.000 1.180 0.931
EEF3 0.962 0.038 25.437 0.000 1.122 0.914
EEC =~
EEC1 1.000 1.054 0.761
EEC2 1.223 0.076 16.010 0.000 1.289 0.888
EEC3 1.276 0.067 19.045 0.000 1.345 0.950
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_11) -0.096 0.145 -0.665 0.506 -0.095 -0.035
rwrd1_2 (b_12) 0.265 0.136 1.945 0.052 0.261 0.103
TR (b_TR) 0.171 0.056 3.043 0.002 0.228 0.228
PEB_yes (b_PE) 1.116 0.168 6.624 0.000 1.099 0.470
EEF ~
IM (c_IM) 0.713 0.070 10.179 0.000 0.620 0.620
ADT (c_AD) 0.374 0.076 4.949 0.000 0.316 0.316
EEC ~
ADT (d_AD) 0.158 0.065 2.430 0.015 0.147 0.147
EEF (d_EE) 0.560 0.054 10.282 0.000 0.620 0.620
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.636 0.113 5.622 0.000 0.476 0.476
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.TR1 0.434 0.070 6.179 0.000 0.434 0.190
.TR2 0.314 0.066 4.764 0.000 0.314 0.134
.TR3 0.316 0.072 4.395 0.000 0.316 0.139
.ADT1 0.277 0.056 4.912 0.000 0.277 0.222
.ADT2 0.202 0.044 4.581 0.000 0.202 0.158
.ADT3 0.294 0.071 4.126 0.000 0.294 0.192
.IM1 0.496 0.113 4.370 0.000 0.496 0.325
.IM2 0.281 0.058 4.814 0.000 0.281 0.212
.IM3 0.372 0.164 2.267 0.023 0.372 0.260
.EEF1 0.250 0.047 5.342 0.000 0.250 0.155
.EEF2 0.214 0.039 5.514 0.000 0.214 0.133
.EEF3 0.249 0.052 4.760 0.000 0.249 0.165
.EEC1 0.808 0.086 9.341 0.000 0.808 0.421
.EEC2 0.447 0.083 5.365 0.000 0.447 0.212
.EEC3 0.195 0.052 3.761 0.000 0.195 0.097
TR 1.844 0.155 11.883 0.000 1.000 1.000
ADT 0.971 0.145 6.693 0.000 1.000 1.000
.IM 0.739 0.095 7.755 0.000 0.717 0.717
.EEF 0.644 0.107 6.001 0.000 0.473 0.473
.EEC 0.583 0.083 7.031 0.000 0.524 0.524
R-Square:
Estimate
TR1 0.810
TR2 0.866
TR3 0.861
ADT1 0.778
ADT2 0.842
ADT3 0.808
IM1 0.675
IM2 0.788
IM3 0.740
EEF1 0.845
EEF2 0.867
EEF3 0.835
EEC1 0.579
EEC2 0.788
EEC3 0.903
IM 0.283
EEF 0.527
EEC 0.476Interaction graphs
IM
Call:
lm(formula = IM_mean ~ IM_FS, data = data_filtered)
Residuals:
Min 1Q Median 3Q Max
-0.42894 -0.07085 -0.00271 0.06123 0.34761
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.383459 0.007097 758.5 <2e-16 ***
IM_FS 1.099988 0.007168 153.5 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1158 on 264 degrees of freedom
Multiple R-squared: 0.9889, Adjusted R-squared: 0.9889
F-statistic: 2.355e+04 on 1 and 264 DF, p-value: < 2.2e-16
EEF
Call:
lm(formula = EEF_mean ~ EEF_FS, data = data_filtered)
Residuals:
Min 1Q Median 3Q Max
-0.210060 -0.056013 -0.005797 0.042750 0.298292
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.296992 0.004996 1060.2 <2e-16 ***
EEF_FS 1.038514 0.004156 249.9 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.08149 on 264 degrees of freedom
Multiple R-squared: 0.9958, Adjusted R-squared: 0.9958
F-statistic: 6.245e+04 on 1 and 264 DF, p-value: < 2.2e-16
EEC
Call:
lm(formula = EEC_mean ~ EEC_FS, data = data_filtered)
Residuals:
Min 1Q Median 3Q Max
-0.75712 -0.12418 0.04295 0.14348 0.58566
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.25564 0.01389 306.29 <2e-16 ***
EEC_FS 1.23578 0.01310 94.37 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2266 on 264 degrees of freedom
Multiple R-squared: 0.9712, Adjusted R-squared: 0.9711
F-statistic: 8905 on 1 and 264 DF, p-value: < 2.2e-16 Min. 1st Qu. Median Mean 3rd Qu. Max.
-2.7506 -0.7209 0.2052 0.0000 0.7136 2.0916 Min. 1st Qu. Median Mean 3rd Qu. Max.
0.8565 3.3648 4.5092 4.2556 5.1375 6.8404 [1] 0.9854987
Comparing difference reference groups
Reference group: r0e1
lavaan 0.6-21 ended normally after 64 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 235.373 217.311
Degrees of freedom 152 152
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.981
Robust Tucker-Lewis Index (TLI) 0.976
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4915.372 -4915.372
Scaling correction factor 1.619
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.231
for the MLR correction
Akaike (AIC) 9946.744 9946.744
Bayesian (BIC) 10154.587 10154.587
Sample-size adjusted Bayesian (SABIC) 9970.694 9970.694
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.056 0.051
P-value H_0: RMSEA <= 0.050 0.741 0.924
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.054
P-value H_0: Robust RMSEA <= 0.050 0.861
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.056 0.056
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 1.014 0.827
IM2 0.993 0.101 9.881 0.000 1.007 0.883
IM3 1.003 0.110 9.113 0.000 1.017 0.856
EEF =~
EEF1 1.000 1.201 0.925
EEF2 1.010 0.033 30.739 0.000 1.212 0.935
EEF3 0.958 0.038 25.056 0.000 1.150 0.916
EEC =~
EEC1 1.000 1.074 0.768
EEC2 1.220 0.076 15.985 0.000 1.310 0.891
EEC3 1.270 0.067 18.865 0.000 1.364 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.853 0.000 1.428 0.931
TR3 1.030 0.041 24.977 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.047 0.053 19.807 0.000 1.033 0.913
ADT3 1.132 0.061 18.534 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd1_1 (b_11) 0.270 0.172 1.567 0.117 0.266 0.103
rwrd0_2 (b_02) 0.083 0.189 0.439 0.661 0.082 0.031
rwrd1_2 (b_12) 0.350 0.166 2.111 0.035 0.345 0.136
rwrd0_3 (b_03) 0.013 0.214 0.060 0.952 0.013 0.004
rwrd1_3 (b_13) -0.030 0.214 -0.139 0.889 -0.029 -0.010
TR (b_TR) 0.055 0.047 1.181 0.238 0.074 0.074
ADT (b_AD) 0.333 0.101 3.284 0.001 0.324 0.324
PEB_yes (b_PE) 1.027 0.156 6.598 0.000 1.013 0.433
EEF ~
rwrd1_1 (c_11) -0.118 0.187 -0.631 0.528 -0.098 -0.038
rwrd0_2 (c_02) -0.151 0.169 -0.890 0.373 -0.125 -0.048
rwrd1_2 (c_12) -0.004 0.165 -0.023 0.981 -0.003 -0.001
rwrd0_3 (c_03) -0.150 0.173 -0.871 0.384 -0.125 -0.044
rwrd1_3 (c_13) -0.009 0.186 -0.046 0.964 -0.007 -0.003
IM (c_IM) 0.605 0.078 7.749 0.000 0.511 0.511
TR (c_TR) 0.012 0.049 0.236 0.813 0.013 0.013
ADT (c_AD) 0.361 0.079 4.560 0.000 0.297 0.297
PEB_yes (c_PE) 0.398 0.165 2.408 0.016 0.332 0.142
EEC ~
rwrd1_1 (d_11) 0.173 0.193 0.895 0.371 0.161 0.063
rwrd0_2 (d_02) 0.160 0.204 0.785 0.433 0.149 0.057
rwrd1_2 (d_12) 0.312 0.177 1.763 0.078 0.291 0.114
rwrd0_3 (d_03) 0.167 0.177 0.942 0.346 0.155 0.054
rwrd1_3 (d_13) 0.153 0.194 0.791 0.429 0.143 0.051
IM (d_IM) 0.429 0.084 5.100 0.000 0.405 0.405
TR (d_TR) 0.072 0.050 1.454 0.146 0.091 0.091
ADT (d_AD) 0.277 0.078 3.541 0.000 0.255 0.255
PEB_yes (d_PE) 0.254 0.163 1.556 0.120 0.237 0.101
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEF ~~
.EEC 0.283 0.071 3.974 0.000 0.427 0.427
TR ~~
ADT 0.631 0.112 5.627 0.000 0.471 0.471
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.476 0.118 4.018 0.000 0.476 0.316
.IM2 0.286 0.065 4.401 0.000 0.286 0.220
.IM3 0.376 0.168 2.243 0.025 0.376 0.267
.EEF1 0.242 0.048 5.053 0.000 0.242 0.144
.EEF2 0.213 0.039 5.500 0.000 0.213 0.126
.EEF3 0.253 0.054 4.728 0.000 0.253 0.161
.EEC1 0.802 0.086 9.348 0.000 0.802 0.410
.EEC2 0.446 0.083 5.355 0.000 0.446 0.206
.EEC3 0.201 0.053 3.819 0.000 0.201 0.098
.TR1 0.436 0.070 6.186 0.000 0.436 0.191
.TR2 0.311 0.066 4.749 0.000 0.311 0.132
.TR3 0.315 0.073 4.324 0.000 0.315 0.139
.ADT1 0.274 0.056 4.897 0.000 0.274 0.220
.ADT2 0.214 0.045 4.715 0.000 0.214 0.167
.ADT3 0.283 0.071 4.004 0.000 0.283 0.185
.IM 0.679 0.076 8.887 0.000 0.660 0.660
.EEF 0.643 0.105 6.141 0.000 0.446 0.446
.EEC 0.683 0.089 7.706 0.000 0.592 0.592
TR 1.842 0.155 11.886 0.000 1.000 1.000
ADT 0.974 0.145 6.698 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.684
IM2 0.780
IM3 0.733
EEF1 0.856
EEF2 0.874
EEF3 0.839
EEC1 0.590
EEC2 0.794
EEC3 0.902
TR1 0.809
TR2 0.868
TR3 0.861
ADT1 0.780
ADT2 0.833
ADT3 0.815
IM 0.340
EEF 0.554
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.270 0.172 1.567 0.117 0.266 0.103
reward2_IM 0.267 0.176 1.519 0.129 0.263 0.105
reward3_IM -0.043 0.241 -0.177 0.859 -0.042 -0.015
reward_avg_IM 0.165 0.116 1.417 0.156 0.162 0.064
eco2_noRwrd_IM 0.083 0.189 0.439 0.661 0.082 0.031
eco3_noRwrd_IM 0.013 0.214 0.060 0.952 0.013 0.004
eco2_reward_IM 0.080 0.159 0.505 0.614 0.079 0.033
eco3_reward_IM -0.299 0.201 -1.491 0.136 -0.295 -0.113
eco2_IM 0.081 0.122 0.668 0.504 0.080 0.032
eco3_IM -0.143 0.146 -0.983 0.326 -0.141 -0.054
eco_avg_IM -0.031 0.113 -0.274 0.784 -0.030 -0.011
reward1_EEF -0.118 0.187 -0.631 0.528 -0.098 -0.038
reward2_EEF 0.147 0.179 0.821 0.412 0.122 0.047
reward3_EEF 0.142 0.197 0.720 0.472 0.118 0.041
reward_avg_EEF 0.057 0.110 0.519 0.604 0.047 0.017
ind_rewrd1_EEF 0.163 0.103 1.582 0.114 0.136 0.053
ind_rewrd2_EEF 0.161 0.108 1.498 0.134 0.135 0.053
ind_rewrd3_EEF -0.026 0.146 -0.177 0.859 -0.022 -0.008
ind_rwrd_v_EEF 0.100 0.070 1.416 0.157 0.083 0.033
tt_rwrd_vg_EEF 0.157 0.121 1.295 0.195 0.130 0.049
reward1_EEC 0.173 0.193 0.895 0.371 0.161 0.063
reward2_EEC 0.152 0.192 0.794 0.427 0.142 0.058
reward3_EEC -0.013 0.185 -0.071 0.943 -0.012 -0.004
reward_avg_EEC 0.104 0.110 0.949 0.342 0.097 0.039
ind_rewrd1_EEC 0.116 0.077 1.505 0.132 0.108 0.042
ind_rewrd2_EEC 0.114 0.078 1.461 0.144 0.107 0.042
ind_rewrd3_EEC -0.018 0.103 -0.177 0.859 -0.017 -0.006
ind_rwrd_v_EEC 0.071 0.052 1.366 0.172 0.066 0.026
tt_rwrd_vg_EEC 0.175 0.115 1.517 0.129 0.163 0.065
eco2_dirct_EEF -0.018 0.126 -0.146 0.884 -0.015 -0.006
eco3_dirct_EEF -0.021 0.135 -0.153 0.879 -0.017 -0.004
ec_vg_drct_EEF -0.019 0.113 -0.172 0.863 -0.016 -0.005
eco2_IM_effect 0.081 0.122 0.668 0.504 0.080 0.032
eco3_IM_effect -0.143 0.146 -0.983 0.326 -0.141 -0.054
ind_eco2_EEF 0.049 0.074 0.665 0.506 0.041 0.016
ind_eco3_EEF -0.087 0.088 -0.985 0.324 -0.072 -0.028
ind_eco_vg_EEF -0.019 0.068 -0.274 0.784 -0.016 -0.006
tot_eco2_EEF 0.031 0.145 0.213 0.831 0.026 0.011
tot_eco3_EEF -0.107 0.150 -0.717 0.473 -0.089 -0.032
tot_eco_vg_EEF -0.038 0.127 -0.300 0.764 -0.032 -0.011
eco2_dirct_EEC 0.149 0.137 1.091 0.275 0.139 0.054
eco3_dirct_EEC 0.073 0.133 0.553 0.580 0.068 0.021
ec_vg_drct_EEC 0.111 0.118 0.946 0.344 0.104 0.038
ec2_IM_ffc_EEC 0.081 0.122 0.668 0.504 0.080 0.032
ec3_IM_ffc_EEC -0.143 0.146 -0.983 0.326 -0.141 -0.054
ind_eco2_EEC 0.035 0.053 0.662 0.508 0.033 0.013
ind_eco3_EEC -0.061 0.064 -0.967 0.333 -0.057 -0.022
ind_eco_vg_EEC -0.013 0.048 -0.273 0.785 -0.012 -0.005
tot_eco2_EEC 0.184 0.148 1.247 0.212 0.172 0.067
tot_eco3_EEC 0.012 0.135 0.088 0.929 0.011 -0.001
tot_eco_vg_EEC 0.098 0.123 0.797 0.425 0.091 0.033Reference group: r1e1 - check with r0e1
With controls_r1e1 reference grouplavaan 0.6-21 ended normally after 55 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 235.373 217.311
Degrees of freedom 152 152
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.981
Robust Tucker-Lewis Index (TLI) 0.976
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4915.372 -4915.372
Scaling correction factor 1.619
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.231
for the MLR correction
Akaike (AIC) 9946.744 9946.744
Bayesian (BIC) 10154.587 10154.587
Sample-size adjusted Bayesian (SABIC) 9970.694 9970.694
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.056 0.051
P-value H_0: RMSEA <= 0.050 0.741 0.924
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.054
P-value H_0: Robust RMSEA <= 0.050 0.861
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.056 0.056
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 1.014 0.827
IM2 0.993 0.101 9.881 0.000 1.007 0.883
IM3 1.003 0.110 9.113 0.000 1.017 0.856
EEF =~
EEF1 1.000 1.201 0.925
EEF2 1.010 0.033 30.739 0.000 1.212 0.935
EEF3 0.958 0.038 25.056 0.000 1.150 0.916
EEC =~
EEC1 1.000 1.074 0.768
EEC2 1.220 0.076 15.985 0.000 1.310 0.891
EEC3 1.270 0.067 18.865 0.000 1.364 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.853 0.000 1.428 0.931
TR3 1.030 0.041 24.977 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.047 0.053 19.807 0.000 1.033 0.913
ADT3 1.132 0.061 18.534 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) -0.270 0.172 -1.567 0.117 -0.266 -0.097
rwrd0_2 (b_02) -0.187 0.178 -1.049 0.294 -0.184 -0.070
rwrd1_2 (b_12) 0.080 0.159 0.505 0.614 0.079 0.031
rwrd0_3 (b_03) -0.257 0.202 -1.269 0.205 -0.253 -0.089
rwrd1_3 (b_13) -0.299 0.201 -1.491 0.136 -0.295 -0.104
TR (b_TR) 0.055 0.047 1.181 0.238 0.074 0.074
ADT (b_AD) 0.333 0.101 3.284 0.001 0.324 0.324
PEB_yes (b_PE) 1.027 0.156 6.598 0.000 1.013 0.433
EEF ~
rwrd0_1 (c_01) 0.190 0.182 1.044 0.296 0.158 0.058
rwrd0_2 (c_02) -0.027 0.178 -0.153 0.878 -0.023 -0.009
rwrd1_2 (c_12) 0.056 0.167 0.337 0.736 0.047 0.018
rwrd0_3 (c_03) -0.030 0.180 -0.166 0.868 -0.025 -0.009
rwrd1_3 (c_13) 0.118 0.195 0.603 0.547 0.098 0.035
IM (c_IM) 0.427 0.079 5.404 0.000 0.361 0.361
TR (c_TR) -0.018 0.043 -0.429 0.668 -0.021 -0.021
ADT (c_AD) 0.246 0.070 3.523 0.000 0.203 0.203
PEB_yes (c_PE) 0.293 0.147 1.989 0.047 0.244 0.104
EEC 0.415 0.092 4.504 0.000 0.371 0.371
EEC ~
rwrd0_1 (d_01) -0.173 0.193 -0.896 0.371 -0.161 -0.059
rwrd0_2 (d_02) -0.013 0.208 -0.065 0.949 -0.013 -0.005
rwrd1_2 (d_12) 0.139 0.181 0.766 0.443 0.129 0.051
rwrd0_3 (d_03) -0.007 0.182 -0.037 0.971 -0.006 -0.002
rwrd1_3 (d_13) -0.020 0.200 -0.099 0.921 -0.018 -0.007
IM (d_IM) 0.429 0.084 5.100 0.000 0.405 0.405
TR (d_TR) 0.072 0.050 1.454 0.146 0.091 0.091
ADT (d_AD) 0.277 0.078 3.541 0.000 0.255 0.255
PEB_yes (d_PE) 0.254 0.163 1.556 0.120 0.237 0.101
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.631 0.112 5.627 0.000 0.471 0.471
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.476 0.118 4.018 0.000 0.476 0.316
.IM2 0.286 0.065 4.401 0.000 0.286 0.220
.IM3 0.376 0.168 2.243 0.025 0.376 0.267
.EEF1 0.242 0.048 5.053 0.000 0.242 0.144
.EEF2 0.213 0.039 5.500 0.000 0.213 0.126
.EEF3 0.253 0.054 4.728 0.000 0.253 0.161
.EEC1 0.802 0.086 9.348 0.000 0.802 0.410
.EEC2 0.446 0.083 5.355 0.000 0.446 0.206
.EEC3 0.201 0.053 3.819 0.000 0.201 0.098
.TR1 0.436 0.070 6.186 0.000 0.436 0.191
.TR2 0.311 0.066 4.749 0.000 0.311 0.132
.TR3 0.315 0.073 4.324 0.000 0.315 0.139
.ADT1 0.274 0.056 4.897 0.000 0.274 0.220
.ADT2 0.214 0.045 4.715 0.000 0.214 0.167
.ADT3 0.283 0.071 4.004 0.000 0.283 0.185
.IM 0.679 0.076 8.887 0.000 0.660 0.660
.EEF 0.525 0.073 7.238 0.000 0.365 0.365
.EEC 0.683 0.089 7.706 0.000 0.592 0.592
TR 1.842 0.155 11.886 0.000 1.000 1.000
ADT 0.974 0.145 6.698 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.684
IM2 0.780
IM3 0.733
EEF1 0.856
EEF2 0.874
EEF3 0.839
EEC1 0.590
EEC2 0.794
EEC3 0.902
TR1 0.809
TR2 0.868
TR3 0.861
ADT1 0.780
ADT2 0.833
ADT3 0.815
IM 0.340
EEF 0.635
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.270 0.172 1.567 0.117 0.266 0.097
reward2_IM 0.267 0.176 1.519 0.129 0.263 0.101
reward3_IM -0.299 0.201 -1.491 0.136 -0.295 -0.104
reward_vrgd_IM 0.079 0.094 0.842 0.400 0.078 0.031
reward_EEF_ec1 -0.190 0.182 -1.044 0.296 -0.158 -0.058
reward_EEF_ec2 0.084 0.153 0.545 0.586 0.070 0.027
reward_EEF_ec3 0.147 0.182 0.809 0.418 0.123 0.043
reward_man_EEF 0.014 0.101 0.137 0.891 0.012 0.004
ind_rwrd_EEF_1 0.115 0.072 1.594 0.111 0.096 0.035
ind_rwrd_EEF_2 0.114 0.079 1.441 0.150 0.095 0.037
ind_rwrd_EEF_3 -0.018 0.103 -0.178 0.859 -0.015 -0.006
ind_rw__IM_EEF 0.030 0.024 1.267 0.205 0.021 0.008
tt_rwrd_mn_EEF 0.044 0.103 0.425 0.671 0.033 0.012
reward_EEC_ec1 0.173 0.193 0.896 0.371 0.161 0.059
reward_EEC_ec2 0.152 0.192 0.794 0.427 0.142 0.056
reward_EEC_ec3 -0.013 0.185 -0.071 0.943 -0.012 -0.004
reward_man_EEC 0.104 0.110 0.949 0.342 0.097 0.037
ind_rwrd_EEC_1 0.116 0.077 1.505 0.132 0.108 0.039
ind_rwrd_EEC_2 0.114 0.078 1.461 0.144 0.107 0.041
ind_rwrd_EEC_3 -0.018 0.103 -0.177 0.859 -0.017 -0.006
ind_rw__IM_EEC 0.030 0.024 1.240 0.215 0.027 0.010
tt_rwrd_mn_EEC 0.134 0.109 1.231 0.218 0.124 0.047
eco1_EEF 0.095 0.091 1.044 0.296 0.079 0.029
eco2_EEF 0.015 0.155 0.094 0.925 0.012 0.005
eco3_EEF 0.044 0.164 0.267 0.790 0.036 0.013
eco2_vs_c1_EEF -0.040 0.058 -0.690 0.490 -0.033 -0.012
eco3_vs_c1_EEF -0.026 0.063 -0.404 0.686 -0.021 -0.008
eco3_vs_c2_EEF 0.015 0.060 0.245 0.806 0.012 0.004
eco1_EEC -0.087 0.097 -0.896 0.371 -0.081 -0.029
eco2_EEC 0.063 0.170 0.368 0.713 0.058 0.023
eco3_EEC -0.013 0.167 -0.079 0.937 -0.012 -0.004
eco2_vs_c1_EEC 0.075 0.068 1.091 0.275 0.070 0.026
eco3_vs_c1_EEC 0.037 0.066 0.553 0.580 0.034 0.013
eco3_vs_c2_EEC -0.038 0.066 -0.578 0.563 -0.035 -0.014Reference group: r0e2 - check with r0e1
With controls_r0e2 reference grouplavaan 0.6-21 ended normally after 56 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 235.373 217.311
Degrees of freedom 152 152
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.981
Robust Tucker-Lewis Index (TLI) 0.976
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4915.372 -4915.372
Scaling correction factor 1.619
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.231
for the MLR correction
Akaike (AIC) 9946.744 9946.744
Bayesian (BIC) 10154.587 10154.587
Sample-size adjusted Bayesian (SABIC) 9970.694 9970.694
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.056 0.051
P-value H_0: RMSEA <= 0.050 0.741 0.924
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.054
P-value H_0: Robust RMSEA <= 0.050 0.861
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.057 0.057
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 1.014 0.827
IM2 0.993 0.101 9.881 0.000 1.007 0.883
IM3 1.003 0.110 9.113 0.000 1.017 0.856
EEF =~
EEF1 1.000 1.201 0.925
EEF2 1.010 0.033 30.739 0.000 1.212 0.935
EEF3 0.958 0.038 25.056 0.000 1.150 0.916
EEC =~
EEC1 1.000 1.074 0.768
EEC2 1.220 0.076 15.985 0.000 1.310 0.891
EEC3 1.270 0.067 18.865 0.000 1.364 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.853 0.000 1.428 0.931
TR3 1.030 0.041 24.977 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.047 0.053 19.807 0.000 1.033 0.913
ADT3 1.132 0.061 18.534 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) -0.083 0.189 -0.439 0.661 -0.082 -0.030
rwrd1_1 (b_11) 0.187 0.178 1.049 0.294 0.184 0.071
rwrd1_2 (b_12) 0.267 0.176 1.519 0.129 0.263 0.104
rwrd0_3 (b_03) -0.070 0.219 -0.319 0.749 -0.069 -0.024
rwrd1_3 (b_13) -0.113 0.219 -0.515 0.607 -0.111 -0.039
TR (b_TR) 0.055 0.047 1.181 0.238 0.074 0.074
ADT (b_AD) 0.333 0.101 3.284 0.001 0.324 0.324
PEB_yes (b_PE) 1.027 0.156 6.598 0.000 1.013 0.433
EEF ~
rwrd0_1 (c_01) 0.217 0.161 1.344 0.179 0.181 0.066
rwrd1_1 (c_11) 0.027 0.178 0.153 0.878 0.023 0.009
rwrd1_2 (c_12) 0.084 0.153 0.545 0.586 0.070 0.027
rwrd0_3 (c_03) -0.003 0.166 -0.016 0.987 -0.002 -0.001
rwrd1_3 (c_13) 0.145 0.181 0.799 0.424 0.121 0.043
IM (c_IM) 0.427 0.079 5.404 0.000 0.361 0.361
TR (c_TR) -0.018 0.043 -0.429 0.668 -0.021 -0.021
ADT (c_AD) 0.246 0.070 3.523 0.000 0.203 0.203
PEB_yes (c_PE) 0.293 0.147 1.989 0.047 0.244 0.104
EEC 0.415 0.092 4.504 0.000 0.371 0.371
EEC ~
rwrd0_1 (d_01) -0.160 0.204 -0.785 0.433 -0.149 -0.054
rwrd1_1 (d_11) 0.013 0.208 0.065 0.949 0.013 0.005
rwrd1_2 (d_12) 0.152 0.192 0.794 0.427 0.142 0.056
rwrd0_3 (d_03) 0.007 0.191 0.035 0.972 0.006 0.002
rwrd1_3 (d_13) -0.006 0.209 -0.031 0.976 -0.006 -0.002
IM (d_IM) 0.429 0.084 5.100 0.000 0.405 0.405
TR (d_TR) 0.072 0.050 1.454 0.146 0.091 0.091
ADT (d_AD) 0.277 0.078 3.541 0.000 0.255 0.255
PEB_yes (d_PE) 0.254 0.163 1.556 0.120 0.237 0.101
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.631 0.112 5.627 0.000 0.471 0.471
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.476 0.118 4.018 0.000 0.476 0.316
.IM2 0.286 0.065 4.401 0.000 0.286 0.220
.IM3 0.376 0.168 2.243 0.025 0.376 0.267
.EEF1 0.242 0.048 5.053 0.000 0.242 0.144
.EEF2 0.213 0.039 5.500 0.000 0.213 0.126
.EEF3 0.253 0.054 4.728 0.000 0.253 0.161
.EEC1 0.802 0.086 9.348 0.000 0.802 0.410
.EEC2 0.446 0.083 5.355 0.000 0.446 0.206
.EEC3 0.201 0.053 3.819 0.000 0.201 0.098
.TR1 0.436 0.070 6.186 0.000 0.436 0.191
.TR2 0.311 0.066 4.749 0.000 0.311 0.132
.TR3 0.315 0.073 4.324 0.000 0.315 0.139
.ADT1 0.274 0.056 4.897 0.000 0.274 0.220
.ADT2 0.214 0.045 4.715 0.000 0.214 0.167
.ADT3 0.283 0.071 4.004 0.000 0.283 0.185
.IM 0.679 0.076 8.887 0.000 0.660 0.660
.EEF 0.525 0.073 7.238 0.000 0.365 0.365
.EEC 0.683 0.089 7.706 0.000 0.592 0.592
TR 1.842 0.155 11.886 0.000 1.000 1.000
ADT 0.974 0.145 6.698 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.684
IM2 0.780
IM3 0.733
EEF1 0.856
EEF2 0.874
EEF3 0.839
EEC1 0.590
EEC2 0.794
EEC3 0.902
TR1 0.809
TR2 0.868
TR3 0.861
ADT1 0.780
ADT2 0.833
ADT3 0.815
IM 0.340
EEF 0.635
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.270 0.172 1.567 0.117 0.266 0.101
reward2_IM 0.267 0.176 1.519 0.129 0.263 0.104
reward3_IM -0.043 0.241 -0.177 0.859 -0.042 -0.015
reward_vrgd_IM 0.165 0.116 1.417 0.156 0.162 0.063
reward_EEF_ec1 -0.190 0.182 -1.044 0.296 -0.158 -0.057
reward_EEF_ec2 0.084 0.153 0.545 0.586 0.070 0.027
reward_EEF_ec3 0.147 0.182 0.809 0.418 0.123 0.043
reward_man_EEF 0.014 0.101 0.137 0.891 0.012 0.005
ind_rwrd_EEF_1 0.115 0.072 1.594 0.111 0.096 0.037
ind_rwrd_EEF_2 0.114 0.079 1.441 0.150 0.095 0.037
ind_rwrd_EEF_3 -0.018 0.103 -0.178 0.859 -0.015 -0.005
ind_rw__IM_EEF 0.030 0.024 1.267 0.205 0.021 0.008
tt_rwrd_mn_EEF 0.044 0.103 0.425 0.671 0.033 0.013
reward_EEC_ec1 0.173 0.193 0.895 0.371 0.161 0.059
reward_EEC_ec2 0.152 0.192 0.794 0.427 0.142 0.056
reward_EEC_ec3 -0.013 0.185 -0.071 0.943 -0.012 -0.004
reward_man_EEC 0.104 0.110 0.949 0.342 0.097 0.037
ind_rwrd_EEC_1 0.116 0.077 1.505 0.132 0.108 0.041
ind_rwrd_EEC_2 0.114 0.078 1.461 0.144 0.107 0.042
ind_rwrd_EEC_3 -0.018 0.103 -0.177 0.859 -0.017 -0.006
ind_rw__IM_EEC 0.030 0.024 1.240 0.215 0.027 0.010
tt_rwrd_mn_EEC 0.134 0.109 1.231 0.218 0.124 0.047
eco1_EEF 0.122 0.144 0.849 0.396 0.102 0.037
eco2_EEF 0.042 0.077 0.545 0.586 0.035 0.014
eco3_EEF 0.072 0.091 0.799 0.424 0.060 0.021
eco2_vs_c1_EEF -0.040 0.058 -0.690 0.490 -0.033 -0.012
eco3_vs_c1_EEF -0.025 0.062 -0.398 0.691 -0.021 -0.008
eco3_vs_c2_EEF 0.015 0.043 0.358 0.720 0.013 0.004
eco1_EEC -0.073 0.182 -0.402 0.688 -0.068 -0.025
eco2_EEC 0.076 0.096 0.794 0.427 0.071 0.028
eco3_EEC -0.003 0.104 -0.031 0.976 -0.003 -0.001
eco2_vs_c1_EEC 0.075 0.068 1.091 0.275 0.070 0.026
eco3_vs_c1_EEC 0.035 0.071 0.490 0.624 0.033 0.012
eco3_vs_c2_EEC -0.040 0.046 -0.867 0.386 -0.037 -0.014Reference group: r1e2 - check with r0e1
With controls_r1e2 reference grouplavaan 0.6-21 ended normally after 55 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 235.373 217.311
Degrees of freedom 152 152
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.981
Robust Tucker-Lewis Index (TLI) 0.976
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4915.372 -4915.372
Scaling correction factor 1.619
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.231
for the MLR correction
Akaike (AIC) 9946.744 9946.744
Bayesian (BIC) 10154.587 10154.587
Sample-size adjusted Bayesian (SABIC) 9970.694 9970.694
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.056 0.051
P-value H_0: RMSEA <= 0.050 0.741 0.924
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.054
P-value H_0: Robust RMSEA <= 0.050 0.861
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.057 0.057
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 1.014 0.827
IM2 0.993 0.101 9.881 0.000 1.007 0.883
IM3 1.003 0.110 9.113 0.000 1.017 0.856
EEF =~
EEF1 1.000 1.201 0.925
EEF2 1.010 0.033 30.739 0.000 1.212 0.935
EEF3 0.958 0.038 25.056 0.000 1.150 0.916
EEC =~
EEC1 1.000 1.074 0.768
EEC2 1.220 0.076 15.985 0.000 1.310 0.891
EEC3 1.270 0.067 18.865 0.000 1.364 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.853 0.000 1.428 0.931
TR3 1.030 0.041 24.977 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.047 0.053 19.807 0.000 1.033 0.913
ADT3 1.132 0.061 18.534 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) -0.350 0.166 -2.111 0.035 -0.345 -0.126
rwrd1_1 (b_11) -0.080 0.159 -0.505 0.614 -0.079 -0.031
rwrd0_2 (b_02) -0.267 0.176 -1.519 0.129 -0.263 -0.100
rwrd0_3 (b_03) -0.337 0.203 -1.663 0.096 -0.332 -0.116
rwrd1_3 (b_13) -0.379 0.192 -1.976 0.048 -0.374 -0.132
TR (b_TR) 0.055 0.047 1.181 0.238 0.074 0.074
ADT (b_AD) 0.333 0.101 3.284 0.001 0.324 0.324
PEB_yes (b_PE) 1.027 0.156 6.598 0.000 1.013 0.433
EEF ~
rwrd0_1 (c_01) 0.133 0.158 0.845 0.398 0.111 0.040
rwrd1_1 (c_11) -0.056 0.167 -0.337 0.736 -0.047 -0.018
rwrd0_2 (c_02) -0.084 0.153 -0.545 0.586 -0.070 -0.027
rwrd0_3 (c_03) -0.086 0.154 -0.559 0.576 -0.072 -0.025
rwrd1_3 (c_13) 0.061 0.171 0.358 0.720 0.051 0.018
IM (c_IM) 0.427 0.079 5.404 0.000 0.361 0.361
TR (c_TR) -0.018 0.043 -0.429 0.668 -0.021 -0.021
ADT (c_AD) 0.246 0.070 3.523 0.000 0.203 0.203
PEB_yes (c_PE) 0.293 0.147 1.989 0.047 0.244 0.104
EEC 0.415 0.092 4.504 0.000 0.371 0.371
EEC ~
rwrd0_1 (d_01) -0.312 0.177 -1.763 0.078 -0.291 -0.106
rwrd1_1 (d_11) -0.139 0.181 -0.767 0.443 -0.129 -0.050
rwrd0_2 (d_02) -0.152 0.192 -0.794 0.427 -0.142 -0.054
rwrd0_3 (d_03) -0.145 0.162 -0.897 0.370 -0.135 -0.047
rwrd1_3 (d_13) -0.159 0.183 -0.867 0.386 -0.148 -0.052
IM (d_IM) 0.429 0.084 5.100 0.000 0.405 0.405
TR (d_TR) 0.072 0.050 1.454 0.146 0.091 0.091
ADT (d_AD) 0.277 0.078 3.541 0.000 0.255 0.255
PEB_yes (d_PE) 0.254 0.163 1.556 0.120 0.237 0.101
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.631 0.112 5.627 0.000 0.471 0.471
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.476 0.118 4.018 0.000 0.476 0.316
.IM2 0.286 0.065 4.401 0.000 0.286 0.220
.IM3 0.376 0.168 2.243 0.025 0.376 0.267
.EEF1 0.242 0.048 5.053 0.000 0.242 0.144
.EEF2 0.213 0.039 5.500 0.000 0.213 0.126
.EEF3 0.253 0.054 4.728 0.000 0.253 0.161
.EEC1 0.802 0.086 9.348 0.000 0.802 0.410
.EEC2 0.446 0.083 5.355 0.000 0.446 0.206
.EEC3 0.201 0.053 3.819 0.000 0.201 0.098
.TR1 0.436 0.070 6.186 0.000 0.436 0.191
.TR2 0.311 0.066 4.749 0.000 0.311 0.132
.TR3 0.315 0.073 4.324 0.000 0.315 0.139
.ADT1 0.274 0.056 4.897 0.000 0.274 0.220
.ADT2 0.214 0.045 4.715 0.000 0.214 0.167
.ADT3 0.283 0.071 4.004 0.000 0.283 0.185
.IM 0.679 0.076 8.887 0.000 0.660 0.660
.EEF 0.525 0.073 7.238 0.000 0.365 0.365
.EEC 0.683 0.089 7.706 0.000 0.592 0.592
TR 1.842 0.155 11.886 0.000 1.000 1.000
ADT 0.974 0.145 6.698 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.684
IM2 0.780
IM3 0.733
EEF1 0.856
EEF2 0.874
EEF3 0.839
EEC1 0.590
EEC2 0.794
EEC3 0.902
TR1 0.809
TR2 0.868
TR3 0.861
ADT1 0.780
ADT2 0.833
ADT3 0.815
IM 0.340
EEF 0.635
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.270 0.172 1.567 0.117 0.266 0.095
reward2_IM -0.267 0.176 -1.519 0.129 -0.263 -0.100
reward3_IM -0.043 0.241 -0.177 0.859 -0.042 -0.016
reward_vrgd_IM -0.013 0.114 -0.117 0.907 -0.013 -0.007
reward_EEF_ec1 -0.190 0.182 -1.044 0.296 -0.158 -0.059
reward_EEF_ec2 0.084 0.153 0.545 0.586 0.070 0.027
reward_EEF_ec3 0.147 0.182 0.809 0.418 0.123 0.043
reward_man_EEF 0.014 0.101 0.137 0.891 0.012 0.004
ind_rwrd_EEF_1 0.115 0.072 1.594 0.111 0.096 0.034
ind_rwrd_EEF_2 0.114 0.079 1.441 0.150 0.095 0.036
ind_rwrd_EEF_3 -0.018 0.103 -0.178 0.859 -0.015 -0.006
ind_rw__IM_EEF 0.030 0.024 1.267 0.205 0.021 0.008
tt_rwrd_mn_EEF 0.044 0.103 0.425 0.671 0.033 0.011
reward_EEC_ec1 0.173 0.193 0.895 0.371 0.161 0.056
reward_EEC_ec2 0.152 0.192 0.794 0.427 0.142 0.054
reward_EEC_ec3 -0.013 0.185 -0.071 0.943 -0.012 -0.005
reward_man_EEC 0.104 0.110 0.949 0.342 0.097 0.035
ind_rwrd_EEC_1 0.116 0.077 1.505 0.132 0.108 0.039
ind_rwrd_EEC_2 0.114 0.078 1.461 0.144 0.107 0.041
ind_rwrd_EEC_3 -0.018 0.103 -0.177 0.859 -0.017 -0.007
ind_rw__IM_EEC 0.030 0.024 1.240 0.215 0.027 0.010
tt_rwrd_mn_EEC 0.134 0.109 1.231 0.218 0.124 0.045
eco1_EEF 0.038 0.135 0.285 0.775 0.032 0.011
eco2_EEF -0.042 0.077 -0.545 0.586 -0.035 -0.013
eco3_EEF -0.013 0.135 -0.093 0.926 -0.010 -0.004
eco2_vs_c1_EEF -0.040 0.058 -0.690 0.490 -0.033 -0.012
eco3_vs_c1_EEF -0.026 0.063 -0.404 0.686 -0.021 -0.007
eco3_vs_c2_EEF 0.015 0.060 0.245 0.806 0.012 0.005
eco1_EEC -0.225 0.151 -1.496 0.135 -0.210 -0.078
eco2_EEC -0.076 0.096 -0.794 0.427 -0.071 -0.027
eco3_EEC -0.152 0.146 -1.041 0.298 -0.142 -0.050
eco2_vs_c1_EEC 0.075 0.068 1.091 0.275 0.070 0.025
eco3_vs_c1_EEC 0.037 0.066 0.553 0.580 0.034 0.014
eco3_vs_c2_EEC -0.038 0.066 -0.578 0.563 -0.035 -0.011Reference group: r0e3 - check with r0e1
r0e3 referencelavaan 0.6-21 ended normally after 55 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 235.373 217.311
Degrees of freedom 152 152
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.981
Robust Tucker-Lewis Index (TLI) 0.976
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4915.372 -4915.372
Scaling correction factor 1.619
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.231
for the MLR correction
Akaike (AIC) 9946.744 9946.744
Bayesian (BIC) 10154.587 10154.587
Sample-size adjusted Bayesian (SABIC) 9970.694 9970.694
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.056 0.051
P-value H_0: RMSEA <= 0.050 0.741 0.924
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.054
P-value H_0: Robust RMSEA <= 0.050 0.861
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.057 0.057
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 1.014 0.827
IM2 0.993 0.101 9.881 0.000 1.007 0.883
IM3 1.003 0.110 9.113 0.000 1.017 0.856
EEF =~
EEF1 1.000 1.201 0.925
EEF2 1.010 0.033 30.739 0.000 1.212 0.935
EEF3 0.958 0.038 25.056 0.000 1.150 0.916
EEC =~
EEC1 1.000 1.074 0.768
EEC2 1.220 0.076 15.985 0.000 1.310 0.891
EEC3 1.270 0.067 18.865 0.000 1.364 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.853 0.000 1.428 0.931
TR3 1.030 0.041 24.977 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.047 0.053 19.807 0.000 1.033 0.913
ADT3 1.132 0.061 18.534 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) -0.013 0.214 -0.060 0.952 -0.013 -0.005
rwrd1_1 (b_11) 0.257 0.202 1.269 0.204 0.253 0.098
rwrd0_2 (b_02) 0.070 0.219 0.319 0.749 0.069 0.026
rwrd1_2 (b_12) 0.337 0.203 1.663 0.096 0.332 0.131
rwrd1_3 (b_13) -0.043 0.241 -0.177 0.859 -0.042 -0.015
TR (b_TR) 0.055 0.047 1.181 0.238 0.074 0.074
ADT (b_AD) 0.333 0.101 3.284 0.001 0.324 0.324
PEB_yes (b_PE) 1.027 0.156 6.598 0.000 1.013 0.433
EEF ~
rwrd0_1 (c_01) 0.220 0.164 1.337 0.181 0.183 0.067
rwrd1_1 (c_11) 0.030 0.180 0.166 0.868 0.025 0.010
rwrd0_2 (c_02) 0.003 0.166 0.016 0.987 0.002 0.001
rwrd1_2 (c_12) 0.086 0.154 0.559 0.576 0.072 0.028
rwrd1_3 (c_13) 0.147 0.182 0.809 0.418 0.123 0.043
IM (c_IM) 0.427 0.079 5.404 0.000 0.361 0.361
TR (c_TR) -0.018 0.043 -0.429 0.668 -0.021 -0.021
ADT (c_AD) 0.246 0.070 3.523 0.000 0.203 0.203
PEB_yes (c_PE) 0.293 0.147 1.989 0.047 0.244 0.104
EEC 0.415 0.092 4.504 0.000 0.371 0.371
EEC ~
rwrd0_1 (d_01) -0.167 0.177 -0.942 0.346 -0.155 -0.057
rwrd1_1 (d_11) 0.007 0.182 0.037 0.971 0.006 0.002
rwrd0_2 (d_02) -0.007 0.191 -0.035 0.972 -0.006 -0.002
rwrd1_2 (d_12) 0.145 0.162 0.897 0.370 0.135 0.053
rwrd1_3 (d_13) -0.013 0.185 -0.071 0.943 -0.012 -0.004
IM (d_IM) 0.429 0.084 5.100 0.000 0.405 0.405
TR (d_TR) 0.072 0.050 1.454 0.146 0.091 0.091
ADT (d_AD) 0.277 0.078 3.541 0.000 0.255 0.255
PEB_yes (d_PE) 0.254 0.163 1.556 0.120 0.237 0.101
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.631 0.112 5.627 0.000 0.471 0.471
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.476 0.118 4.018 0.000 0.476 0.316
.IM2 0.286 0.065 4.401 0.000 0.286 0.220
.IM3 0.376 0.168 2.243 0.025 0.376 0.267
.EEF1 0.242 0.048 5.053 0.000 0.242 0.144
.EEF2 0.213 0.039 5.500 0.000 0.213 0.126
.EEF3 0.253 0.054 4.728 0.000 0.253 0.161
.EEC1 0.802 0.086 9.348 0.000 0.802 0.410
.EEC2 0.446 0.083 5.355 0.000 0.446 0.206
.EEC3 0.201 0.053 3.819 0.000 0.201 0.098
.TR1 0.436 0.070 6.186 0.000 0.436 0.191
.TR2 0.311 0.066 4.749 0.000 0.311 0.132
.TR3 0.315 0.073 4.324 0.000 0.315 0.139
.ADT1 0.274 0.056 4.897 0.000 0.274 0.220
.ADT2 0.214 0.045 4.715 0.000 0.214 0.167
.ADT3 0.283 0.071 4.004 0.000 0.283 0.185
.IM 0.679 0.076 8.887 0.000 0.660 0.660
.EEF 0.525 0.073 7.238 0.000 0.365 0.365
.EEC 0.683 0.089 7.706 0.000 0.592 0.592
TR 1.842 0.155 11.886 0.000 1.000 1.000
ADT 0.974 0.145 6.698 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.684
IM2 0.780
IM3 0.733
EEF1 0.856
EEF2 0.874
EEF3 0.839
EEC1 0.590
EEC2 0.794
EEC3 0.902
TR1 0.809
TR2 0.868
TR3 0.861
ADT1 0.780
ADT2 0.833
ADT3 0.815
IM 0.340
EEF 0.635
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.270 0.172 1.567 0.117 0.266 0.103
reward2_IM 0.267 0.176 1.519 0.129 0.263 0.104
reward3_IM -0.043 0.241 -0.177 0.859 -0.042 -0.015
reward_vrgd_IM 0.165 0.116 1.417 0.156 0.162 0.064
reward_EEF_ec1 -0.190 0.182 -1.044 0.296 -0.158 -0.057
reward_EEF_ec2 0.084 0.153 0.545 0.586 0.070 0.027
reward_EEF_ec3 0.147 0.182 0.809 0.418 0.123 0.043
reward_man_EEF 0.014 0.101 0.137 0.891 0.012 0.005
ind_rwrd_EEF_1 0.115 0.072 1.594 0.111 0.096 0.037
ind_rwrd_EEF_2 0.114 0.079 1.441 0.150 0.095 0.038
ind_rwrd_EEF_3 -0.018 0.103 -0.178 0.859 -0.015 -0.005
ind_rw__IM_EEF 0.030 0.024 1.267 0.205 0.021 0.008
tt_rwrd_mn_EEF 0.044 0.103 0.425 0.671 0.033 0.013
reward_EEC_ec1 0.173 0.193 0.895 0.371 0.161 0.059
reward_EEC_ec2 0.152 0.192 0.794 0.427 0.142 0.056
reward_EEC_ec3 -0.013 0.185 -0.071 0.943 -0.012 -0.004
reward_man_EEC 0.104 0.110 0.949 0.342 0.097 0.037
ind_rwrd_EEC_1 0.116 0.077 1.505 0.132 0.108 0.042
ind_rwrd_EEC_2 0.114 0.078 1.461 0.144 0.107 0.042
ind_rwrd_EEC_3 -0.018 0.103 -0.177 0.859 -0.017 -0.006
ind_rw__IM_EEC 0.030 0.024 1.240 0.215 0.027 0.011
tt_rwrd_mn_EEC 0.134 0.109 1.231 0.218 0.124 0.047
eco1_EEF 0.125 0.146 0.851 0.395 0.104 0.038
eco2_EEF 0.044 0.141 0.315 0.752 0.037 0.015
eco3_EEF 0.074 0.091 0.809 0.418 0.061 0.022
eco2_vs_c1_EEF -0.040 0.058 -0.690 0.490 -0.033 -0.012
eco3_vs_c1_EEF -0.026 0.063 -0.404 0.686 -0.021 -0.008
eco3_vs_c2_EEF 0.015 0.060 0.245 0.806 0.012 0.004
eco1_EEC -0.080 0.151 -0.529 0.597 -0.074 -0.027
eco2_EEC 0.069 0.149 0.465 0.642 0.065 0.025
eco3_EEC -0.007 0.092 -0.071 0.943 -0.006 -0.002
eco2_vs_c1_EEC 0.075 0.068 1.091 0.275 0.070 0.026
eco3_vs_c1_EEC 0.037 0.066 0.553 0.580 0.034 0.012
eco3_vs_c2_EEC -0.038 0.066 -0.579 0.563 -0.035 -0.014Reference group: r1e3 - check with r0e1
r1e3 reference copylavaan 0.6-21 ended normally after 56 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 266
Model Test User Model:
Standard Scaled
Test Statistic 235.373 217.311
Degrees of freedom 152 152
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.083
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3961.465 3242.996
Degrees of freedom 195 195
P-value 0.000 0.000
Scaling correction factor 1.222
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.978 0.979
Tucker-Lewis Index (TLI) 0.972 0.973
Robust Comparative Fit Index (CFI) 0.981
Robust Tucker-Lewis Index (TLI) 0.976
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4915.372 -4915.372
Scaling correction factor 1.619
for the MLR correction
Loglikelihood unrestricted model (H1) -4797.686 -4797.686
Scaling correction factor 1.231
for the MLR correction
Akaike (AIC) 9946.744 9946.744
Bayesian (BIC) 10154.587 10154.587
Sample-size adjusted Bayesian (SABIC) 9970.694 9970.694
Root Mean Square Error of Approximation:
RMSEA 0.045 0.040
90 Percent confidence interval - lower 0.034 0.028
90 Percent confidence interval - upper 0.056 0.051
P-value H_0: RMSEA <= 0.050 0.741 0.924
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.042
90 Percent confidence interval - lower 0.028
90 Percent confidence interval - upper 0.054
P-value H_0: Robust RMSEA <= 0.050 0.861
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.056 0.056
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 1.014 0.827
IM2 0.993 0.101 9.881 0.000 1.007 0.883
IM3 1.003 0.110 9.113 0.000 1.017 0.856
EEF =~
EEF1 1.000 1.201 0.925
EEF2 1.010 0.033 30.739 0.000 1.212 0.935
EEF3 0.958 0.038 25.056 0.000 1.150 0.916
EEC =~
EEC1 1.000 1.074 0.768
EEC2 1.220 0.076 15.985 0.000 1.310 0.891
EEC3 1.270 0.067 18.865 0.000 1.364 0.950
TR =~
TR1 1.000 1.357 0.899
TR2 1.052 0.041 25.853 0.000 1.428 0.931
TR3 1.030 0.041 24.977 0.000 1.397 0.928
ADT =~
ADT1 1.000 0.987 0.883
ADT2 1.047 0.053 19.807 0.000 1.033 0.913
ADT3 1.132 0.061 18.534 0.000 1.117 0.903
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
IM ~
rwrd0_1 (b_01) 0.030 0.214 0.139 0.889 0.029 0.011
rwrd1_1 (b_11) 0.299 0.201 1.491 0.136 0.295 0.114
rwrd0_2 (b_02) 0.113 0.219 0.515 0.607 0.111 0.042
rwrd1_2 (b_12) 0.379 0.192 1.976 0.048 0.374 0.147
rwrd0_3 (b_03) 0.043 0.241 0.177 0.859 0.042 0.015
TR (b_TR) 0.055 0.047 1.181 0.238 0.074 0.074
ADT (b_AD) 0.333 0.101 3.284 0.001 0.324 0.324
PEB_yes (b_PE) 1.027 0.156 6.598 0.000 1.013 0.433
EEF ~
rwrd0_1 (c_01) 0.072 0.180 0.401 0.689 0.060 0.022
rwrd1_1 (c_11) -0.117 0.195 -0.603 0.547 -0.098 -0.038
rwrd0_2 (c_02) -0.145 0.181 -0.799 0.424 -0.121 -0.046
rwrd1_2 (c_12) -0.061 0.171 -0.358 0.721 -0.051 -0.020
rwrd0_3 (c_03) -0.147 0.182 -0.809 0.418 -0.123 -0.043
IM (c_IM) 0.427 0.079 5.404 0.000 0.361 0.361
TR (c_TR) -0.018 0.043 -0.429 0.668 -0.021 -0.021
ADT (c_AD) 0.246 0.070 3.523 0.000 0.203 0.203
PEB_yes (c_PE) 0.293 0.147 1.989 0.047 0.244 0.104
EEC 0.415 0.092 4.504 0.000 0.371 0.371
EEC ~
rwrd0_1 (d_01) -0.153 0.194 -0.791 0.429 -0.143 -0.052
rwrd1_1 (d_11) 0.020 0.200 0.099 0.921 0.018 0.007
rwrd0_2 (d_02) 0.006 0.209 0.031 0.976 0.006 0.002
rwrd1_2 (d_12) 0.159 0.183 0.867 0.386 0.148 0.058
rwrd0_3 (d_03) 0.013 0.185 0.071 0.943 0.012 0.004
IM (d_IM) 0.429 0.084 5.100 0.000 0.405 0.405
TR (d_TR) 0.072 0.050 1.454 0.146 0.091 0.091
ADT (d_AD) 0.277 0.078 3.541 0.000 0.255 0.255
PEB_yes (d_PE) 0.254 0.163 1.556 0.120 0.237 0.101
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
ADT 0.631 0.112 5.627 0.000 0.471 0.471
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.IM1 0.476 0.118 4.018 0.000 0.476 0.316
.IM2 0.286 0.065 4.401 0.000 0.286 0.220
.IM3 0.376 0.168 2.243 0.025 0.376 0.267
.EEF1 0.242 0.048 5.053 0.000 0.242 0.144
.EEF2 0.213 0.039 5.500 0.000 0.213 0.126
.EEF3 0.253 0.054 4.728 0.000 0.253 0.161
.EEC1 0.802 0.086 9.348 0.000 0.802 0.410
.EEC2 0.446 0.083 5.355 0.000 0.446 0.206
.EEC3 0.201 0.053 3.819 0.000 0.201 0.098
.TR1 0.436 0.070 6.186 0.000 0.436 0.191
.TR2 0.311 0.066 4.749 0.000 0.311 0.132
.TR3 0.315 0.073 4.324 0.000 0.315 0.139
.ADT1 0.274 0.056 4.897 0.000 0.274 0.220
.ADT2 0.214 0.045 4.715 0.000 0.214 0.167
.ADT3 0.283 0.071 4.004 0.000 0.283 0.185
.IM 0.679 0.076 8.887 0.000 0.660 0.660
.EEF 0.525 0.073 7.238 0.000 0.365 0.365
.EEC 0.683 0.089 7.706 0.000 0.592 0.592
TR 1.842 0.155 11.886 0.000 1.000 1.000
ADT 0.974 0.145 6.698 0.000 1.000 1.000
R-Square:
Estimate
IM1 0.684
IM2 0.780
IM3 0.733
EEF1 0.856
EEF2 0.874
EEF3 0.839
EEC1 0.590
EEC2 0.794
EEC3 0.902
TR1 0.809
TR2 0.868
TR3 0.861
ADT1 0.780
ADT2 0.833
ADT3 0.815
IM 0.340
EEF 0.635
EEC 0.408
Defined Parameters:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
reward1_IM 0.270 0.172 1.567 0.117 0.266 0.104
reward2_IM 0.267 0.176 1.519 0.129 0.263 0.105
reward3_IM -0.043 0.241 -0.177 0.859 -0.042 -0.015
reward_vrgd_IM 0.165 0.116 1.417 0.156 0.162 0.065
reward_EEF_ec1 -0.190 0.182 -1.044 0.296 -0.158 -0.060
reward_EEF_ec2 0.084 0.153 0.545 0.586 0.070 0.026
reward_EEF_ec3 0.147 0.182 0.809 0.418 0.123 0.043
reward_man_EEF 0.014 0.101 0.137 0.891 0.012 0.003
ind_rwrd_EEF_1 0.115 0.072 1.594 0.111 0.096 0.037
ind_rwrd_EEF_2 0.114 0.079 1.441 0.150 0.095 0.038
ind_rwrd_EEF_3 -0.018 0.103 -0.178 0.859 -0.015 -0.005
ind_rw__IM_EEF 0.030 0.024 1.267 0.205 0.021 0.008
tt_rwrd_mn_EEF 0.044 0.103 0.425 0.671 0.033 0.011
reward_EEC_ec1 0.173 0.193 0.895 0.371 0.161 0.059
reward_EEC_ec2 0.152 0.192 0.794 0.427 0.142 0.056
reward_EEC_ec3 -0.013 0.185 -0.071 0.943 -0.012 -0.004
reward_man_EEC 0.104 0.110 0.949 0.342 0.097 0.037
ind_rwrd_EEC_1 0.116 0.077 1.505 0.132 0.108 0.042
ind_rwrd_EEC_2 0.114 0.078 1.461 0.144 0.107 0.043
ind_rwrd_EEC_3 -0.018 0.103 -0.177 0.859 -0.017 -0.006
ind_rw__IM_EEC 0.030 0.024 1.240 0.215 0.027 0.011
tt_rwrd_mn_EEC 0.134 0.109 1.231 0.218 0.124 0.048
eco1_EEF -0.023 0.164 -0.138 0.890 -0.019 -0.008
eco2_EEF -0.103 0.158 -0.650 0.516 -0.086 -0.033
eco3_EEF -0.074 0.091 -0.809 0.418 -0.061 -0.021
eco2_vs_c1_EEF -0.040 0.058 -0.690 0.490 -0.033 -0.013
eco3_vs_c1_EEF -0.026 0.063 -0.405 0.686 -0.021 -0.007
eco3_vs_c2_EEF 0.015 0.060 0.245 0.806 0.012 0.006
eco1_EEC -0.067 0.172 -0.389 0.697 -0.062 -0.022
eco2_EEC 0.083 0.171 0.482 0.630 0.077 0.030
eco3_EEC 0.007 0.092 0.071 0.943 0.006 0.002
eco2_vs_c1_EEC 0.075 0.068 1.091 0.275 0.070 0.026
eco3_vs_c1_EEC 0.037 0.066 0.553 0.580 0.034 0.012
eco3_vs_c2_EEC -0.038 0.066 -0.578 0.563 -0.035 -0.014[1] FALSE