$all
[1] 211Full model
Dataset preperation - raw dataset
Composite
Sample size
Group statistics
Reward groups
no_reward performance_reward process_reward
73 61 77 Eco orientation groups
both_ori EEC_ori EEF_ori
70 78 63 Ease and feedback
Overall, how easy was it for you to relate to the scenario and the questions? (5 stars=very easy)
vars n mean sd median trimmed mad min max range skew kurtosis se
X1 1 211 4.43 0.74 4.73 4.56 0.4 0.57 5 4.43 -1.89 4.62 0.05Qualitative feedback
is_no
FALSE TRUE
67 144 Data Quality
Manipulation and attention checks
FALSE TRUE
1 73 0
2 69 8
3 47 14
FALSE TRUE
1 47 16
2 43 35
3 65 5
FALSE TRUE
209 2 Filtering out bad participants
Filtered dataset
Descriptive on good participants
all good
211 135 Conditions
Group statistics Reward
Reward groups
1 2 3
52 53 30 Eco-orientation
Eco orientation groups
1 2 3
41 40 54 Decriptive
# A tibble: 9 × 9
Condition_reward Condition_eco n mean_EEF sd_EEF mean_EEC sd_EEC mean_IM
<fct> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 1 1 16 4.96 1.69 3.81 1.68 5.21
2 1 2 10 5.83 0.790 4.1 1.61 5.63
3 1 3 26 5.27 1.51 4.45 1.61 5.45
4 2 1 17 5.37 1.37 4.08 1.38 5.53
5 2 2 23 5.38 1.26 4 1.48 5.23
6 2 3 13 5.38 1.63 4.38 1.81 5.54
7 3 1 8 5.54 1.14 3.58 1.53 5.75
8 3 2 7 5.71 1.39 4.81 1.43 5.76
9 3 3 15 5.22 1.67 4.47 1.64 5.4
# ℹ 1 more variable: sd_IM <dbl>
# A tibble: 27 × 7
Condition_reward Condition_eco Measure Mean Median SD N
<fct> <fct> <chr> <dbl> <dbl> <dbl> <int>
1 1 1 EEC_composite 3.81 3.67 1.68 16
2 1 1 EEF_composite 4.96 5.67 1.69 16
3 1 1 IM_composite 5.21 5.67 1.60 16
4 1 2 EEC_composite 4.1 4.33 1.61 10
5 1 2 EEF_composite 5.83 6 0.790 10
6 1 2 IM_composite 5.63 5.67 1.15 10
7 1 3 EEC_composite 4.45 4.5 1.61 26
8 1 3 EEF_composite 5.27 5.67 1.51 26
9 1 3 IM_composite 5.45 5.67 1.15 26
10 2 1 EEC_composite 4.08 4.33 1.38 17
# ℹ 17 more rowsNormality tests
Across all scales
$S1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.89712, p-value = 3.449e-08
$S2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.89673, p-value = 3.289e-08
$S3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.88996, p-value = 1.466e-08
$IM1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.86817, p-value = 1.317e-09
$IM2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.80735, p-value = 4.945e-12
$IM3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.81597, p-value = 1.008e-11
$INR1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.90137, p-value = 5.83e-08
$INR2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.92581, p-value = 1.606e-06
$INR3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.9272, p-value = 1.975e-06
$IDR1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.75411, p-value = 9.316e-14
$IDR2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.69934, p-value = 2.823e-15
$IDR3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.73008, p-value = 1.889e-14
$EEF1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.87643, p-value = 3.18e-09
$EEF2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.83268, p-value = 4.284e-11
$EEF3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.8405, p-value = 8.719e-11
$EEC1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.93054, p-value = 3.269e-06
$EEC2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.94092, p-value = 1.711e-05
$EEC3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.94144, p-value = 1.868e-05
$TR1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.92341, p-value = 1.13e-06
$TR2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.91611, p-value = 4.036e-07
$TR3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.89392, p-value = 2.341e-08
$BV1
Shapiro-Wilk normality test
data: newX[, i]
W = 0.90214, p-value = 6.425e-08
$BV2
Shapiro-Wilk normality test
data: newX[, i]
W = 0.8638, p-value = 8.383e-10
$BV3
Shapiro-Wilk normality test
data: newX[, i]
W = 0.845, p-value = 1.327e-10On dependent variables
Shapiro-Wilk normality test
data: data_filtered$EEF_composite
W = 0.87944, p-value = 4.428e-09EEC composite
Shapiro-Wilk normality test
data: data_filtered$EEC_composite
W = 0.96899, p-value = 0.00357On DV per condition
`summarise()` has grouped output by 'Condition_reward'. You can override using
the `.groups` argument.# A tibble: 9 × 4
# Groups: Condition_reward [3]
Condition_reward Condition_eco n shapiro_p
<fct> <fct> <int> <dbl>
1 1 1 16 0.0169
2 1 2 10 0.543
3 1 3 26 0.0109
4 2 1 17 0.0684
5 2 2 23 0.0324
6 2 3 13 0.0140
7 3 1 8 0.770
8 3 2 7 0.204
9 3 3 15 0.0316`summarise()` has grouped output by 'Condition_reward'. You can override using
the `.groups` argument.# A tibble: 9 × 4
# Groups: Condition_reward [3]
Condition_reward Condition_eco n shapiro_p
<fct> <fct> <int> <dbl>
1 1 1 16 0.594
2 1 2 10 0.978
3 1 3 26 0.665
4 2 1 17 0.242
5 2 2 23 0.531
6 2 3 13 0.599
7 3 1 8 0.150
8 3 2 7 0.407
9 3 3 15 0.234On motivation variables
IM composite
Shapiro-Wilk normality test
data: data_filtered$IM_composite
W = 0.871, p-value = 1.775e-09IDR composite
Shapiro-Wilk normality test
data: data_filtered$IDR_composite
W = 0.76862, p-value = 2.578e-13INR composite
Shapiro-Wilk normality test
data: data_filtered$INR_composite
W = 0.95132, p-value = 0.000105Non-normality test on motivation per condition
`summarise()` has grouped output by 'Condition_reward'. You can override using
the `.groups` argument.# A tibble: 9 × 4
# Groups: Condition_reward [3]
Condition_reward Condition_eco n shapiro_p
<fct> <fct> <int> <dbl>
1 1 1 16 0.0654
2 1 2 10 0.320
3 1 3 26 0.0230
4 2 1 17 0.252
5 2 2 23 0.000710
6 2 3 13 0.00331
7 3 1 8 0.0283
8 3 2 7 0.157
9 3 3 15 0.00620 `summarise()` has grouped output by 'Condition_reward'. You can override using
the `.groups` argument.# A tibble: 9 × 4
# Groups: Condition_reward [3]
Condition_reward Condition_eco n shapiro_p
<fct> <fct> <int> <dbl>
1 1 1 16 0.0000217
2 1 2 10 0.0736
3 1 3 26 0.000451
4 2 1 17 0.0544
5 2 2 23 0.00238
6 2 3 13 0.000482
7 3 1 8 0.00525
8 3 2 7 0.179
9 3 3 15 0.000712 `summarise()` has grouped output by 'Condition_reward'. You can override using
the `.groups` argument.# A tibble: 9 × 4
# Groups: Condition_reward [3]
Condition_reward Condition_eco n shapiro_p
<fct> <fct> <int> <dbl>
1 1 1 16 0.768
2 1 2 10 0.231
3 1 3 26 0.0206
4 2 1 17 0.835
5 2 2 23 0.874
6 2 3 13 0.0509
7 3 1 8 0.156
8 3 2 7 0.825
9 3 3 15 0.0665Factor analyses
Kaiser-Meyer-Olkin factor adequacy
Call: KMO(r = only_scales_good)
Overall MSA = 0.92
MSA for each item =
S1 S2 S3 IM1 IM2 IM3 INR1 INR2 INR3 IDR1 IDR2 IDR3 EEF1 EEF2 EEF3 EEC1
0.90 0.91 0.91 0.96 0.95 0.94 0.90 0.93 0.91 0.94 0.93 0.92 0.92 0.92 0.90 0.97
EEC2 EEC3 TR1 TR2 TR3 BV1 BV2 BV3
0.90 0.88 0.92 0.80 0.84 0.97 0.90 0.91 EFA
Parallel analysis suggests that the number of factors = 5 and the number of components = NA Factor Analysis using method = minres
Call: fa(r = only_scales_good, nfactors = 5, rotate = "varimax")
Unstandardized loadings (pattern matrix) based upon covariance matrix
MR1 MR3 MR5 MR4 MR2 h2 u2 H2 U2
S1 NA NA NA 0.74 NA NA 0.30 NA NA
S2 NA NA NA 0.77 NA NA 0.26 NA NA
S3 NA NA NA 0.75 NA NA 0.30 NA NA
IM1 0.48 NA 0.46 NA NA NA 0.27 NA NA
IM2 0.61 NA 0.44 NA NA NA 0.27 NA NA
IM3 0.55 NA 0.50 NA NA NA 0.26 NA NA
INR1 NA NA 0.78 NA NA NA 0.17 NA NA
INR2 NA NA 0.75 NA NA NA 0.27 NA NA
INR3 NA NA 0.81 NA NA NA 0.14 NA NA
IDR1 0.76 NA NA NA NA NA 0.19 NA NA
IDR2 0.78 NA NA NA NA NA 0.13 NA NA
IDR3 0.81 NA NA NA NA NA 0.14 NA NA
EEF1 NA 0.80 NA NA NA NA 0.17 NA NA
EEF2 NA 0.74 NA NA NA NA 0.23 NA NA
EEF3 NA 0.73 NA NA NA NA 0.25 NA NA
EEC1 NA 0.68 NA NA NA NA 0.23 NA NA
EEC2 NA 0.63 NA NA NA NA 0.28 NA NA
EEC3 NA 0.68 NA NA NA NA 0.25 NA NA
TR1 NA NA NA NA 0.71 NA 0.35 NA NA
TR2 NA NA NA NA 0.88 NA 0.16 NA NA
TR3 NA NA NA NA 0.89 NA 0.13 NA NA
BV1 0.48 0.41 0.54 NA NA NA 0.29 NA NA
BV2 0.58 NA 0.53 NA NA NA 0.23 NA NA
BV3 0.65 NA 0.53 NA NA NA 0.20 NA NA
MR1 MR3 MR5 MR4 MR2
SS loadings NA NA NA NA NA
Proportion Var NA NA NA NA NA
Cumulative Var NA NA NA NA NA
Proportion Explained NA NA NA NA NA
Cumulative Proportion NA NA NA NA NA
Standardized loadings (pattern matrix)
item MR1 MR3 MR5 MR4 MR2 h2 u2
S1 1 NA NA NA NA NA NA NA
S2 2 NA NA NA NA NA NA NA
S3 3 NA NA NA NA NA NA NA
IM1 4 NA NA NA NA NA NA NA
IM2 5 NA NA NA NA NA NA NA
IM3 6 NA NA NA NA NA NA NA
INR1 7 NA NA NA NA NA NA NA
INR2 8 NA NA NA NA NA NA NA
INR3 9 NA NA NA NA NA NA NA
IDR1 10 NA NA NA NA NA NA NA
IDR2 11 NA NA NA NA NA NA NA
IDR3 12 NA NA NA NA NA NA NA
EEF1 13 NA NA NA NA NA NA NA
EEF2 14 NA NA NA NA NA NA NA
EEF3 15 NA NA NA NA NA NA NA
EEC1 16 NA NA NA NA NA NA NA
EEC2 17 NA NA NA NA NA NA NA
EEC3 18 NA NA NA NA NA NA NA
TR1 19 NA NA NA NA NA NA NA
TR2 20 NA NA NA NA NA NA NA
TR3 21 NA NA NA NA NA NA NA
BV1 22 NA NA NA NA NA NA NA
BV2 23 NA NA NA NA NA NA NA
BV3 24 NA NA NA NA NA NA NA
MR1 MR3 MR5 MR4 MR2
SS loadings NA NA NA NA NA
Proportion Var NA NA NA NA NA
Cumulative Var NA NA NA NA NA
Cum. factor Var NA NA NA NA NA
Mean item complexity = 2.1
Test of the hypothesis that 5 factors are sufficient.
df null model = 276 with the objective function = 28.31 with Chi Square = 3542.87
df of the model are 166 and the objective function was 4.21
The root mean square of the residuals (RMSR) is 0.03
The df corrected root mean square of the residuals is 0.04
The harmonic n.obs is 135 with the empirical chi square 66.33 with prob < 1
The total n.obs was 135 with Likelihood Chi Square = 513.19 with prob < 4.1e-37
Tucker Lewis Index of factoring reliability = 0.818
RMSEA index = 0.124 and the 90 % confidence intervals are 0.113 0.137
BIC = -301.08
Fit based upon off diagonal values = 1
Measures of factor score adequacy
MR1 MR3 MR5 MR4 MR2
Correlation of (regression) scores with factors 0.95 0.94 0.94 0.92 0.96
Multiple R square of scores with factors 0.90 0.88 0.89 0.84 0.91
Minimum correlation of possible factor scores 0.81 0.77 0.77 0.68 0.83CFA
lavaan 0.6-19 ended normally after 65 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 51
Number of observations 135
Model Test User Model:
Standard Scaled
Test Statistic 197.890 187.608
Degrees of freedom 120 120
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.055
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2781.619 2383.550
Degrees of freedom 153 153
P-value 0.000 0.000
Scaling correction factor 1.167
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.970 0.970
Tucker-Lewis Index (TLI) 0.962 0.961
Robust Comparative Fit Index (CFI) 0.973
Robust Tucker-Lewis Index (TLI) 0.965
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3313.793 -3313.793
Scaling correction factor 1.396
for the MLR correction
Loglikelihood unrestricted model (H1) -3214.848 -3214.848
Scaling correction factor 1.157
for the MLR correction
Akaike (AIC) 6729.586 6729.586
Bayesian (BIC) 6877.755 6877.755
Sample-size adjusted Bayesian (SABIC) 6716.424 6716.424
Root Mean Square Error of Approximation:
RMSEA 0.069 0.065
90 Percent confidence interval - lower 0.052 0.047
90 Percent confidence interval - upper 0.086 0.081
P-value H_0: RMSEA <= 0.050 0.037 0.087
P-value H_0: RMSEA >= 0.080 0.156 0.068
Robust RMSEA 0.066
90 Percent confidence interval - lower 0.047
90 Percent confidence interval - upper 0.084
P-value H_0: Robust RMSEA <= 0.050 0.076
P-value H_0: Robust RMSEA >= 0.080 0.108
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|) ci.lower ci.upper
EEC =~
EEC1 1.000 1.000 1.000
EEC2 1.142 0.064 17.788 0.000 1.016 1.268
EEC3 1.165 0.068 17.169 0.000 1.032 1.298
EEF =~
EEF1 1.000 1.000 1.000
EEF2 0.986 0.083 11.894 0.000 0.823 1.148
EEF3 1.001 0.081 12.404 0.000 0.843 1.159
IM =~
IM1 1.000 1.000 1.000
IM2 0.879 0.073 12.111 0.000 0.737 1.021
IM3 0.909 0.063 14.332 0.000 0.785 1.033
INR =~
INR1 1.000 1.000 1.000
INR2 1.077 0.069 15.573 0.000 0.942 1.213
INR3 1.176 0.066 17.936 0.000 1.047 1.304
TR =~
TR1 1.000 1.000 1.000
TR2 1.158 0.098 11.785 0.000 0.965 1.350
TR3 1.126 0.093 12.125 0.000 0.944 1.308
BV =~
BV1 1.000 1.000 1.000
BV2 1.113 0.079 14.114 0.000 0.958 1.267
BV3 1.058 0.084 12.614 0.000 0.893 1.222
Std.lv Std.all
1.374 0.869
1.570 0.934
1.601 0.951
1.374 0.937
1.355 0.925
1.375 0.895
1.328 0.865
1.167 0.902
1.206 0.936
1.462 0.929
1.575 0.866
1.719 0.945
1.308 0.788
1.514 0.910
1.473 0.937
1.592 0.838
1.772 0.964
1.684 0.947
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
EEC ~~
EEF 1.409 0.267 5.286 0.000 0.887 1.931
IM 1.169 0.236 4.959 0.000 0.707 1.631
INR 1.278 0.244 5.236 0.000 0.800 1.757
TR 0.823 0.217 3.792 0.000 0.398 1.249
BV 1.229 0.273 4.499 0.000 0.694 1.764
EEF ~~
IM 1.226 0.260 4.718 0.000 0.717 1.736
INR 1.303 0.233 5.596 0.000 0.846 1.759
TR 0.623 0.194 3.217 0.001 0.243 1.002
BV 1.456 0.278 5.231 0.000 0.910 2.002
IM ~~
INR 1.512 0.257 5.889 0.000 1.009 2.015
TR 0.763 0.195 3.910 0.000 0.381 1.145
BV 1.584 0.308 5.149 0.000 0.981 2.187
INR ~~
TR 0.632 0.208 3.031 0.002 0.223 1.040
BV 1.749 0.306 5.713 0.000 1.149 2.350
TR ~~
BV 0.402 0.223 1.808 0.071 -0.034 0.838
Std.lv Std.all
0.746 0.746
0.641 0.641
0.636 0.636
0.458 0.458
0.562 0.562
0.672 0.672
0.648 0.648
0.346 0.346
0.665 0.665
0.779 0.779
0.440 0.440
0.749 0.749
0.331 0.331
0.752 0.752
0.193 0.193
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.EEC1 0.613 0.118 5.177 0.000 0.381 0.845
.EEC2 0.359 0.081 4.437 0.000 0.200 0.517
.EEC3 0.274 0.086 3.182 0.001 0.105 0.443
.EEF1 0.262 0.098 2.667 0.008 0.069 0.455
.EEF2 0.309 0.111 2.777 0.005 0.091 0.527
.EEF3 0.469 0.100 4.681 0.000 0.273 0.666
.IM1 0.594 0.142 4.195 0.000 0.316 0.871
.IM2 0.312 0.091 3.441 0.001 0.134 0.490
.IM3 0.207 0.055 3.737 0.000 0.098 0.315
.INR1 0.341 0.074 4.581 0.000 0.195 0.487
.INR2 0.826 0.125 6.610 0.000 0.581 1.070
.INR3 0.351 0.106 3.321 0.001 0.144 0.558
.TR1 1.040 0.230 4.520 0.000 0.589 1.491
.TR2 0.473 0.148 3.192 0.001 0.183 0.763
.TR3 0.302 0.102 2.968 0.003 0.102 0.501
.BV1 1.072 0.209 5.129 0.000 0.662 1.481
.BV2 0.240 0.077 3.108 0.002 0.089 0.392
.BV3 0.329 0.091 3.622 0.000 0.151 0.507
EEC 1.889 0.294 6.422 0.000 1.313 2.466
EEF 1.889 0.318 5.950 0.000 1.267 2.512
IM 1.762 0.311 5.660 0.000 1.152 2.373
INR 2.136 0.306 6.972 0.000 1.536 2.737
TR 1.710 0.303 5.640 0.000 1.115 2.304
BV 2.535 0.413 6.136 0.000 1.725 3.345
Std.lv Std.all
0.613 0.245
0.359 0.127
0.274 0.097
0.262 0.122
0.309 0.144
0.469 0.199
0.594 0.252
0.312 0.187
0.207 0.124
0.341 0.138
0.826 0.250
0.351 0.106
1.040 0.378
0.473 0.171
0.302 0.122
1.072 0.297
0.240 0.071
0.329 0.104
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
1.000 1.000
R-Square:
Estimate
EEC1 0.755
EEC2 0.873
EEC3 0.903
EEF1 0.878
EEF2 0.856
EEF3 0.801
IM1 0.748
IM2 0.813
IM3 0.876
INR1 0.862
INR2 0.750
INR3 0.894
TR1 0.622
TR2 0.829
TR3 0.878
BV1 0.703
BV2 0.929
BV3 0.896Cronbach’s Alpha: EEC EEF IM INR TR BV
0.939 0.942 0.921 0.935 0.908 0.936 Omega: EEC EEF IM INR TR BV
0.946 0.942 0.929 0.938 0.911 0.944 Average Variance Extracted (AVE): EEC EEF IM INR TR BV
0.847 0.844 0.804 0.833 0.773 0.838 $type
[1] "cor.bentler"
$cov
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3 INR1
EEC1 0.000
EEC2 -0.014 0.000
EEC3 -0.010 0.010 0.000
EEF1 0.118 -0.010 -0.002 0.000
EEF2 0.071 -0.050 -0.035 0.004 0.000
EEF3 0.094 -0.035 0.004 -0.008 0.003 0.000
IM1 0.166 0.094 0.098 0.042 0.050 0.049 0.000
IM2 0.009 -0.029 -0.029 -0.035 0.013 0.048 -0.026 0.000
IM3 -0.003 -0.053 -0.033 -0.046 -0.015 0.007 -0.003 0.014 0.000
INR1 0.075 -0.016 -0.038 -0.014 -0.029 0.016 0.057 0.008 0.032 0.000
INR2 0.110 -0.025 -0.009 0.011 -0.008 -0.028 0.002 -0.028 0.004 -0.011
INR3 0.098 -0.027 -0.002 0.013 0.002 0.020 0.018 -0.026 -0.034 0.001
TR1 0.119 0.103 0.085 0.091 0.119 0.077 0.155 0.115 0.097 0.087
TR2 0.016 -0.035 -0.085 -0.007 -0.040 -0.025 0.061 -0.072 -0.037 0.021
TR3 0.016 0.021 -0.004 -0.001 -0.005 -0.035 0.043 -0.040 -0.021 -0.004
BV1 0.185 0.053 0.072 0.106 0.071 0.129 0.122 0.061 0.056 0.100
BV2 0.081 -0.023 -0.007 -0.011 -0.024 0.027 -0.019 0.000 -0.049 -0.030
BV3 0.050 -0.041 -0.051 -0.025 -0.035 0.003 0.037 0.041 -0.004 0.011
INR2 INR3 TR1 TR2 TR3 BV1 BV2 BV3
EEC1
EEC2
EEC3
EEF1
EEF2
EEF3
IM1
IM2
IM3
INR1
INR2 0.000
INR3 0.006 0.000
TR1 0.105 0.117 0.000
TR2 0.001 -0.023 0.003 0.000
TR3 -0.035 -0.040 -0.009 0.003 0.000
BV1 0.111 0.071 0.183 0.087 0.087 0.000
BV2 0.016 -0.020 0.150 -0.051 -0.036 0.002 0.000
BV3 0.000 -0.013 0.166 -0.045 -0.030 -0.025 0.005 0.000
$cov.z
EEC1 EEC2 EEC3 EEF1 EEF2 EEF3 IM1 IM2 IM3 INR1
EEC1 0.000
EEC2 -0.172 0.000
EEC3 -0.126 0.126 0.000
EEF1 1.565 -0.153 -0.037 0.000
EEF2 0.932 -0.717 -0.518 0.054 0.000
EEF3 1.354 -0.578 0.070 -0.112 0.039 0.000
IM1 2.291 1.409 1.499 0.533 0.634 0.661 0.000
IM2 0.109 -0.441 -0.492 -0.572 0.192 0.740 -0.423 0.000
IM3 -0.035 -0.771 -0.542 -0.726 -0.211 0.100 -0.048 0.214 0.000
INR1 1.037 -0.305 -0.711 -0.213 -0.425 0.200 0.908 0.146 0.563 0.000
INR2 1.416 -0.360 -0.132 0.151 -0.106 -0.302 0.031 -0.436 0.067 -0.143
INR3 1.269 -0.413 -0.030 0.200 0.033 0.240 0.245 -0.418 -0.503 0.016
TR1 2.054 1.719 1.416 1.419 1.787 1.160 2.491 2.798 2.372 1.304
TR2 0.224 -0.493 -1.140 -0.117 -0.587 -0.423 1.054 -1.055 -0.581 0.353
TR3 0.226 0.317 -0.052 -0.018 -0.076 -0.606 0.715 -0.605 -0.350 -0.070
BV1 2.636 0.901 1.223 1.621 1.093 2.086 2.446 1.151 1.084 1.825
BV2 1.226 -0.399 -0.126 -0.181 -0.357 0.361 -0.267 0.007 -0.874 -0.475
BV3 0.710 -0.678 -0.886 -0.439 -0.520 0.040 0.511 0.730 -0.077 0.177
INR2 INR3 TR1 TR2 TR3 BV1 BV2 BV3
EEC1
EEC2
EEC3
EEF1
EEF2
EEF3
IM1
IM2
IM3
INR1
INR2 0.000
INR3 0.075 0.000
TR1 1.610 1.826 0.000
TR2 0.017 -0.365 0.063 0.000
TR3 -0.521 -0.637 -0.235 0.041 0.000
BV1 1.848 1.127 3.006 1.588 1.677 0.000
BV2 0.248 -0.297 2.725 -1.095 -0.772 0.030 0.000
BV3 0.000 -0.188 2.828 -0.862 -0.563 -0.457 0.067 0.000
$summary
cov
srmr 0.057
srmr.se 0.022
srmr.exactfit.z 0.000
srmr.exactfit.pvalue 0.500
usrmr 0.000
usrmr.se 0.029
usrmr.ci.lower -0.047
usrmr.ci.upper 0.047
usrmr.closefit.h0.value 0.050
usrmr.closefit.z -1.753
usrmr.closefit.pvalue 0.960SEM
Prepare dummy variables
Full model
Create interaction terms manually (no “:”)
lavaan 0.6-19 ended normally after 87 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 70
Number of observations 135
Model Test User Model:
Standard Scaled
Test Statistic 791.632 789.585
Degrees of freedom 539 539
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.003
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3392.521 3320.180
Degrees of freedom 588 588
P-value 0.000 0.000
Scaling correction factor 1.022
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.910 0.908
Tucker-Lewis Index (TLI) 0.902 0.900
Robust Comparative Fit Index (CFI) 0.910
Robust Tucker-Lewis Index (TLI) 0.902
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4311.172 -4311.172
Scaling correction factor 1.381
for the MLR correction
Loglikelihood unrestricted model (H1) -3915.356 -3915.356
Scaling correction factor 1.046
for the MLR correction
Akaike (AIC) 8762.343 8762.343
Bayesian (BIC) 8965.713 8965.713
Sample-size adjusted Bayesian (SABIC) 8744.278 8744.278
Root Mean Square Error of Approximation:
RMSEA 0.059 0.059
90 Percent confidence interval - lower 0.050 0.050
90 Percent confidence interval - upper 0.068 0.067
P-value H_0: RMSEA <= 0.050 0.051 0.056
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.059
90 Percent confidence interval - lower 0.050
90 Percent confidence interval - upper 0.067
P-value H_0: Robust RMSEA <= 0.050 0.055
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.144 0.144
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
EEF =~
EEF1 1.000 1.330 0.931
EEF2 0.991 0.083 11.932 0.000 1.318 0.924
EEF3 1.003 0.081 12.317 0.000 1.333 0.889
EEC =~
EEC1 1.000 1.329 0.858
EEC2 1.149 0.063 18.191 0.000 1.528 0.933
EEC3 1.172 0.064 18.186 0.000 1.558 0.949
IM =~
IM1 1.000 1.242 0.845
IM2 0.884 0.074 11.955 0.000 1.098 0.891
IM3 0.919 0.062 14.910 0.000 1.141 0.934
S =~
S1 1.000 1.256 0.862
S2 1.027 0.082 12.590 0.000 1.289 0.841
S3 0.981 0.079 12.484 0.000 1.231 0.857
TR =~
TR1 1.000 1.306 0.787
TR2 1.171 0.103 11.325 0.000 1.529 0.919
TR3 1.118 0.088 12.660 0.000 1.460 0.929
BV =~
BV1 1.000 1.569 0.826
BV2 1.147 0.084 13.673 0.000 1.800 0.979
BV3 1.062 0.084 12.699 0.000 1.666 0.937
SxBV =~
S1.BV1 1.000 2.863 0.860
S2.BV2 1.051 0.107 9.822 0.000 3.009 0.898
S3.BV3 1.149 0.110 10.403 0.000 3.290 0.928
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
S ~
rw_C_2 (a1) -0.047 0.347 -0.136 0.892 -0.038 -0.018
rw_C_3 (a2) 0.278 0.368 0.755 0.450 0.221 0.092
ec_C_2 (a3) -0.044 0.405 -0.108 0.914 -0.035 -0.016
ec_C_3 (a4) 0.107 0.330 0.323 0.747 0.085 0.042
rwrE22 (a5) -0.362 0.556 -0.652 0.515 -0.288 -0.108
rwrE33 (a6) 0.142 0.549 0.259 0.796 0.113 0.036
TR1._C (tr_r1) -0.100 0.326 -0.307 0.758 -0.080 -0.064
TR2._C (tr_r2) 0.046 0.270 0.169 0.866 0.036 0.030
TR3._C (tr_r3) -0.018 0.350 -0.051 0.959 -0.014 -0.011
TR1._C (tr_r4) 0.326 0.227 1.437 0.151 0.260 0.184
TR2._C (tr_r5) -0.235 0.249 -0.944 0.345 -0.187 -0.134
TR3._C (tr_r6) 0.044 0.310 0.142 0.887 0.035 0.023
TR1._C (tr_e1) -0.165 0.240 -0.688 0.492 -0.131 -0.102
TR2._C (tr_e2) 0.148 0.290 0.512 0.609 0.118 0.096
TR3._C (tr_e3) -0.298 0.346 -0.863 0.388 -0.238 -0.176
TR1._C (tr_e4) -0.027 0.302 -0.088 0.930 -0.021 -0.017
TR2._C (tr_e5) -0.360 0.296 -1.216 0.224 -0.287 -0.226
TR3._C (tr_e6) 0.197 0.415 0.474 0.636 0.157 0.119
IM ~
S (b1) 0.503 0.091 5.499 0.000 0.508 0.508
SxBV (b2) -0.178 0.033 -5.449 0.000 -0.410 -0.410
EEF ~
IM (c1) 0.606 0.113 5.349 0.000 0.566 0.566
S (c2) 0.163 0.125 1.297 0.195 0.154 0.154
EEC ~
IM (d1) 0.439 0.081 5.423 0.000 0.410 0.410
S (d2) 0.381 0.105 3.647 0.000 0.360 0.360
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
BV 0.381 0.219 1.738 0.082 0.186 0.186
SxBV -0.710 0.451 -1.575 0.115 -0.190 -0.190
BV ~~
SxBV -1.558 0.900 -1.731 0.083 -0.347 -0.347
.EEF ~~
.EEC 0.534 0.138 3.878 0.000 0.540 0.540
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEF1 0.271 0.102 2.662 0.008 0.271 0.133
.EEF2 0.298 0.108 2.753 0.006 0.298 0.147
.EEF3 0.471 0.102 4.617 0.000 0.471 0.209
.EEC1 0.631 0.117 5.383 0.000 0.631 0.263
.EEC2 0.350 0.079 4.457 0.000 0.350 0.130
.EEC3 0.267 0.077 3.467 0.001 0.267 0.099
.IM1 0.615 0.135 4.564 0.000 0.615 0.285
.IM2 0.314 0.091 3.433 0.001 0.314 0.207
.IM3 0.192 0.051 3.728 0.000 0.192 0.128
.S1 0.546 0.110 4.956 0.000 0.546 0.257
.S2 0.686 0.160 4.276 0.000 0.686 0.292
.S3 0.550 0.124 4.419 0.000 0.550 0.266
.TR1 1.045 0.227 4.607 0.000 1.045 0.380
.TR2 0.428 0.156 2.748 0.006 0.428 0.155
.TR3 0.338 0.109 3.098 0.002 0.338 0.137
.BV1 1.144 0.214 5.345 0.000 1.144 0.317
.BV2 0.142 0.085 1.666 0.096 0.142 0.042
.BV3 0.389 0.112 3.463 0.001 0.389 0.123
.S1.BV1 2.887 0.573 5.039 0.000 2.887 0.260
.S2.BV2 2.170 0.538 4.032 0.000 2.170 0.193
.S3.BV3 1.757 0.545 3.222 0.001 1.757 0.140
.EEF 1.003 0.201 4.993 0.000 0.567 0.567
.EEC 0.974 0.149 6.525 0.000 0.551 0.551
.IM 0.884 0.175 5.054 0.000 0.574 0.574
.S 1.434 0.280 5.130 0.000 0.909 0.909
TR 1.705 0.301 5.656 0.000 1.000 1.000
BV 2.463 0.412 5.979 0.000 1.000 1.000
SxBV 8.198 3.120 2.627 0.009 1.000 1.000
R-Square:
Estimate
EEF1 0.867
EEF2 0.853
EEF3 0.791
EEC1 0.737
EEC2 0.870
EEC3 0.901
IM1 0.715
IM2 0.793
IM3 0.872
S1 0.743
S2 0.708
S3 0.734
TR1 0.620
TR2 0.845
TR3 0.863
BV1 0.683
BV2 0.958
BV3 0.877
S1.BV1 0.740
S2.BV2 0.807
S3.BV3 0.860
EEF 0.433
EEC 0.449
IM 0.426
S 0.091 EEF EEC IM S TR BV SxBV
0.942 0.939 0.921 0.889 0.908 0.936 0.924 EEF EEC IM S TR BV SxBV
0.886 0.893 0.822 0.888 0.911 0.939 0.924 EEF EEC IM S TR BV SxBV
0.793 0.800 0.711 0.727 0.773 0.835 0.805 $type
[1] "cor.bentler"
$cov
EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 IM1
EEF1 0.052
EEF2 0.055 0.051
EEF3 0.044 0.050 0.048
EEC1 0.172 0.122 0.145 0.042
EEC2 0.045 0.001 0.016 0.034 0.049
EEC3 0.054 0.017 0.057 0.039 0.057 0.051
IM1 0.114 0.119 0.117 0.244 0.175 0.180 0.084
IM2 0.037 0.081 0.117 0.088 0.053 0.055 0.068
IM3 0.027 0.054 0.075 0.077 0.030 0.051 0.090
S1 0.089 0.103 0.080 0.052 0.057 0.046 0.172
S2 0.004 0.005 0.029 0.041 0.064 0.018 0.189
S3 0.070 0.105 0.110 0.058 0.058 0.019 0.143
TR1 0.316 0.340 0.292 0.412 0.417 0.405 0.405
TR2 0.252 0.215 0.222 0.354 0.327 0.284 0.349
TR3 0.266 0.258 0.220 0.364 0.395 0.377 0.340
BV1 0.568 0.528 0.571 0.553 0.449 0.475 0.571
BV2 0.519 0.498 0.532 0.504 0.431 0.455 0.493
BV3 0.497 0.480 0.501 0.466 0.406 0.404 0.543
S1.BV1 -0.104 -0.156 -0.200 -0.082 -0.042 -0.055 -0.064
S2.BV2 -0.105 -0.139 -0.178 -0.131 -0.051 -0.065 -0.074
S3.BV3 -0.086 -0.176 -0.227 -0.133 -0.063 -0.099 -0.098
reward_Condition_reward2 0.057 0.041 0.071 0.008 0.008 0.045 0.021
reward_Condition_reward3 -0.025 0.008 -0.019 -0.039 0.016 -0.006 -0.023
eco_Condition_eco2 0.165 0.127 0.083 0.013 0.052 0.053 0.020
eco_Condition_eco3 -0.094 -0.081 -0.066 0.075 0.056 0.073 -0.010
rewardEco22 0.086 0.084 0.021 0.016 0.021 0.022 0.010
rewardEco33 -0.085 -0.063 -0.078 0.010 0.013 -0.017 -0.028
TR1.reward_Condition_reward2 0.042 0.025 0.009 0.065 -0.018 -0.016 -0.006
TR2.reward_Condition_reward2 -0.025 0.003 -0.006 0.031 0.014 -0.018 0.043
TR3.reward_Condition_reward2 0.039 0.048 0.067 0.067 0.007 -0.018 0.056
TR1.reward_Condition_reward3 -0.041 -0.068 -0.087 -0.102 -0.053 -0.069 -0.023
TR2.reward_Condition_reward3 -0.042 -0.025 -0.023 -0.055 -0.098 -0.115 -0.086
TR3.reward_Condition_reward3 -0.051 -0.062 -0.057 -0.147 -0.115 -0.134 -0.029
TR1.eco_Condition_eco2 -0.212 -0.128 -0.160 -0.144 -0.122 -0.108 -0.097
TR2.eco_Condition_eco2 -0.117 -0.030 -0.075 -0.084 -0.047 -0.053 -0.027
TR3.eco_Condition_eco2 -0.117 -0.043 -0.056 -0.117 -0.064 -0.070 -0.049
TR1.eco_Condition_eco3 0.200 0.177 0.228 0.148 0.137 0.130 0.109
TR2.eco_Condition_eco3 0.158 0.099 0.136 0.103 0.094 0.076 0.036
TR3.eco_Condition_eco3 0.137 0.063 0.078 0.096 0.076 0.056 0.038
IM2 IM3 S1 S2 S3 TR1 TR2
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2 0.093
IM3 0.107 0.101
S1 0.093 0.110 0.000
S2 0.079 0.104 -0.004 0.000
S3 0.061 0.075 0.005 0.001 0.000
TR1 0.376 0.367 0.348 0.420 0.345 0.000
TR2 0.228 0.274 0.323 0.407 0.328 -0.003 0.000
TR3 0.270 0.301 0.345 0.406 0.332 -0.001 0.001
BV1 0.528 0.540 0.338 0.280 0.317 0.189 0.093
BV2 0.534 0.504 0.318 0.252 0.293 0.153 -0.048
BV3 0.568 0.542 0.338 0.295 0.275 0.173 -0.039
S1.BV1 -0.182 -0.147 -0.255 -0.271 -0.233 -0.068 -0.010
S2.BV2 -0.100 -0.085 -0.321 -0.266 -0.276 0.003 0.003
S3.BV3 -0.114 -0.136 -0.325 -0.265 -0.333 -0.022 -0.012
reward_Condition_reward2 0.016 0.027 0.027 -0.050 0.015 0.007 -0.039
reward_Condition_reward3 0.021 0.040 -0.027 0.004 0.021 -0.010 0.001
eco_Condition_eco2 0.021 0.055 0.071 -0.060 -0.031 -0.113 -0.054
eco_Condition_eco3 -0.073 -0.043 -0.045 0.047 -0.012 0.122 0.076
rewardEco22 -0.033 -0.010 0.056 -0.067 0.003 -0.087 -0.052
rewardEco33 -0.090 -0.070 -0.037 0.006 0.044 0.079 0.093
TR1.reward_Condition_reward2 0.035 0.079 -0.036 0.044 -0.014 -0.029 0.077
TR2.reward_Condition_reward2 -0.002 0.037 -0.065 0.057 0.014 0.075 0.110
TR3.reward_Condition_reward2 -0.007 0.058 -0.063 0.065 0.005 0.017 0.110
TR1.reward_Condition_reward3 -0.044 -0.013 0.049 -0.023 -0.017 0.039 0.030
TR2.reward_Condition_reward3 -0.004 -0.033 0.063 -0.040 -0.010 0.030 0.050
TR3.reward_Condition_reward3 0.091 0.028 0.068 -0.031 -0.027 0.042 0.014
TR1.eco_Condition_eco2 -0.128 -0.092 -0.029 0.075 0.001 0.070 0.180
TR2.eco_Condition_eco2 -0.015 -0.006 -0.043 0.056 0.002 0.173 0.160
TR3.eco_Condition_eco2 -0.042 -0.037 -0.046 0.054 0.020 0.158 0.133
TR1.eco_Condition_eco3 0.172 0.125 -0.005 -0.019 -0.021 -0.047 -0.169
TR2.eco_Condition_eco3 0.127 0.098 0.024 -0.043 -0.017 -0.172 -0.150
TR3.eco_Condition_eco3 0.150 0.110 0.027 -0.053 -0.014 -0.127 -0.122
TR3 BV1 BV2 BV3 S1.BV1 S2.BV2 S3.BV3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3 0.000
BV1 0.096 0.000
BV2 -0.030 0.001 0.000
BV3 -0.020 -0.005 0.000 0.000
S1.BV1 0.030 -0.035 -0.025 -0.058 0.000
S2.BV2 0.025 0.040 0.050 0.002 -0.002 0.000
S3.BV3 0.030 0.005 0.035 0.031 -0.004 0.008 0.000
reward_Condition_reward2 -0.018 0.000 -0.020 -0.033 -0.026 -0.115 -0.087
reward_Condition_reward3 -0.048 -0.006 -0.012 -0.016 0.014 0.056 -0.040
eco_Condition_eco2 -0.089 0.032 0.047 0.075 -0.049 -0.096 -0.030
eco_Condition_eco3 0.098 0.049 0.077 0.024 0.079 0.130 0.094
rewardEco22 -0.083 -0.045 0.019 0.007 0.005 -0.059 -0.020
rewardEco33 -0.002 -0.066 -0.001 -0.050 0.031 0.042 -0.002
TR1.reward_Condition_reward2 0.018 -0.077 -0.104 -0.075 0.008 0.057 0.024
TR2.reward_Condition_reward2 0.108 -0.078 -0.138 -0.107 -0.043 -0.006 -0.051
TR3.reward_Condition_reward2 0.034 -0.015 -0.071 -0.047 -0.071 -0.032 -0.070
TR1.reward_Condition_reward3 0.040 0.035 0.056 0.000 0.021 0.000 0.107
TR2.reward_Condition_reward3 0.014 0.015 0.039 -0.010 0.063 0.031 0.119
TR3.reward_Condition_reward3 -0.020 0.025 0.080 0.058 -0.008 0.005 0.104
TR1.eco_Condition_eco2 0.159 -0.210 -0.257 -0.228 0.051 0.121 0.033
TR2.eco_Condition_eco2 0.129 -0.080 -0.118 -0.078 0.041 0.095 0.036
TR3.eco_Condition_eco2 0.083 -0.099 -0.104 -0.089 0.016 0.077 0.004
TR1.eco_Condition_eco3 -0.127 0.195 0.207 0.199 -0.130 -0.110 -0.085
TR2.eco_Condition_eco3 -0.124 0.077 0.179 0.162 -0.097 -0.076 -0.011
TR3.eco_Condition_eco3 -0.058 0.081 0.149 0.168 -0.042 -0.069 0.023
rw_C_2 rw_C_3 ec_C_2 ec_C_3 rwrE22 rwrE33
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2 0.000
reward_Condition_reward3 0.000 0.000
eco_Condition_eco2 0.000 0.000 0.000
eco_Condition_eco3 0.000 0.000 0.000 0.000
rewardEco22 0.000 0.000 0.000 0.000 0.000
rewardEco33 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.r_C_2 TR2.r_C_2 TR3.r_C_2 TR1.r_C_3 TR2.r_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2 0.000
TR2.reward_Condition_reward2 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.r_C_3 TR1.c_C_2 TR2.c_C_2 TR3.c_C_2 TR1.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3 0.000
TR1.eco_Condition_eco2 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.c_C_3 TR3.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3
TR1.eco_Condition_eco2
TR2.eco_Condition_eco2
TR3.eco_Condition_eco2
TR1.eco_Condition_eco3
TR2.eco_Condition_eco3 0.000
TR3.eco_Condition_eco3 0.000 0.000
$cov.z
EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 IM1
EEF1 0.337
EEF2 0.399 0.379
EEF3 0.337 0.397 0.383
EEC1 1.461 1.030 1.304 0.272
EEC2 0.367 0.012 0.150 0.246 0.360
EEC3 0.444 0.143 0.512 0.272 0.412 0.349
IM1 0.945 1.033 1.089 2.282 1.529 1.633 0.546
IM2 0.292 0.665 0.977 0.724 0.436 0.466 0.476
IM3 0.212 0.440 0.622 0.623 0.243 0.442 0.635
S1 0.621 0.702 0.577 0.398 0.434 0.331 1.361
S2 0.030 0.032 0.212 0.326 0.499 0.134 1.410
S3 0.516 0.765 0.864 0.472 0.459 0.141 1.132
TR1 3.971 4.340 3.888 4.735 4.641 4.480 4.818
TR2 2.894 2.574 2.821 4.070 3.693 3.190 4.284
TR3 3.066 3.148 2.870 4.164 4.339 4.022 3.953
BV1 7.570 7.739 8.266 7.476 5.938 6.165 6.835
BV2 7.521 7.632 7.914 7.389 6.207 6.620 5.964
BV3 7.267 6.908 7.121 6.425 5.558 5.747 6.732
S1.BV1 -0.666 -0.951 -1.278 -0.577 -0.285 -0.373 -0.382
S2.BV2 -0.631 -0.817 -1.074 -0.884 -0.344 -0.439 -0.443
S3.BV3 -0.479 -0.930 -1.295 -0.866 -0.416 -0.656 -0.554
reward_Condition_reward2 0.900 0.619 1.114 0.140 0.128 0.700 0.378
reward_Condition_reward3 -0.421 0.130 -0.312 -0.649 0.260 -0.096 -0.361
eco_Condition_eco2 2.442 1.761 1.247 0.195 0.754 0.741 0.330
eco_Condition_eco3 -1.484 -1.269 -1.033 1.201 0.819 1.021 -0.173
rewardEco22 1.255 1.174 0.320 0.230 0.297 0.309 0.168
rewardEco33 -1.390 -1.057 -1.380 0.189 0.202 -0.255 -0.445
TR1.reward_Condition_reward2 0.752 0.380 0.169 1.113 -0.250 -0.220 -0.123
TR2.reward_Condition_reward2 -0.425 0.048 -0.112 0.526 0.204 -0.269 0.832
TR3.reward_Condition_reward2 0.639 0.792 1.263 1.084 0.097 -0.258 1.170
TR1.reward_Condition_reward3 -0.783 -1.129 -1.657 -1.718 -0.868 -1.106 -0.379
TR2.reward_Condition_reward3 -0.625 -0.351 -0.362 -0.951 -1.486 -1.754 -1.394
TR3.reward_Condition_reward3 -0.794 -0.917 -0.928 -2.471 -1.759 -1.978 -0.534
TR1.eco_Condition_eco2 -3.270 -1.777 -2.642 -2.361 -1.689 -1.516 -1.733
TR2.eco_Condition_eco2 -1.768 -0.410 -1.161 -1.432 -0.669 -0.751 -0.483
TR3.eco_Condition_eco2 -1.756 -0.616 -0.889 -1.962 -0.957 -1.039 -1.001
TR1.eco_Condition_eco3 3.476 2.918 4.435 2.609 2.052 2.000 1.984
TR2.eco_Condition_eco3 2.473 1.506 2.315 1.769 1.351 1.072 0.669
TR3.eco_Condition_eco3 2.184 1.007 1.348 1.664 1.136 0.768 0.716
IM2 IM3 S1 S2 S3 TR1 TR2
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2 0.558
IM3 0.681 0.653
S1 0.667 0.755 0.000
S2 0.523 0.671 -0.025 0.000
S3 0.439 0.527 0.028 0.009 0.000
TR1 4.992 4.986 3.628 4.909 3.533 0.000
TR2 2.907 3.565 3.487 4.775 3.527 -0.028 0.000
TR3 3.156 3.502 3.796 4.820 3.726 -0.012 0.011
BV1 6.504 6.322 3.287 2.900 2.999 1.762 0.745
BV2 6.907 6.032 3.022 2.489 2.600 1.284 -0.344
BV3 7.332 6.800 3.021 2.793 2.324 1.483 -0.288
S1.BV1 -1.084 -0.873 -1.395 -1.761 -1.279 -0.609 -0.068
S2.BV2 -0.611 -0.512 -1.970 -1.700 -1.591 0.026 0.021
S3.BV3 -0.675 -0.794 -1.788 -1.652 -1.659 -0.180 -0.080
reward_Condition_reward2 0.247 0.425 0.436 -0.724 0.233 0.086 -0.487
reward_Condition_reward3 0.336 0.670 -0.462 0.074 0.264 -0.121 0.015
eco_Condition_eco2 0.313 0.850 1.022 -0.859 -0.405 -1.436 -0.712
eco_Condition_eco3 -1.119 -0.682 -0.640 0.689 -0.170 1.504 0.908
rewardEco22 -0.515 -0.154 0.880 -0.943 0.046 -1.048 -0.711
rewardEco33 -1.270 -1.000 -0.593 0.107 0.531 0.926 0.998
TR1.reward_Condition_reward2 0.592 1.332 -0.443 0.495 -0.164 -0.262 0.763
TR2.reward_Condition_reward2 -0.040 0.670 -0.842 0.658 0.172 0.720 1.014
TR3.reward_Condition_reward2 -0.131 1.051 -0.825 0.757 0.057 0.166 1.112
TR1.reward_Condition_reward3 -0.687 -0.205 0.670 -0.295 -0.203 0.414 0.332
TR2.reward_Condition_reward3 -0.075 -0.634 0.804 -0.482 -0.102 0.322 0.497
TR3.reward_Condition_reward3 1.467 0.492 0.888 -0.390 -0.298 0.486 0.155
TR1.eco_Condition_eco2 -2.000 -1.437 -0.365 0.860 0.010 0.668 1.965
TR2.eco_Condition_eco2 -0.248 -0.099 -0.595 0.679 0.030 1.733 1.624
TR3.eco_Condition_eco2 -0.690 -0.624 -0.643 0.677 0.238 1.578 1.425
TR1.eco_Condition_eco3 2.480 1.997 -0.058 -0.208 -0.223 -0.421 -1.639
TR2.eco_Condition_eco3 2.237 1.773 0.258 -0.460 -0.176 -1.657 -1.310
TR3.eco_Condition_eco3 2.394 1.762 0.308 -0.591 -0.148 -1.234 -1.185
TR3 BV1 BV2 BV3 S1.BV1 S2.BV2 S3.BV3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3 0.000
BV1 0.725 0.000
BV2 -0.204 0.004 0.000
BV3 -0.138 -0.023 0.001 0.000
S1.BV1 0.194 -0.152 -0.096 -0.233 0.000
S2.BV2 0.161 0.167 0.188 0.007 -0.011 0.000
S3.BV3 0.181 0.018 0.125 0.116 -0.017 0.036 0.000
reward_Condition_reward2 -0.225 -0.004 -0.256 -0.418 -0.302 -1.287 -0.999
reward_Condition_reward3 -0.595 -0.077 -0.155 -0.210 0.207 0.867 -0.669
eco_Condition_eco2 -1.155 0.389 0.573 0.913 -0.604 -1.089 -0.360
eco_Condition_eco3 1.200 0.621 1.033 0.315 0.944 1.588 1.117
rewardEco22 -1.042 -0.492 0.208 0.081 0.051 -0.556 -0.211
rewardEco33 -0.017 -0.749 -0.019 -0.639 0.445 0.701 -0.052
TR1.reward_Condition_reward2 0.171 -0.862 -1.203 -0.843 0.071 0.514 0.206
TR2.reward_Condition_reward2 1.070 -0.879 -1.629 -1.246 -0.421 -0.052 -0.468
TR3.reward_Condition_reward2 0.305 -0.170 -0.848 -0.538 -0.746 -0.336 -0.715
TR1.reward_Condition_reward3 0.454 0.436 0.749 -0.003 0.264 -0.005 1.455
TR2.reward_Condition_reward3 0.152 0.177 0.512 -0.134 0.812 0.421 1.770
TR3.reward_Condition_reward3 -0.195 0.306 1.039 0.736 -0.113 0.074 1.585
TR1.eco_Condition_eco2 1.626 -2.339 -2.842 -2.556 0.521 1.135 0.318
TR2.eco_Condition_eco2 1.341 -0.906 -1.335 -0.906 0.447 0.936 0.362
TR3.eco_Condition_eco2 0.733 -1.137 -1.185 -1.019 0.183 0.843 0.046
TR1.eco_Condition_eco3 -1.226 2.318 2.525 2.297 -1.223 -1.066 -0.763
TR2.eco_Condition_eco3 -1.193 0.868 2.149 1.906 -0.920 -0.741 -0.103
TR3.eco_Condition_eco3 -0.519 0.947 1.832 1.969 -0.445 -0.760 0.249
rw_C_2 rw_C_3 ec_C_2 ec_C_3 rwrE22 rwrE33
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2 0.000
reward_Condition_reward3 0.000 0.000
eco_Condition_eco2 0.000 0.000 0.000
eco_Condition_eco3 0.000 0.000 0.000 0.000
rewardEco22 0.000 0.000 0.000 0.000 0.000
rewardEco33 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.r_C_2 TR2.r_C_2 TR3.r_C_2 TR1.r_C_3 TR2.r_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2 0.000
TR2.reward_Condition_reward2 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.r_C_3 TR1.c_C_2 TR2.c_C_2 TR3.c_C_2 TR1.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3 0.000
TR1.eco_Condition_eco2 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.c_C_3 TR3.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3
TR1.eco_Condition_eco2
TR2.eco_Condition_eco2
TR3.eco_Condition_eco2
TR1.eco_Condition_eco3
TR2.eco_Condition_eco3 0.000
TR3.eco_Condition_eco3 0.000 0.000
$summary
cov
srmr 0.144
srmr.se 0.026
srmr.exactfit.z 2.043
srmr.exactfit.pvalue 0.021
usrmr 0.110
usrmr.se 0.022
usrmr.ci.lower 0.073
usrmr.ci.upper 0.147
usrmr.closefit.h0.value 0.050
usrmr.closefit.z 2.684
usrmr.closefit.pvalue 0.004###Simplified model
lavaan 0.6-19 ended normally after 87 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 70
Number of observations 135
Model Test User Model:
Standard Scaled
Test Statistic 791.632 789.585
Degrees of freedom 539 539
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.003
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 3392.521 3320.180
Degrees of freedom 588 588
P-value 0.000 0.000
Scaling correction factor 1.022
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.910 0.908
Tucker-Lewis Index (TLI) 0.902 0.900
Robust Comparative Fit Index (CFI) 0.910
Robust Tucker-Lewis Index (TLI) 0.902
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4311.172 -4311.172
Scaling correction factor 1.381
for the MLR correction
Loglikelihood unrestricted model (H1) -3915.356 -3915.356
Scaling correction factor 1.046
for the MLR correction
Akaike (AIC) 8762.343 8762.343
Bayesian (BIC) 8965.713 8965.713
Sample-size adjusted Bayesian (SABIC) 8744.278 8744.278
Root Mean Square Error of Approximation:
RMSEA 0.059 0.059
90 Percent confidence interval - lower 0.050 0.050
90 Percent confidence interval - upper 0.068 0.067
P-value H_0: RMSEA <= 0.050 0.051 0.056
P-value H_0: RMSEA >= 0.080 0.000 0.000
Robust RMSEA 0.059
90 Percent confidence interval - lower 0.050
90 Percent confidence interval - upper 0.067
P-value H_0: Robust RMSEA <= 0.050 0.055
P-value H_0: Robust RMSEA >= 0.080 0.000
Standardized Root Mean Square Residual:
SRMR 0.144 0.144
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
EEF =~
EEF1 1.000 1.330 0.931
EEF2 0.991 0.083 11.932 0.000 1.318 0.924
EEF3 1.003 0.081 12.317 0.000 1.333 0.889
EEC =~
EEC1 1.000 1.329 0.858
EEC2 1.149 0.063 18.191 0.000 1.528 0.933
EEC3 1.172 0.064 18.186 0.000 1.558 0.949
IM =~
IM1 1.000 1.242 0.845
IM2 0.884 0.074 11.955 0.000 1.098 0.891
IM3 0.919 0.062 14.910 0.000 1.141 0.934
S =~
S1 1.000 1.256 0.862
S2 1.027 0.082 12.590 0.000 1.289 0.841
S3 0.981 0.079 12.484 0.000 1.231 0.857
TR =~
TR1 1.000 1.306 0.787
TR2 1.171 0.103 11.325 0.000 1.529 0.919
TR3 1.118 0.088 12.660 0.000 1.460 0.929
BV =~
BV1 1.000 1.569 0.826
BV2 1.147 0.084 13.673 0.000 1.800 0.979
BV3 1.062 0.084 12.699 0.000 1.666 0.937
SxBV =~
S1.BV1 1.000 2.863 0.860
S2.BV2 1.051 0.107 9.822 0.000 3.009 0.898
S3.BV3 1.149 0.110 10.403 0.000 3.290 0.928
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
S ~
rw_C_2 (a1) -0.047 0.347 -0.136 0.892 -0.038 -0.018
rw_C_3 (a2) 0.278 0.368 0.755 0.450 0.221 0.092
ec_C_2 (a3) -0.044 0.405 -0.108 0.914 -0.035 -0.016
ec_C_3 (a4) 0.107 0.330 0.323 0.747 0.085 0.042
rwrE22 (a5) -0.362 0.556 -0.652 0.515 -0.288 -0.108
rwrE33 (a6) 0.142 0.549 0.259 0.796 0.113 0.036
TR1._C (tr_r1) -0.100 0.326 -0.307 0.758 -0.080 -0.064
TR2._C (tr_r2) 0.046 0.270 0.169 0.866 0.036 0.030
TR3._C (tr_r3) -0.018 0.350 -0.051 0.959 -0.014 -0.011
TR1._C (tr_r4) 0.326 0.227 1.437 0.151 0.260 0.184
TR2._C (tr_r5) -0.235 0.249 -0.944 0.345 -0.187 -0.134
TR3._C (tr_r6) 0.044 0.310 0.142 0.887 0.035 0.023
TR1._C (tr_e1) -0.165 0.240 -0.688 0.492 -0.131 -0.102
TR2._C (tr_e2) 0.148 0.290 0.512 0.609 0.118 0.096
TR3._C (tr_e3) -0.298 0.346 -0.863 0.388 -0.238 -0.176
TR1._C (tr_e4) -0.027 0.302 -0.088 0.930 -0.021 -0.017
TR2._C (tr_e5) -0.360 0.296 -1.216 0.224 -0.287 -0.226
TR3._C (tr_e6) 0.197 0.415 0.474 0.636 0.157 0.119
IM ~
S (b1) 0.503 0.091 5.499 0.000 0.508 0.508
SxBV (b2) -0.178 0.033 -5.449 0.000 -0.410 -0.410
EEF ~
IM (c1) 0.606 0.113 5.349 0.000 0.566 0.566
S (c2) 0.163 0.125 1.297 0.195 0.154 0.154
EEC ~
IM (d1) 0.439 0.081 5.423 0.000 0.410 0.410
S (d2) 0.381 0.105 3.647 0.000 0.360 0.360
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
TR ~~
BV 0.381 0.219 1.738 0.082 0.186 0.186
SxBV -0.710 0.451 -1.575 0.115 -0.190 -0.190
BV ~~
SxBV -1.558 0.900 -1.731 0.083 -0.347 -0.347
.EEF ~~
.EEC 0.534 0.138 3.878 0.000 0.540 0.540
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.EEF1 0.271 0.102 2.662 0.008 0.271 0.133
.EEF2 0.298 0.108 2.753 0.006 0.298 0.147
.EEF3 0.471 0.102 4.617 0.000 0.471 0.209
.EEC1 0.631 0.117 5.383 0.000 0.631 0.263
.EEC2 0.350 0.079 4.457 0.000 0.350 0.130
.EEC3 0.267 0.077 3.467 0.001 0.267 0.099
.IM1 0.615 0.135 4.564 0.000 0.615 0.285
.IM2 0.314 0.091 3.433 0.001 0.314 0.207
.IM3 0.192 0.051 3.728 0.000 0.192 0.128
.S1 0.546 0.110 4.956 0.000 0.546 0.257
.S2 0.686 0.160 4.276 0.000 0.686 0.292
.S3 0.550 0.124 4.419 0.000 0.550 0.266
.TR1 1.045 0.227 4.607 0.000 1.045 0.380
.TR2 0.428 0.156 2.748 0.006 0.428 0.155
.TR3 0.338 0.109 3.098 0.002 0.338 0.137
.BV1 1.144 0.214 5.345 0.000 1.144 0.317
.BV2 0.142 0.085 1.666 0.096 0.142 0.042
.BV3 0.389 0.112 3.463 0.001 0.389 0.123
.S1.BV1 2.887 0.573 5.039 0.000 2.887 0.260
.S2.BV2 2.170 0.538 4.032 0.000 2.170 0.193
.S3.BV3 1.757 0.545 3.222 0.001 1.757 0.140
.EEF 1.003 0.201 4.993 0.000 0.567 0.567
.EEC 0.974 0.149 6.525 0.000 0.551 0.551
.IM 0.884 0.175 5.054 0.000 0.574 0.574
.S 1.434 0.280 5.130 0.000 0.909 0.909
TR 1.705 0.301 5.656 0.000 1.000 1.000
BV 2.463 0.412 5.979 0.000 1.000 1.000
SxBV 8.198 3.120 2.627 0.009 1.000 1.000
R-Square:
Estimate
EEF1 0.867
EEF2 0.853
EEF3 0.791
EEC1 0.737
EEC2 0.870
EEC3 0.901
IM1 0.715
IM2 0.793
IM3 0.872
S1 0.743
S2 0.708
S3 0.734
TR1 0.620
TR2 0.845
TR3 0.863
BV1 0.683
BV2 0.958
BV3 0.877
S1.BV1 0.740
S2.BV2 0.807
S3.BV3 0.860
EEF 0.433
EEC 0.449
IM 0.426
S 0.091 EEF EEC IM S TR BV SxBV
0.942 0.939 0.921 0.889 0.908 0.936 0.924 EEF EEC IM S TR BV SxBV
0.886 0.893 0.822 0.888 0.911 0.939 0.924 EEF EEC IM S TR BV SxBV
0.793 0.800 0.711 0.727 0.773 0.835 0.805 $type
[1] "cor.bentler"
$cov
EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 IM1
EEF1 0.052
EEF2 0.055 0.051
EEF3 0.044 0.050 0.048
EEC1 0.172 0.122 0.145 0.042
EEC2 0.045 0.001 0.016 0.034 0.049
EEC3 0.054 0.017 0.057 0.039 0.057 0.051
IM1 0.114 0.119 0.117 0.244 0.175 0.180 0.084
IM2 0.037 0.081 0.117 0.088 0.053 0.055 0.068
IM3 0.027 0.054 0.075 0.077 0.030 0.051 0.090
S1 0.089 0.103 0.080 0.052 0.057 0.046 0.172
S2 0.004 0.005 0.029 0.041 0.064 0.018 0.189
S3 0.070 0.105 0.110 0.058 0.058 0.019 0.143
TR1 0.316 0.340 0.292 0.412 0.417 0.405 0.405
TR2 0.252 0.215 0.222 0.354 0.327 0.284 0.349
TR3 0.266 0.258 0.220 0.364 0.395 0.377 0.340
BV1 0.568 0.528 0.571 0.553 0.449 0.475 0.571
BV2 0.519 0.498 0.532 0.504 0.431 0.455 0.493
BV3 0.497 0.480 0.501 0.466 0.406 0.404 0.543
S1.BV1 -0.104 -0.156 -0.200 -0.082 -0.042 -0.055 -0.064
S2.BV2 -0.105 -0.139 -0.178 -0.131 -0.051 -0.065 -0.074
S3.BV3 -0.086 -0.176 -0.227 -0.133 -0.063 -0.099 -0.098
reward_Condition_reward2 0.057 0.041 0.071 0.008 0.008 0.045 0.021
reward_Condition_reward3 -0.025 0.008 -0.019 -0.039 0.016 -0.006 -0.023
eco_Condition_eco2 0.165 0.127 0.083 0.013 0.052 0.053 0.020
eco_Condition_eco3 -0.094 -0.081 -0.066 0.075 0.056 0.073 -0.010
rewardEco22 0.086 0.084 0.021 0.016 0.021 0.022 0.010
rewardEco33 -0.085 -0.063 -0.078 0.010 0.013 -0.017 -0.028
TR1.reward_Condition_reward2 0.042 0.025 0.009 0.065 -0.018 -0.016 -0.006
TR2.reward_Condition_reward2 -0.025 0.003 -0.006 0.031 0.014 -0.018 0.043
TR3.reward_Condition_reward2 0.039 0.048 0.067 0.067 0.007 -0.018 0.056
TR1.reward_Condition_reward3 -0.041 -0.068 -0.087 -0.102 -0.053 -0.069 -0.023
TR2.reward_Condition_reward3 -0.042 -0.025 -0.023 -0.055 -0.098 -0.115 -0.086
TR3.reward_Condition_reward3 -0.051 -0.062 -0.057 -0.147 -0.115 -0.134 -0.029
TR1.eco_Condition_eco2 -0.212 -0.128 -0.160 -0.144 -0.122 -0.108 -0.097
TR2.eco_Condition_eco2 -0.117 -0.030 -0.075 -0.084 -0.047 -0.053 -0.027
TR3.eco_Condition_eco2 -0.117 -0.043 -0.056 -0.117 -0.064 -0.070 -0.049
TR1.eco_Condition_eco3 0.200 0.177 0.228 0.148 0.137 0.130 0.109
TR2.eco_Condition_eco3 0.158 0.099 0.136 0.103 0.094 0.076 0.036
TR3.eco_Condition_eco3 0.137 0.063 0.078 0.096 0.076 0.056 0.038
IM2 IM3 S1 S2 S3 TR1 TR2
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2 0.093
IM3 0.107 0.101
S1 0.093 0.110 0.000
S2 0.079 0.104 -0.004 0.000
S3 0.061 0.075 0.005 0.001 0.000
TR1 0.376 0.367 0.348 0.420 0.345 0.000
TR2 0.228 0.274 0.323 0.407 0.328 -0.003 0.000
TR3 0.270 0.301 0.345 0.406 0.332 -0.001 0.001
BV1 0.528 0.540 0.338 0.280 0.317 0.189 0.093
BV2 0.534 0.504 0.318 0.252 0.293 0.153 -0.048
BV3 0.568 0.542 0.338 0.295 0.275 0.173 -0.039
S1.BV1 -0.182 -0.147 -0.255 -0.271 -0.233 -0.068 -0.010
S2.BV2 -0.100 -0.085 -0.321 -0.266 -0.276 0.003 0.003
S3.BV3 -0.114 -0.136 -0.325 -0.265 -0.333 -0.022 -0.012
reward_Condition_reward2 0.016 0.027 0.027 -0.050 0.015 0.007 -0.039
reward_Condition_reward3 0.021 0.040 -0.027 0.004 0.021 -0.010 0.001
eco_Condition_eco2 0.021 0.055 0.071 -0.060 -0.031 -0.113 -0.054
eco_Condition_eco3 -0.073 -0.043 -0.045 0.047 -0.012 0.122 0.076
rewardEco22 -0.033 -0.010 0.056 -0.067 0.003 -0.087 -0.052
rewardEco33 -0.090 -0.070 -0.037 0.006 0.044 0.079 0.093
TR1.reward_Condition_reward2 0.035 0.079 -0.036 0.044 -0.014 -0.029 0.077
TR2.reward_Condition_reward2 -0.002 0.037 -0.065 0.057 0.014 0.075 0.110
TR3.reward_Condition_reward2 -0.007 0.058 -0.063 0.065 0.005 0.017 0.110
TR1.reward_Condition_reward3 -0.044 -0.013 0.049 -0.023 -0.017 0.039 0.030
TR2.reward_Condition_reward3 -0.004 -0.033 0.063 -0.040 -0.010 0.030 0.050
TR3.reward_Condition_reward3 0.091 0.028 0.068 -0.031 -0.027 0.042 0.014
TR1.eco_Condition_eco2 -0.128 -0.092 -0.029 0.075 0.001 0.070 0.180
TR2.eco_Condition_eco2 -0.015 -0.006 -0.043 0.056 0.002 0.173 0.160
TR3.eco_Condition_eco2 -0.042 -0.037 -0.046 0.054 0.020 0.158 0.133
TR1.eco_Condition_eco3 0.172 0.125 -0.005 -0.019 -0.021 -0.047 -0.169
TR2.eco_Condition_eco3 0.127 0.098 0.024 -0.043 -0.017 -0.172 -0.150
TR3.eco_Condition_eco3 0.150 0.110 0.027 -0.053 -0.014 -0.127 -0.122
TR3 BV1 BV2 BV3 S1.BV1 S2.BV2 S3.BV3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3 0.000
BV1 0.096 0.000
BV2 -0.030 0.001 0.000
BV3 -0.020 -0.005 0.000 0.000
S1.BV1 0.030 -0.035 -0.025 -0.058 0.000
S2.BV2 0.025 0.040 0.050 0.002 -0.002 0.000
S3.BV3 0.030 0.005 0.035 0.031 -0.004 0.008 0.000
reward_Condition_reward2 -0.018 0.000 -0.020 -0.033 -0.026 -0.115 -0.087
reward_Condition_reward3 -0.048 -0.006 -0.012 -0.016 0.014 0.056 -0.040
eco_Condition_eco2 -0.089 0.032 0.047 0.075 -0.049 -0.096 -0.030
eco_Condition_eco3 0.098 0.049 0.077 0.024 0.079 0.130 0.094
rewardEco22 -0.083 -0.045 0.019 0.007 0.005 -0.059 -0.020
rewardEco33 -0.002 -0.066 -0.001 -0.050 0.031 0.042 -0.002
TR1.reward_Condition_reward2 0.018 -0.077 -0.104 -0.075 0.008 0.057 0.024
TR2.reward_Condition_reward2 0.108 -0.078 -0.138 -0.107 -0.043 -0.006 -0.051
TR3.reward_Condition_reward2 0.034 -0.015 -0.071 -0.047 -0.071 -0.032 -0.070
TR1.reward_Condition_reward3 0.040 0.035 0.056 0.000 0.021 0.000 0.107
TR2.reward_Condition_reward3 0.014 0.015 0.039 -0.010 0.063 0.031 0.119
TR3.reward_Condition_reward3 -0.020 0.025 0.080 0.058 -0.008 0.005 0.104
TR1.eco_Condition_eco2 0.159 -0.210 -0.257 -0.228 0.051 0.121 0.033
TR2.eco_Condition_eco2 0.129 -0.080 -0.118 -0.078 0.041 0.095 0.036
TR3.eco_Condition_eco2 0.083 -0.099 -0.104 -0.089 0.016 0.077 0.004
TR1.eco_Condition_eco3 -0.127 0.195 0.207 0.199 -0.130 -0.110 -0.085
TR2.eco_Condition_eco3 -0.124 0.077 0.179 0.162 -0.097 -0.076 -0.011
TR3.eco_Condition_eco3 -0.058 0.081 0.149 0.168 -0.042 -0.069 0.023
rw_C_2 rw_C_3 ec_C_2 ec_C_3 rwrE22 rwrE33
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2 0.000
reward_Condition_reward3 0.000 0.000
eco_Condition_eco2 0.000 0.000 0.000
eco_Condition_eco3 0.000 0.000 0.000 0.000
rewardEco22 0.000 0.000 0.000 0.000 0.000
rewardEco33 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.r_C_2 TR2.r_C_2 TR3.r_C_2 TR1.r_C_3 TR2.r_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2 0.000
TR2.reward_Condition_reward2 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.r_C_3 TR1.c_C_2 TR2.c_C_2 TR3.c_C_2 TR1.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3 0.000
TR1.eco_Condition_eco2 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.c_C_3 TR3.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3
TR1.eco_Condition_eco2
TR2.eco_Condition_eco2
TR3.eco_Condition_eco2
TR1.eco_Condition_eco3
TR2.eco_Condition_eco3 0.000
TR3.eco_Condition_eco3 0.000 0.000
$cov.z
EEF1 EEF2 EEF3 EEC1 EEC2 EEC3 IM1
EEF1 0.337
EEF2 0.399 0.379
EEF3 0.337 0.397 0.383
EEC1 1.461 1.030 1.304 0.272
EEC2 0.367 0.012 0.150 0.246 0.360
EEC3 0.444 0.143 0.512 0.272 0.412 0.349
IM1 0.945 1.033 1.089 2.282 1.529 1.633 0.546
IM2 0.292 0.665 0.977 0.724 0.436 0.466 0.476
IM3 0.212 0.440 0.622 0.623 0.243 0.442 0.635
S1 0.621 0.702 0.577 0.398 0.434 0.331 1.361
S2 0.030 0.032 0.212 0.326 0.499 0.134 1.410
S3 0.516 0.765 0.864 0.472 0.459 0.141 1.132
TR1 3.971 4.340 3.888 4.735 4.641 4.480 4.818
TR2 2.894 2.574 2.821 4.070 3.693 3.190 4.284
TR3 3.066 3.148 2.870 4.164 4.339 4.022 3.953
BV1 7.570 7.739 8.266 7.476 5.938 6.165 6.835
BV2 7.521 7.632 7.914 7.389 6.207 6.620 5.964
BV3 7.267 6.908 7.121 6.425 5.558 5.747 6.732
S1.BV1 -0.666 -0.951 -1.278 -0.577 -0.285 -0.373 -0.382
S2.BV2 -0.631 -0.817 -1.074 -0.884 -0.344 -0.439 -0.443
S3.BV3 -0.479 -0.930 -1.295 -0.866 -0.416 -0.656 -0.554
reward_Condition_reward2 0.900 0.619 1.114 0.140 0.128 0.700 0.378
reward_Condition_reward3 -0.421 0.130 -0.312 -0.649 0.260 -0.096 -0.361
eco_Condition_eco2 2.442 1.761 1.247 0.195 0.754 0.741 0.330
eco_Condition_eco3 -1.484 -1.269 -1.033 1.201 0.819 1.021 -0.173
rewardEco22 1.255 1.174 0.320 0.230 0.297 0.309 0.168
rewardEco33 -1.390 -1.057 -1.380 0.189 0.202 -0.255 -0.445
TR1.reward_Condition_reward2 0.752 0.380 0.169 1.113 -0.250 -0.220 -0.123
TR2.reward_Condition_reward2 -0.425 0.048 -0.112 0.526 0.204 -0.269 0.832
TR3.reward_Condition_reward2 0.639 0.792 1.263 1.084 0.097 -0.258 1.170
TR1.reward_Condition_reward3 -0.783 -1.129 -1.657 -1.718 -0.868 -1.106 -0.379
TR2.reward_Condition_reward3 -0.625 -0.351 -0.362 -0.951 -1.486 -1.754 -1.394
TR3.reward_Condition_reward3 -0.794 -0.917 -0.928 -2.471 -1.759 -1.978 -0.534
TR1.eco_Condition_eco2 -3.270 -1.777 -2.642 -2.361 -1.689 -1.516 -1.733
TR2.eco_Condition_eco2 -1.768 -0.410 -1.161 -1.432 -0.669 -0.751 -0.483
TR3.eco_Condition_eco2 -1.756 -0.616 -0.889 -1.962 -0.957 -1.039 -1.001
TR1.eco_Condition_eco3 3.476 2.918 4.435 2.609 2.052 2.000 1.984
TR2.eco_Condition_eco3 2.473 1.506 2.315 1.769 1.351 1.072 0.669
TR3.eco_Condition_eco3 2.184 1.007 1.348 1.664 1.136 0.768 0.716
IM2 IM3 S1 S2 S3 TR1 TR2
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2 0.558
IM3 0.681 0.653
S1 0.667 0.755 0.000
S2 0.523 0.671 -0.025 0.000
S3 0.439 0.527 0.028 0.009 0.000
TR1 4.992 4.986 3.628 4.909 3.533 0.000
TR2 2.907 3.565 3.487 4.775 3.527 -0.028 0.000
TR3 3.156 3.502 3.796 4.820 3.726 -0.012 0.011
BV1 6.504 6.322 3.287 2.900 2.999 1.762 0.745
BV2 6.907 6.032 3.022 2.489 2.600 1.284 -0.344
BV3 7.332 6.800 3.021 2.793 2.324 1.483 -0.288
S1.BV1 -1.084 -0.873 -1.395 -1.761 -1.279 -0.609 -0.068
S2.BV2 -0.611 -0.512 -1.970 -1.700 -1.591 0.026 0.021
S3.BV3 -0.675 -0.794 -1.788 -1.652 -1.659 -0.180 -0.080
reward_Condition_reward2 0.247 0.425 0.436 -0.724 0.233 0.086 -0.487
reward_Condition_reward3 0.336 0.670 -0.462 0.074 0.264 -0.121 0.015
eco_Condition_eco2 0.313 0.850 1.022 -0.859 -0.405 -1.436 -0.712
eco_Condition_eco3 -1.119 -0.682 -0.640 0.689 -0.170 1.504 0.908
rewardEco22 -0.515 -0.154 0.880 -0.943 0.046 -1.048 -0.711
rewardEco33 -1.270 -1.000 -0.593 0.107 0.531 0.926 0.998
TR1.reward_Condition_reward2 0.592 1.332 -0.443 0.495 -0.164 -0.262 0.763
TR2.reward_Condition_reward2 -0.040 0.670 -0.842 0.658 0.172 0.720 1.014
TR3.reward_Condition_reward2 -0.131 1.051 -0.825 0.757 0.057 0.166 1.112
TR1.reward_Condition_reward3 -0.687 -0.205 0.670 -0.295 -0.203 0.414 0.332
TR2.reward_Condition_reward3 -0.075 -0.634 0.804 -0.482 -0.102 0.322 0.497
TR3.reward_Condition_reward3 1.467 0.492 0.888 -0.390 -0.298 0.486 0.155
TR1.eco_Condition_eco2 -2.000 -1.437 -0.365 0.860 0.010 0.668 1.965
TR2.eco_Condition_eco2 -0.248 -0.099 -0.595 0.679 0.030 1.733 1.624
TR3.eco_Condition_eco2 -0.690 -0.624 -0.643 0.677 0.238 1.578 1.425
TR1.eco_Condition_eco3 2.480 1.997 -0.058 -0.208 -0.223 -0.421 -1.639
TR2.eco_Condition_eco3 2.237 1.773 0.258 -0.460 -0.176 -1.657 -1.310
TR3.eco_Condition_eco3 2.394 1.762 0.308 -0.591 -0.148 -1.234 -1.185
TR3 BV1 BV2 BV3 S1.BV1 S2.BV2 S3.BV3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3 0.000
BV1 0.725 0.000
BV2 -0.204 0.004 0.000
BV3 -0.138 -0.023 0.001 0.000
S1.BV1 0.194 -0.152 -0.096 -0.233 0.000
S2.BV2 0.161 0.167 0.188 0.007 -0.011 0.000
S3.BV3 0.181 0.018 0.125 0.116 -0.017 0.036 0.000
reward_Condition_reward2 -0.225 -0.004 -0.256 -0.418 -0.302 -1.287 -0.999
reward_Condition_reward3 -0.595 -0.077 -0.155 -0.210 0.207 0.867 -0.669
eco_Condition_eco2 -1.155 0.389 0.573 0.913 -0.604 -1.089 -0.360
eco_Condition_eco3 1.200 0.621 1.033 0.315 0.944 1.588 1.117
rewardEco22 -1.042 -0.492 0.208 0.081 0.051 -0.556 -0.211
rewardEco33 -0.017 -0.749 -0.019 -0.639 0.445 0.701 -0.052
TR1.reward_Condition_reward2 0.171 -0.862 -1.203 -0.843 0.071 0.514 0.206
TR2.reward_Condition_reward2 1.070 -0.879 -1.629 -1.246 -0.421 -0.052 -0.468
TR3.reward_Condition_reward2 0.305 -0.170 -0.848 -0.538 -0.746 -0.336 -0.715
TR1.reward_Condition_reward3 0.454 0.436 0.749 -0.003 0.264 -0.005 1.455
TR2.reward_Condition_reward3 0.152 0.177 0.512 -0.134 0.812 0.421 1.770
TR3.reward_Condition_reward3 -0.195 0.306 1.039 0.736 -0.113 0.074 1.585
TR1.eco_Condition_eco2 1.626 -2.339 -2.842 -2.556 0.521 1.135 0.318
TR2.eco_Condition_eco2 1.341 -0.906 -1.335 -0.906 0.447 0.936 0.362
TR3.eco_Condition_eco2 0.733 -1.137 -1.185 -1.019 0.183 0.843 0.046
TR1.eco_Condition_eco3 -1.226 2.318 2.525 2.297 -1.223 -1.066 -0.763
TR2.eco_Condition_eco3 -1.193 0.868 2.149 1.906 -0.920 -0.741 -0.103
TR3.eco_Condition_eco3 -0.519 0.947 1.832 1.969 -0.445 -0.760 0.249
rw_C_2 rw_C_3 ec_C_2 ec_C_3 rwrE22 rwrE33
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2 0.000
reward_Condition_reward3 0.000 0.000
eco_Condition_eco2 0.000 0.000 0.000
eco_Condition_eco3 0.000 0.000 0.000 0.000
rewardEco22 0.000 0.000 0.000 0.000 0.000
rewardEco33 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000 0.000
TR1.r_C_2 TR2.r_C_2 TR3.r_C_2 TR1.r_C_3 TR2.r_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2 0.000
TR2.reward_Condition_reward2 0.000 0.000
TR3.reward_Condition_reward2 0.000 0.000 0.000
TR1.reward_Condition_reward3 0.000 0.000 0.000 0.000
TR2.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR3.reward_Condition_reward3 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.r_C_3 TR1.c_C_2 TR2.c_C_2 TR3.c_C_2 TR1.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3 0.000
TR1.eco_Condition_eco2 0.000 0.000
TR2.eco_Condition_eco2 0.000 0.000 0.000
TR3.eco_Condition_eco2 0.000 0.000 0.000 0.000
TR1.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR3.eco_Condition_eco3 0.000 0.000 0.000 0.000 0.000
TR2.c_C_3 TR3.c_C_3
EEF1
EEF2
EEF3
EEC1
EEC2
EEC3
IM1
IM2
IM3
S1
S2
S3
TR1
TR2
TR3
BV1
BV2
BV3
S1.BV1
S2.BV2
S3.BV3
reward_Condition_reward2
reward_Condition_reward3
eco_Condition_eco2
eco_Condition_eco3
rewardEco22
rewardEco33
TR1.reward_Condition_reward2
TR2.reward_Condition_reward2
TR3.reward_Condition_reward2
TR1.reward_Condition_reward3
TR2.reward_Condition_reward3
TR3.reward_Condition_reward3
TR1.eco_Condition_eco2
TR2.eco_Condition_eco2
TR3.eco_Condition_eco2
TR1.eco_Condition_eco3
TR2.eco_Condition_eco3 0.000
TR3.eco_Condition_eco3 0.000 0.000
$summary
cov
srmr 0.144
srmr.se 0.026
srmr.exactfit.z 2.043
srmr.exactfit.pvalue 0.021
usrmr 0.110
usrmr.se 0.022
usrmr.ci.lower 0.073
usrmr.ci.upper 0.147
usrmr.closefit.h0.value 0.050
usrmr.closefit.z 2.684
usrmr.closefit.pvalue 0.004Group analysis
EEF
Robost two-way ANOVA
Call: rlm(formula = EEF_composite ~ Condition_reward * Condition_eco,
data = data_filtered)
Residuals:
Min 1Q Median 3Q Max
-4.6293 -0.7313 0.1667 0.7741 1.7613
Coefficients:
Value Std. Error t value
(Intercept) 5.2387 0.3067 17.0792
Condition_reward2 0.3076 0.4274 0.7198
Condition_reward3 0.3466 0.5313 0.6525
Condition_eco2 0.5946 0.4946 1.2022
Condition_eco3 0.2233 0.3898 0.5727
Condition_reward2:Condition_eco2 -0.6263 0.6314 -0.9920
Condition_reward3:Condition_eco2 -0.2748 0.8049 -0.3414
Condition_reward2:Condition_eco3 -0.1403 0.5969 -0.2350
Condition_reward3:Condition_eco3 -0.3064 0.6637 -0.4617
Residual standard error: 1.167 on 126 degrees of freedomChecks assumptions
Shapiro-Wilk normality test
data: residuals(robust_EEF)
W = 0.89492, p-value = 2.64e-08Levene's Test for Homogeneity of Variance (center = median)
Df F value Pr(>F)
group 8 0.2948 0.9666
126 Two-way ANOVA using trimmed means
Call:
t2way(formula = EEF_composite ~ Condition_reward * Condition_eco,
data = data_filtered, tr = 0.2)
value p.value
Condition_reward 0.2787 0.874
Condition_eco 1.1677 0.573
Condition_reward:Condition_eco 1.3446 0.869EEC
Two-way ANOVA using trimmed means
Call:
t2way(formula = EEC_composite ~ Condition_reward * Condition_eco,
data = data_filtered, tr = 0.2)
value p.value
Condition_reward 0.5666 0.760
Condition_eco 3.1680 0.231
Condition_reward:Condition_eco 1.8645 0.785IM
Two-way ANOVA using trimmed means
Call:
t2way(formula = IM_composite ~ Condition_reward * Condition_eco,
data = data_filtered, tr = 0.2)
value p.value
Condition_reward 1.4767 0.498
Condition_eco 0.3545 0.843
Condition_reward:Condition_eco 2.1726 0.739