UofA_Sample <- UofA_Sample %>%
mutate(AgeGroup = if_else(UofA_Sample$AGE <= median(UofA_Sample $AGE), "Younger", "Older"
))model <-'
DISC =~ DISC1 + DISC2 + DISC3 + DISC4 + DISC5 + DISC6
JOB =~ JOB1 + JOB2 +JOB3 + JOB4 + JOB5
CARE =~ CARE1 + CARE2 + CARE3 + CARE4
RISK =~ RISK1 + RISK2 + RISK3
SOC =~ SOC1 + SOC2
EMO =~ EMO1 + EMO2 + EMO3
'## configural invariance
config <- cfa(model, data = UofA_Sample, group = "AgeGroup")## Warning in lav_object_post_check(object): lavaan WARNING: some estimated ov
## variances are negative## Metric invariance
metric <- cfa(model, data = UofA_Sample, group = "AgeGroup",
#set factor loadings to be equal between groups
group.equal="loadings")
## Scalar invarance
scalar <- cfa(model, data = UofA_Sample, group = "AgeGroup",
#set factor loadings and intercepts (means) to be equal between groups
group.equal=c("loadings", "intercepts", "means"))Notes: “Std.lv” standardizes to the latent factors, while the “std.all” uses all path information to determine the standardized estimates for paths
summary(config, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 97 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 168
##
## Number of observations per group:
## Younger 1236
## Older 1209
##
## Model Test User Model:
##
## Test statistic 1658.528
## Degrees of freedom 430
## P-value (Chi-square) 0.000
## Test statistic for each group:
## Younger 825.478
## Older 833.050
##
## Model Test Baseline Model:
##
## Test statistic 32935.697
## Degrees of freedom 506
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.962
## Tucker-Lewis Index (TLI) 0.955
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -75517.333
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 151370.665
## Bayesian (BIC) 152345.368
## Sample-size adjusted Bayesian (BIC) 151811.592
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.048
## 90 Percent confidence interval - lower 0.046
## 90 Percent confidence interval - upper 0.051
## P-value RMSEA <= 0.05 0.864
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.039
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
##
## Group 1 [Younger]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC =~
## DISC1 1.000 0.862 0.798
## DISC2 1.093 0.034 32.135 0.000 0.943 0.815
## DISC3 1.136 0.034 33.277 0.000 0.980 0.836
## DISC4 1.185 0.035 33.727 0.000 1.022 0.844
## DISC5 1.157 0.033 34.933 0.000 0.998 0.866
## DISC6 1.005 0.036 27.677 0.000 0.867 0.726
## JOB =~
## JOB1 1.000 1.041 0.802
## JOB2 1.002 0.035 28.959 0.000 1.043 0.771
## JOB3 1.050 0.032 32.599 0.000 1.094 0.850
## JOB4 1.013 0.032 31.985 0.000 1.055 0.836
## JOB5 2.000 0.147 13.585 0.000 2.083 0.396
## CARE =~
## CARE1 1.000 1.148 0.956
## CARE2 0.987 0.013 78.469 0.000 1.133 0.964
## CARE3 0.941 0.015 64.344 0.000 1.080 0.919
## CARE4 2.294 0.147 15.629 0.000 2.633 0.416
## RISK =~
## RISK1 1.000 0.839 0.831
## RISK2 0.969 0.043 22.399 0.000 0.813 0.736
## RISK3 0.859 0.039 21.778 0.000 0.720 0.699
## SOC =~
## SOC1 1.000 0.882 0.744
## SOC2 0.981 0.108 9.069 0.000 0.865 0.729
## EMO =~
## EMO1 1.000 0.525 0.521
## EMO2 1.533 0.121 12.651 0.000 0.805 0.826
## EMO3 1.154 0.089 12.910 0.000 0.606 0.533
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC ~~
## JOB 0.228 0.030 7.711 0.000 0.254 0.254
## CARE 0.296 0.032 9.373 0.000 0.299 0.299
## RISK 0.155 0.024 6.323 0.000 0.214 0.214
## SOC 0.073 0.027 2.700 0.007 0.097 0.097
## EMO 0.126 0.018 6.990 0.000 0.279 0.279
## JOB ~~
## CARE 0.136 0.037 3.674 0.000 0.113 0.113
## RISK 0.180 0.030 5.997 0.000 0.206 0.206
## SOC 0.178 0.035 5.097 0.000 0.193 0.193
## EMO 0.136 0.022 6.339 0.000 0.249 0.249
## CARE ~~
## RISK 0.194 0.032 6.153 0.000 0.202 0.202
## SOC 0.143 0.036 3.976 0.000 0.141 0.141
## EMO 0.130 0.022 5.877 0.000 0.216 0.216
## RISK ~~
## SOC 0.189 0.030 6.258 0.000 0.256 0.256
## EMO 0.106 0.018 5.930 0.000 0.240 0.240
## SOC ~~
## EMO 0.132 0.022 6.116 0.000 0.285 0.285
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 2.204 0.031 71.669 0.000 2.204 2.039
## .DISC2 2.016 0.033 61.244 0.000 2.016 1.742
## .DISC3 1.988 0.033 59.612 0.000 1.988 1.696
## .DISC4 1.947 0.034 56.546 0.000 1.947 1.608
## .DISC5 2.150 0.033 65.624 0.000 2.150 1.867
## .DISC6 1.928 0.034 56.761 0.000 1.928 1.615
## .JOB1 2.823 0.037 76.461 0.000 2.823 2.175
## .JOB2 2.999 0.039 77.857 0.000 2.999 2.215
## .JOB3 2.643 0.037 72.268 0.000 2.643 2.056
## .JOB4 2.486 0.036 69.257 0.000 2.486 1.970
## .JOB5 7.639 0.150 51.085 0.000 7.639 1.453
## .CARE1 1.731 0.034 50.652 0.000 1.731 1.441
## .CARE2 1.719 0.033 51.424 0.000 1.719 1.463
## .CARE3 1.693 0.033 50.691 0.000 1.693 1.442
## .CARE4 4.792 0.180 26.591 0.000 4.792 0.756
## .RISK1 2.797 0.029 97.466 0.000 2.797 2.772
## .RISK2 2.705 0.031 86.109 0.000 2.705 2.449
## .RISK3 3.095 0.029 105.523 0.000 3.095 3.001
## .SOC1 3.374 0.034 99.988 0.000 3.374 2.844
## .SOC2 3.066 0.034 90.790 0.000 3.066 2.582
## .EMO1 3.036 0.029 105.839 0.000 3.036 3.010
## .EMO2 2.634 0.028 95.080 0.000 2.634 2.704
## .EMO3 2.657 0.032 82.240 0.000 2.657 2.339
## DISC 0.000 0.000 0.000
## JOB 0.000 0.000 0.000
## CARE 0.000 0.000 0.000
## RISK 0.000 0.000 0.000
## SOC 0.000 0.000 0.000
## EMO 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 0.425 0.020 21.417 0.000 0.425 0.364
## .DISC2 0.451 0.021 20.975 0.000 0.451 0.337
## .DISC3 0.414 0.020 20.276 0.000 0.414 0.301
## .DISC4 0.421 0.021 19.951 0.000 0.421 0.287
## .DISC5 0.331 0.018 18.895 0.000 0.331 0.249
## .DISC6 0.674 0.030 22.678 0.000 0.674 0.473
## .JOB1 0.601 0.031 19.366 0.000 0.601 0.357
## .JOB2 0.745 0.036 20.447 0.000 0.745 0.406
## .JOB3 0.458 0.027 16.846 0.000 0.458 0.277
## .JOB4 0.479 0.027 17.730 0.000 0.479 0.301
## .JOB5 23.303 0.958 24.314 0.000 23.303 0.843
## .CARE1 0.125 0.009 14.255 0.000 0.125 0.087
## .CARE2 0.098 0.008 12.220 0.000 0.098 0.071
## .CARE3 0.213 0.011 19.880 0.000 0.213 0.155
## .CARE4 33.206 1.345 24.683 0.000 33.206 0.827
## .RISK1 0.315 0.028 11.383 0.000 0.315 0.309
## .RISK2 0.559 0.033 17.190 0.000 0.559 0.458
## .RISK3 0.544 0.029 18.917 0.000 0.544 0.512
## .SOC1 0.629 0.087 7.247 0.000 0.629 0.447
## .SOC2 0.660 0.084 7.846 0.000 0.660 0.469
## .EMO1 0.742 0.036 20.795 0.000 0.742 0.729
## .EMO2 0.301 0.044 6.839 0.000 0.301 0.317
## .EMO3 0.923 0.045 20.424 0.000 0.923 0.715
## DISC 0.744 0.045 16.550 0.000 1.000 1.000
## JOB 1.084 0.066 16.367 0.000 1.000 1.000
## CARE 1.318 0.058 22.617 0.000 1.000 1.000
## RISK 0.703 0.046 15.275 0.000 1.000 1.000
## SOC 0.778 0.097 8.007 0.000 1.000 1.000
## EMO 0.276 0.034 8.070 0.000 1.000 1.000
##
##
## Group 2 [Older]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC =~
## DISC1 1.000 0.686 0.784
## DISC2 0.960 0.035 27.760 0.000 0.659 0.749
## DISC3 0.885 0.032 27.325 0.000 0.607 0.740
## DISC4 0.969 0.031 31.111 0.000 0.665 0.821
## DISC5 1.118 0.032 34.798 0.000 0.767 0.900
## DISC6 0.887 0.033 26.781 0.000 0.609 0.728
## JOB =~
## JOB1 1.000 1.086 0.901
## JOB2 1.052 0.023 45.789 0.000 1.142 0.884
## JOB3 0.802 0.018 44.306 0.000 0.871 0.871
## JOB4 0.834 0.018 46.810 0.000 0.905 0.893
## JOB5 3.169 0.132 24.007 0.000 3.440 0.607
## CARE =~
## CARE1 1.000 0.716 0.955
## CARE2 1.026 0.014 73.779 0.000 0.734 0.958
## CARE3 1.093 0.018 61.057 0.000 0.782 0.912
## CARE4 2.996 0.181 16.527 0.000 2.144 0.440
## RISK =~
## RISK1 1.000 0.765 0.803
## RISK2 1.122 0.047 23.658 0.000 0.859 0.765
## RISK3 1.067 0.045 23.562 0.000 0.816 0.757
## SOC =~
## SOC1 1.000 1.300 1.032
## SOC2 0.631 0.115 5.480 0.000 0.820 0.605
## EMO =~
## EMO1 1.000 0.672 0.678
## EMO2 1.073 0.077 13.908 0.000 0.721 0.821
## EMO3 0.715 0.058 12.280 0.000 0.480 0.430
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC ~~
## JOB 0.154 0.024 6.468 0.000 0.207 0.207
## CARE 0.100 0.015 6.475 0.000 0.204 0.204
## RISK 0.027 0.017 1.551 0.121 0.051 0.051
## SOC -0.071 0.026 -2.731 0.006 -0.080 -0.080
## EMO 0.108 0.017 6.264 0.000 0.234 0.234
## JOB ~~
## CARE 0.072 0.024 3.033 0.002 0.092 0.092
## RISK 0.101 0.027 3.675 0.000 0.122 0.122
## SOC -0.061 0.041 -1.499 0.134 -0.043 -0.043
## EMO 0.101 0.026 3.949 0.000 0.138 0.138
## CARE ~~
## RISK 0.020 0.018 1.146 0.252 0.037 0.037
## SOC 0.023 0.026 0.884 0.377 0.025 0.025
## EMO 0.051 0.016 3.114 0.002 0.106 0.106
## RISK ~~
## SOC 0.131 0.031 4.222 0.000 0.131 0.131
## EMO 0.105 0.020 5.311 0.000 0.205 0.205
## SOC ~~
## EMO 0.131 0.029 4.532 0.000 0.150 0.150
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 1.635 0.025 64.963 0.000 1.635 1.868
## .DISC2 1.538 0.025 60.811 0.000 1.538 1.749
## .DISC3 1.444 0.024 61.179 0.000 1.444 1.760
## .DISC4 1.407 0.023 60.451 0.000 1.407 1.739
## .DISC5 1.551 0.024 63.310 0.000 1.551 1.821
## .DISC6 1.393 0.024 57.884 0.000 1.393 1.665
## .JOB1 1.796 0.035 51.830 0.000 1.796 1.491
## .JOB2 1.878 0.037 50.565 0.000 1.878 1.454
## .JOB3 1.586 0.029 55.124 0.000 1.586 1.585
## .JOB4 1.595 0.029 54.677 0.000 1.595 1.572
## .JOB5 3.957 0.163 24.261 0.000 3.957 0.698
## .CARE1 1.280 0.022 59.346 0.000 1.280 1.707
## .CARE2 1.289 0.022 58.460 0.000 1.289 1.681
## .CARE3 1.315 0.025 53.329 0.000 1.315 1.534
## .CARE4 2.082 0.140 14.863 0.000 2.082 0.427
## .RISK1 2.539 0.027 92.632 0.000 2.539 2.664
## .RISK2 2.512 0.032 77.742 0.000 2.512 2.236
## .RISK3 2.663 0.031 85.875 0.000 2.663 2.470
## .SOC1 3.385 0.036 93.449 0.000 3.385 2.688
## .SOC2 2.883 0.039 73.943 0.000 2.883 2.127
## .EMO1 2.727 0.029 95.659 0.000 2.727 2.751
## .EMO2 2.264 0.025 89.613 0.000 2.264 2.577
## .EMO3 2.647 0.032 82.344 0.000 2.647 2.368
## DISC 0.000 0.000 0.000
## JOB 0.000 0.000 0.000
## CARE 0.000 0.000 0.000
## RISK 0.000 0.000 0.000
## SOC 0.000 0.000 0.000
## EMO 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 0.296 0.014 21.135 0.000 0.296 0.386
## .DISC2 0.339 0.016 21.828 0.000 0.339 0.439
## .DISC3 0.305 0.014 21.987 0.000 0.305 0.453
## .DISC4 0.213 0.011 20.055 0.000 0.213 0.326
## .DISC5 0.138 0.009 15.321 0.000 0.138 0.190
## .DISC6 0.330 0.015 22.170 0.000 0.330 0.471
## .JOB1 0.273 0.016 17.481 0.000 0.273 0.188
## .JOB2 0.364 0.019 18.729 0.000 0.364 0.218
## .JOB3 0.241 0.012 19.457 0.000 0.241 0.241
## .JOB4 0.209 0.012 18.143 0.000 0.209 0.203
## .JOB5 20.318 0.859 23.664 0.000 20.318 0.632
## .CARE1 0.050 0.004 13.447 0.000 0.050 0.088
## .CARE2 0.048 0.004 12.697 0.000 0.048 0.082
## .CARE3 0.123 0.006 19.686 0.000 0.123 0.168
## .CARE4 19.119 0.785 24.365 0.000 19.119 0.806
## .RISK1 0.323 0.023 13.955 0.000 0.323 0.355
## .RISK2 0.524 0.032 16.299 0.000 0.524 0.415
## .RISK3 0.496 0.030 16.720 0.000 0.496 0.427
## .SOC1 -0.102 0.301 -0.339 0.734 -0.102 -0.064
## .SOC2 1.165 0.129 9.025 0.000 1.165 0.634
## .EMO1 0.531 0.037 14.483 0.000 0.531 0.540
## .EMO2 0.252 0.035 7.134 0.000 0.252 0.326
## .EMO3 1.019 0.045 22.650 0.000 1.019 0.815
## DISC 0.471 0.030 15.885 0.000 1.000 1.000
## JOB 1.179 0.059 19.977 0.000 1.000 1.000
## CARE 0.512 0.023 22.295 0.000 1.000 1.000
## RISK 0.586 0.039 14.852 0.000 1.000 1.000
## SOC 1.689 0.308 5.481 0.000 1.000 1.000
## EMO 0.452 0.045 10.075 0.000 1.000 1.000summary(metric, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 75 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 168
## Number of equality constraints 17
##
## Number of observations per group:
## Younger 1236
## Older 1209
##
## Model Test User Model:
##
## Test statistic 1919.108
## Degrees of freedom 447
## P-value (Chi-square) 0.000
## Test statistic for each group:
## Younger 965.008
## Older 954.100
##
## Model Test Baseline Model:
##
## Test statistic 32935.697
## Degrees of freedom 506
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.955
## Tucker-Lewis Index (TLI) 0.949
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -75647.623
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 151597.245
## Bayesian (BIC) 152473.317
## Sample-size adjusted Bayesian (BIC) 151993.554
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.052
## 90 Percent confidence interval - lower 0.050
## 90 Percent confidence interval - upper 0.054
## P-value RMSEA <= 0.05 0.093
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.047
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
##
## Group 1 [Younger]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC =~
## DISC1 1.000 0.905 0.815
## DISC2 (.p2.) 1.035 0.024 42.544 0.000 0.937 0.812
## DISC3 (.p3.) 1.025 0.024 43.163 0.000 0.928 0.817
## DISC4 (.p4.) 1.080 0.024 45.615 0.000 0.978 0.829
## DISC5 (.p5.) 1.148 0.023 49.227 0.000 1.039 0.878
## DISC6 (.p6.) 0.953 0.025 38.479 0.000 0.863 0.724
## JOB =~
## JOB1 1.000 1.102 0.833
## JOB2 (.p8.) 1.032 0.019 52.966 0.000 1.137 0.810
## JOB3 (.p9.) 0.874 0.016 54.747 0.000 0.963 0.792
## JOB4 (.10.) 0.886 0.016 56.389 0.000 0.976 0.797
## JOB5 (.11.) 2.587 0.098 26.274 0.000 2.852 0.509
## CARE =~
## CARE1 1.000 1.120 0.951
## CARE2 (.13.) 1.008 0.009 107.007 0.000 1.129 0.964
## CARE3 (.14.) 1.006 0.011 87.530 0.000 1.127 0.926
## CARE4 (.15.) 2.594 0.115 22.574 0.000 2.905 0.450
## RISK =~
## RISK1 1.000 0.793 0.800
## RISK2 (.17.) 1.048 0.032 32.473 0.000 0.831 0.748
## RISK3 (.18.) 0.962 0.030 31.993 0.000 0.762 0.726
## SOC =~
## SOC1 1.000 0.947 0.796
## SOC2 (.20.) 0.849 0.077 11.096 0.000 0.804 0.679
## EMO =~
## EMO1 1.000 0.602 0.583
## EMO2 (.22.) 1.282 0.068 18.868 0.000 0.772 0.795
## EMO3 (.23.) 0.901 0.049 18.304 0.000 0.542 0.487
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC ~~
## JOB 0.234 0.032 7.243 0.000 0.234 0.234
## CARE 0.303 0.032 9.450 0.000 0.299 0.299
## RISK 0.156 0.024 6.439 0.000 0.218 0.218
## SOC 0.064 0.030 2.147 0.032 0.075 0.075
## EMO 0.157 0.021 7.604 0.000 0.287 0.287
## JOB ~~
## CARE 0.120 0.038 3.162 0.002 0.098 0.098
## RISK 0.188 0.030 6.259 0.000 0.215 0.215
## SOC 0.198 0.038 5.203 0.000 0.190 0.190
## EMO 0.176 0.025 6.970 0.000 0.264 0.264
## CARE ~~
## RISK 0.179 0.029 6.117 0.000 0.201 0.201
## SOC 0.147 0.037 4.024 0.000 0.139 0.139
## EMO 0.153 0.024 6.327 0.000 0.227 0.227
## RISK ~~
## SOC 0.186 0.029 6.371 0.000 0.248 0.248
## EMO 0.122 0.019 6.444 0.000 0.255 0.255
## SOC ~~
## EMO 0.167 0.024 6.838 0.000 0.293 0.293
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 2.204 0.032 69.722 0.000 2.204 1.983
## .DISC2 2.016 0.033 61.427 0.000 2.016 1.747
## .DISC3 1.988 0.032 61.510 0.000 1.988 1.750
## .DISC4 1.947 0.034 58.021 0.000 1.947 1.650
## .DISC5 2.150 0.034 63.876 0.000 2.150 1.817
## .DISC6 1.928 0.034 56.876 0.000 1.928 1.618
## .JOB1 2.823 0.038 75.008 0.000 2.823 2.134
## .JOB2 2.999 0.040 75.133 0.000 2.999 2.137
## .JOB3 2.643 0.035 76.384 0.000 2.643 2.173
## .JOB4 2.486 0.035 71.376 0.000 2.486 2.030
## .JOB5 7.639 0.159 47.931 0.000 7.639 1.363
## .CARE1 1.731 0.033 51.670 0.000 1.731 1.470
## .CARE2 1.719 0.033 51.601 0.000 1.719 1.468
## .CARE3 1.693 0.035 48.935 0.000 1.693 1.392
## .CARE4 4.792 0.184 26.099 0.000 4.792 0.742
## .RISK1 2.797 0.028 99.296 0.000 2.797 2.824
## .RISK2 2.705 0.032 85.576 0.000 2.705 2.434
## .RISK3 3.095 0.030 103.571 0.000 3.095 2.946
## .SOC1 3.374 0.034 99.778 0.000 3.374 2.838
## .SOC2 3.066 0.034 91.069 0.000 3.066 2.590
## .EMO1 3.036 0.029 103.388 0.000 3.036 2.941
## .EMO2 2.634 0.028 95.409 0.000 2.634 2.714
## .EMO3 2.657 0.032 83.811 0.000 2.657 2.384
## DISC 0.000 0.000 0.000
## JOB 0.000 0.000 0.000
## CARE 0.000 0.000 0.000
## RISK 0.000 0.000 0.000
## SOC 0.000 0.000 0.000
## EMO 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 0.415 0.020 21.068 0.000 0.415 0.336
## .DISC2 0.453 0.021 21.139 0.000 0.453 0.341
## .DISC3 0.430 0.020 21.011 0.000 0.430 0.333
## .DISC4 0.435 0.021 20.656 0.000 0.435 0.313
## .DISC5 0.320 0.017 18.372 0.000 0.320 0.228
## .DISC6 0.675 0.030 22.770 0.000 0.675 0.475
## .JOB1 0.536 0.030 18.145 0.000 0.536 0.306
## .JOB2 0.677 0.035 19.206 0.000 0.677 0.344
## .JOB3 0.552 0.028 19.932 0.000 0.552 0.373
## .JOB4 0.547 0.028 19.762 0.000 0.547 0.365
## .JOB5 23.265 0.976 23.838 0.000 23.265 0.741
## .CARE1 0.132 0.008 15.550 0.000 0.132 0.095
## .CARE2 0.097 0.008 12.536 0.000 0.097 0.071
## .CARE3 0.211 0.011 19.329 0.000 0.211 0.142
## .CARE4 33.224 1.348 24.645 0.000 33.224 0.797
## .RISK1 0.353 0.024 14.719 0.000 0.353 0.360
## .RISK2 0.544 0.031 17.614 0.000 0.544 0.441
## .RISK3 0.522 0.028 18.584 0.000 0.522 0.473
## .SOC1 0.517 0.084 6.162 0.000 0.517 0.366
## .SOC2 0.754 0.066 11.422 0.000 0.754 0.539
## .EMO1 0.704 0.035 19.878 0.000 0.704 0.660
## .EMO2 0.346 0.035 9.780 0.000 0.346 0.368
## .EMO3 0.948 0.043 22.119 0.000 0.948 0.763
## DISC 0.820 0.043 18.916 0.000 1.000 1.000
## JOB 1.215 0.061 19.964 0.000 1.000 1.000
## CARE 1.255 0.054 23.161 0.000 1.000 1.000
## RISK 0.628 0.037 16.775 0.000 1.000 1.000
## SOC 0.896 0.094 9.498 0.000 1.000 1.000
## EMO 0.363 0.032 11.203 0.000 1.000 1.000
##
##
## Group 2 [Older]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC =~
## DISC1 1.000 0.642 0.759
## DISC2 (.p2.) 1.035 0.024 42.544 0.000 0.665 0.753
## DISC3 (.p3.) 1.025 0.024 43.163 0.000 0.659 0.769
## DISC4 (.p4.) 1.080 0.024 45.615 0.000 0.694 0.835
## DISC5 (.p5.) 1.148 0.023 49.227 0.000 0.738 0.887
## DISC6 (.p6.) 0.953 0.025 38.479 0.000 0.613 0.731
## JOB =~
## JOB1 1.000 1.055 0.887
## JOB2 (.p8.) 1.032 0.019 52.966 0.000 1.088 0.864
## JOB3 (.p9.) 0.874 0.016 54.747 0.000 0.922 0.891
## JOB4 (.10.) 0.886 0.016 56.389 0.000 0.934 0.907
## JOB5 (.11.) 2.587 0.098 26.274 0.000 2.729 0.510
## CARE =~
## CARE1 1.000 0.732 0.958
## CARE2 (.13.) 1.008 0.009 107.007 0.000 0.737 0.958
## CARE3 (.14.) 1.006 0.011 87.530 0.000 0.736 0.898
## CARE4 (.15.) 2.594 0.115 22.574 0.000 1.897 0.397
## RISK =~
## RISK1 1.000 0.803 0.829
## RISK2 (.17.) 1.048 0.032 32.473 0.000 0.842 0.754
## RISK3 (.18.) 0.962 0.030 31.993 0.000 0.773 0.730
## SOC =~
## SOC1 1.000 1.123 0.892
## SOC2 (.20.) 0.849 0.077 11.096 0.000 0.954 0.701
## EMO =~
## EMO1 1.000 0.595 0.613
## EMO2 (.22.) 1.282 0.068 18.868 0.000 0.762 0.866
## EMO3 (.23.) 0.901 0.049 18.304 0.000 0.535 0.469
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC ~~
## JOB 0.144 0.022 6.685 0.000 0.213 0.213
## CARE 0.096 0.015 6.532 0.000 0.204 0.204
## RISK 0.026 0.017 1.546 0.122 0.051 0.051
## SOC -0.067 0.024 -2.796 0.005 -0.093 -0.093
## EMO 0.086 0.014 6.275 0.000 0.224 0.224
## JOB ~~
## CARE 0.075 0.023 3.182 0.001 0.097 0.097
## RISK 0.099 0.028 3.543 0.000 0.117 0.117
## SOC -0.048 0.039 -1.233 0.218 -0.040 -0.040
## EMO 0.083 0.021 3.894 0.000 0.132 0.132
## CARE ~~
## RISK 0.022 0.019 1.163 0.245 0.038 0.038
## SOC 0.012 0.026 0.470 0.639 0.015 0.015
## EMO 0.044 0.014 3.042 0.002 0.101 0.101
## RISK ~~
## SOC 0.150 0.032 4.705 0.000 0.166 0.166
## EMO 0.090 0.018 5.111 0.000 0.189 0.189
## SOC ~~
## EMO 0.089 0.024 3.683 0.000 0.133 0.133
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 1.635 0.024 67.169 0.000 1.635 1.932
## .DISC2 1.538 0.025 60.574 0.000 1.538 1.742
## .DISC3 1.444 0.025 58.644 0.000 1.444 1.687
## .DISC4 1.407 0.024 58.846 0.000 1.407 1.692
## .DISC5 1.551 0.024 64.874 0.000 1.551 1.866
## .DISC6 1.393 0.024 57.767 0.000 1.393 1.661
## .JOB1 1.796 0.034 52.518 0.000 1.796 1.510
## .JOB2 1.878 0.036 51.859 0.000 1.878 1.491
## .JOB3 1.586 0.030 53.266 0.000 1.586 1.532
## .JOB4 1.595 0.030 53.825 0.000 1.595 1.548
## .JOB5 3.957 0.154 25.700 0.000 3.957 0.739
## .CARE1 1.280 0.022 58.279 0.000 1.280 1.676
## .CARE2 1.289 0.022 58.222 0.000 1.289 1.674
## .CARE3 1.315 0.024 55.799 0.000 1.315 1.605
## .CARE4 2.082 0.137 15.154 0.000 2.082 0.436
## .RISK1 2.539 0.028 91.054 0.000 2.539 2.619
## .RISK2 2.512 0.032 78.220 0.000 2.512 2.250
## .RISK3 2.663 0.030 87.449 0.000 2.663 2.515
## .SOC1 3.385 0.036 93.560 0.000 3.385 2.691
## .SOC2 2.883 0.039 73.723 0.000 2.883 2.120
## .EMO1 2.727 0.028 97.754 0.000 2.727 2.811
## .EMO2 2.264 0.025 89.397 0.000 2.264 2.571
## .EMO3 2.647 0.033 80.669 0.000 2.647 2.320
## DISC 0.000 0.000 0.000
## JOB 0.000 0.000 0.000
## CARE 0.000 0.000 0.000
## RISK 0.000 0.000 0.000
## SOC 0.000 0.000 0.000
## EMO 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 0.304 0.014 21.743 0.000 0.304 0.424
## .DISC2 0.337 0.015 21.842 0.000 0.337 0.432
## .DISC3 0.299 0.014 21.550 0.000 0.299 0.408
## .DISC4 0.210 0.011 19.683 0.000 0.210 0.303
## .DISC5 0.147 0.009 16.710 0.000 0.147 0.213
## .DISC6 0.328 0.015 22.179 0.000 0.328 0.466
## .JOB1 0.300 0.016 18.606 0.000 0.300 0.213
## .JOB2 0.402 0.020 19.870 0.000 0.402 0.253
## .JOB3 0.221 0.012 18.346 0.000 0.221 0.206
## .JOB4 0.188 0.011 17.051 0.000 0.188 0.177
## .JOB5 21.204 0.882 24.045 0.000 21.204 0.740
## .CARE1 0.048 0.004 12.605 0.000 0.048 0.082
## .CARE2 0.048 0.004 12.614 0.000 0.048 0.082
## .CARE3 0.130 0.006 20.640 0.000 0.130 0.194
## .CARE4 19.215 0.787 24.418 0.000 19.215 0.842
## .RISK1 0.295 0.023 13.062 0.000 0.295 0.313
## .RISK2 0.538 0.031 17.483 0.000 0.538 0.431
## .RISK3 0.524 0.028 18.585 0.000 0.524 0.467
## .SOC1 0.322 0.118 2.740 0.006 0.322 0.204
## .SOC2 0.939 0.093 10.145 0.000 0.939 0.508
## .EMO1 0.587 0.031 19.018 0.000 0.587 0.624
## .EMO2 0.194 0.032 6.118 0.000 0.194 0.251
## .EMO3 1.015 0.045 22.553 0.000 1.015 0.780
## DISC 0.413 0.022 18.411 0.000 1.000 1.000
## JOB 1.113 0.054 20.501 0.000 1.000 1.000
## CARE 0.535 0.023 23.051 0.000 1.000 1.000
## RISK 0.646 0.038 17.122 0.000 1.000 1.000
## SOC 1.261 0.130 9.724 0.000 1.000 1.000
## EMO 0.354 0.031 11.569 0.000 1.000 1.000summary(scalar, standardized = TRUE, fit.measures = TRUE)## lavaan 0.6-7 ended normally after 115 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 168
## Number of equality constraints 40
##
## Number of observations per group:
## Younger 1236
## Older 1209
##
## Model Test User Model:
##
## Test statistic 2789.526
## Degrees of freedom 470
## P-value (Chi-square) 0.000
## Test statistic for each group:
## Younger 1505.454
## Older 1284.072
##
## Model Test Baseline Model:
##
## Test statistic 32935.697
## Degrees of freedom 506
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.928
## Tucker-Lewis Index (TLI) 0.923
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -76082.832
## Loglikelihood unrestricted model (H1) NA
##
## Akaike (AIC) 152421.663
## Bayesian (BIC) 153164.294
## Sample-size adjusted Bayesian (BIC) 152757.608
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.064
## 90 Percent confidence interval - lower 0.061
## 90 Percent confidence interval - upper 0.066
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.110
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
##
## Group 1 [Younger]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC =~
## DISC1 1.000 0.983 0.836
## DISC2 (.p2.) 1.012 0.022 45.150 0.000 0.995 0.827
## DISC3 (.p3.) 1.017 0.022 46.181 0.000 0.999 0.836
## DISC4 (.p4.) 1.065 0.022 48.617 0.000 1.046 0.846
## DISC5 (.p5.) 1.137 0.022 52.687 0.000 1.117 0.892
## DISC6 (.p6.) 0.952 0.023 41.163 0.000 0.935 0.751
## JOB =~
## JOB1 1.000 1.251 0.861
## JOB2 (.p8.) 1.042 0.018 59.243 0.000 1.304 0.843
## JOB3 (.p9.) 0.904 0.015 61.837 0.000 1.131 0.838
## JOB4 (.10.) 0.887 0.014 62.896 0.000 1.109 0.835
## JOB5 (.11.) 2.784 0.089 31.205 0.000 3.483 0.581
## CARE =~
## CARE1 1.000 1.167 0.955
## CARE2 (.13.) 1.005 0.009 110.311 0.000 1.172 0.966
## CARE3 (.14.) 0.996 0.011 89.534 0.000 1.162 0.930
## CARE4 (.15.) 2.779 0.113 24.610 0.000 3.242 0.484
## RISK =~
## RISK1 1.000 0.812 0.807
## RISK2 (.17.) 1.035 0.031 33.158 0.000 0.841 0.749
## RISK3 (.18.) 0.985 0.030 32.956 0.000 0.800 0.741
## SOC =~
## SOC1 1.000 0.900 0.754
## SOC2 (.20.) 0.955 0.081 11.848 0.000 0.859 0.720
## EMO =~
## EMO1 1.000 0.629 0.600
## EMO2 (.22.) 1.296 0.065 19.805 0.000 0.815 0.815
## EMO3 (.23.) 0.835 0.046 18.160 0.000 0.525 0.469
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC ~~
## JOB 0.458 0.041 11.239 0.000 0.373 0.373
## CARE 0.420 0.037 11.408 0.000 0.366 0.366
## RISK 0.226 0.027 8.310 0.000 0.283 0.283
## SOC 0.116 0.031 3.688 0.000 0.131 0.131
## EMO 0.222 0.024 9.321 0.000 0.359 0.359
## JOB ~~
## CARE 0.315 0.045 6.974 0.000 0.216 0.216
## RISK 0.304 0.035 8.659 0.000 0.299 0.299
## SOC 0.259 0.042 6.203 0.000 0.230 0.230
## EMO 0.281 0.030 9.234 0.000 0.358 0.358
## CARE ~~
## RISK 0.239 0.031 7.622 0.000 0.252 0.252
## SOC 0.176 0.037 4.757 0.000 0.168 0.168
## EMO 0.208 0.027 7.833 0.000 0.284 0.284
## RISK ~~
## SOC 0.203 0.029 6.930 0.000 0.277 0.277
## EMO 0.152 0.020 7.538 0.000 0.298 0.298
## SOC ~~
## EMO 0.176 0.025 7.129 0.000 0.312 0.312
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 (.68.) 1.820 0.020 91.960 0.000 1.820 1.549
## .DISC2 (.69.) 1.683 0.020 82.782 0.000 1.683 1.400
## .DISC3 (.70.) 1.617 0.020 80.743 0.000 1.617 1.354
## .DISC4 (.71.) 1.576 0.020 79.106 0.000 1.576 1.274
## .DISC5 (.72.) 1.739 0.020 86.665 0.000 1.739 1.388
## .DISC6 (.73.) 1.561 0.020 77.577 0.000 1.561 1.254
## .JOB1 (.74.) 2.240 0.027 82.933 0.000 2.240 1.542
## .JOB2 (.75.) 2.360 0.029 82.064 0.000 2.360 1.526
## .JOB3 (.76.) 2.025 0.024 82.761 0.000 2.025 1.500
## .JOB4 (.77.) 1.982 0.024 83.274 0.000 1.982 1.492
## .JOB5 (.78.) 5.589 0.116 48.024 0.000 5.589 0.933
## .CARE1 (.79.) 1.402 0.019 75.098 0.000 1.402 1.148
## .CARE2 (.80.) 1.406 0.019 75.177 0.000 1.406 1.159
## .CARE3 (.81.) 1.413 0.020 72.052 0.000 1.413 1.130
## .CARE4 (.82.) 2.964 0.113 26.341 0.000 2.964 0.443
## .RISK1 (.83.) 2.620 0.020 132.210 0.000 2.620 2.603
## .RISK2 (.84.) 2.558 0.022 113.923 0.000 2.558 2.278
## .RISK3 (.85.) 2.832 0.022 130.981 0.000 2.832 2.624
## .SOC1 (.86.) 3.309 0.024 135.377 0.000 3.309 2.774
## .SOC2 (.87.) 2.907 0.025 114.444 0.000 2.907 2.438
## .EMO1 (.88.) 2.840 0.020 139.446 0.000 2.840 2.709
## .EMO2 (.89.) 2.392 0.019 126.797 0.000 2.392 2.391
## .EMO3 (.90.) 2.615 0.023 115.021 0.000 2.615 2.336
## DISC 0.000 0.000 0.000
## JOB 0.000 0.000 0.000
## CARE 0.000 0.000 0.000
## RISK 0.000 0.000 0.000
## SOC 0.000 0.000 0.000
## EMO 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 0.416 0.020 21.003 0.000 0.416 0.301
## .DISC2 0.456 0.021 21.255 0.000 0.456 0.315
## .DISC3 0.429 0.020 20.993 0.000 0.429 0.301
## .DISC4 0.436 0.021 20.700 0.000 0.436 0.285
## .DISC5 0.320 0.017 18.380 0.000 0.320 0.204
## .DISC6 0.676 0.030 22.739 0.000 0.676 0.436
## .JOB1 0.546 0.030 18.365 0.000 0.546 0.259
## .JOB2 0.692 0.036 19.303 0.000 0.692 0.289
## .JOB3 0.542 0.028 19.552 0.000 0.542 0.298
## .JOB4 0.536 0.027 19.710 0.000 0.536 0.303
## .JOB5 23.766 1.002 23.721 0.000 23.766 0.662
## .CARE1 0.131 0.008 15.447 0.000 0.131 0.088
## .CARE2 0.097 0.008 12.534 0.000 0.097 0.066
## .CARE3 0.212 0.011 19.449 0.000 0.212 0.136
## .CARE4 34.305 1.393 24.619 0.000 34.305 0.766
## .RISK1 0.353 0.024 14.807 0.000 0.353 0.349
## .RISK2 0.554 0.031 17.991 0.000 0.554 0.440
## .RISK3 0.525 0.029 18.322 0.000 0.525 0.451
## .SOC1 0.614 0.073 8.412 0.000 0.614 0.431
## .SOC2 0.684 0.068 9.998 0.000 0.684 0.481
## .EMO1 0.704 0.035 19.882 0.000 0.704 0.640
## .EMO2 0.337 0.036 9.343 0.000 0.337 0.336
## .EMO3 0.977 0.043 22.640 0.000 0.977 0.780
## DISC 0.965 0.050 19.484 0.000 1.000 1.000
## JOB 1.565 0.075 20.779 0.000 1.000 1.000
## CARE 1.361 0.058 23.268 0.000 1.000 1.000
## RISK 0.660 0.039 17.027 0.000 1.000 1.000
## SOC 0.809 0.083 9.762 0.000 1.000 1.000
## EMO 0.395 0.034 11.581 0.000 1.000 1.000
##
##
## Group 2 [Older]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC =~
## DISC1 1.000 0.670 0.773
## DISC2 (.p2.) 1.012 0.022 45.150 0.000 0.678 0.759
## DISC3 (.p3.) 1.017 0.022 46.181 0.000 0.681 0.779
## DISC4 (.p4.) 1.065 0.022 48.617 0.000 0.713 0.841
## DISC5 (.p5.) 1.137 0.022 52.687 0.000 0.762 0.894
## DISC6 (.p6.) 0.952 0.023 41.163 0.000 0.637 0.744
## JOB =~
## JOB1 1.000 1.139 0.900
## JOB2 (.p8.) 1.042 0.018 59.243 0.000 1.187 0.882
## JOB3 (.p9.) 0.904 0.015 61.837 0.000 1.030 0.909
## JOB4 (.10.) 0.887 0.014 62.896 0.000 1.010 0.919
## JOB5 (.11.) 2.784 0.089 31.205 0.000 3.170 0.568
## CARE =~
## CARE1 1.000 0.742 0.960
## CARE2 (.13.) 1.005 0.009 110.311 0.000 0.746 0.959
## CARE3 (.14.) 0.996 0.011 89.534 0.000 0.740 0.898
## CARE4 (.15.) 2.779 0.113 24.610 0.000 2.063 0.424
## RISK =~
## RISK1 1.000 0.807 0.829
## RISK2 (.17.) 1.035 0.031 33.158 0.000 0.835 0.748
## RISK3 (.18.) 0.985 0.030 32.956 0.000 0.794 0.738
## SOC =~
## SOC1 1.000 1.058 0.841
## SOC2 (.20.) 0.955 0.081 11.848 0.000 1.010 0.742
## EMO =~
## EMO1 1.000 0.605 0.618
## EMO2 (.22.) 1.296 0.065 19.805 0.000 0.784 0.881
## EMO3 (.23.) 0.835 0.046 18.160 0.000 0.505 0.444
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DISC ~~
## JOB 0.220 0.025 8.957 0.000 0.289 0.289
## CARE 0.117 0.016 7.479 0.000 0.235 0.235
## RISK 0.042 0.018 2.363 0.018 0.078 0.078
## SOC -0.072 0.024 -2.992 0.003 -0.102 -0.102
## EMO 0.102 0.014 7.057 0.000 0.253 0.253
## JOB ~~
## CARE 0.128 0.026 4.981 0.000 0.152 0.152
## RISK 0.141 0.030 4.675 0.000 0.154 0.154
## SOC -0.059 0.040 -1.475 0.140 -0.049 -0.049
## EMO 0.126 0.023 5.365 0.000 0.183 0.183
## CARE ~~
## RISK 0.033 0.019 1.719 0.086 0.056 0.056
## SOC 0.002 0.026 0.077 0.938 0.003 0.003
## EMO 0.055 0.015 3.689 0.000 0.122 0.122
## RISK ~~
## SOC 0.146 0.031 4.680 0.000 0.171 0.171
## EMO 0.096 0.018 5.374 0.000 0.197 0.197
## SOC ~~
## EMO 0.070 0.023 3.008 0.003 0.110 0.110
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 (.68.) 1.820 0.020 91.960 0.000 1.820 2.100
## .DISC2 (.69.) 1.683 0.020 82.782 0.000 1.683 1.885
## .DISC3 (.70.) 1.617 0.020 80.743 0.000 1.617 1.850
## .DISC4 (.71.) 1.576 0.020 79.106 0.000 1.576 1.859
## .DISC5 (.72.) 1.739 0.020 86.665 0.000 1.739 2.040
## .DISC6 (.73.) 1.561 0.020 77.577 0.000 1.561 1.823
## .JOB1 (.74.) 2.240 0.027 82.933 0.000 2.240 1.771
## .JOB2 (.75.) 2.360 0.029 82.064 0.000 2.360 1.754
## .JOB3 (.76.) 2.025 0.024 82.761 0.000 2.025 1.787
## .JOB4 (.77.) 1.982 0.024 83.274 0.000 1.982 1.804
## .JOB5 (.78.) 5.589 0.116 48.024 0.000 5.589 1.001
## .CARE1 (.79.) 1.402 0.019 75.098 0.000 1.402 1.812
## .CARE2 (.80.) 1.406 0.019 75.177 0.000 1.406 1.807
## .CARE3 (.81.) 1.413 0.020 72.052 0.000 1.413 1.715
## .CARE4 (.82.) 2.964 0.113 26.341 0.000 2.964 0.609
## .RISK1 (.83.) 2.620 0.020 132.210 0.000 2.620 2.695
## .RISK2 (.84.) 2.558 0.022 113.923 0.000 2.558 2.294
## .RISK3 (.85.) 2.832 0.022 130.981 0.000 2.832 2.633
## .SOC1 (.86.) 3.309 0.024 135.377 0.000 3.309 2.629
## .SOC2 (.87.) 2.907 0.025 114.444 0.000 2.907 2.135
## .EMO1 (.88.) 2.840 0.020 139.446 0.000 2.840 2.901
## .EMO2 (.89.) 2.392 0.019 126.797 0.000 2.392 2.688
## .EMO3 (.90.) 2.615 0.023 115.021 0.000 2.615 2.299
## DISC 0.000 0.000 0.000
## JOB 0.000 0.000 0.000
## CARE 0.000 0.000 0.000
## RISK 0.000 0.000 0.000
## SOC 0.000 0.000 0.000
## EMO 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DISC1 0.303 0.014 21.688 0.000 0.303 0.403
## .DISC2 0.338 0.015 21.927 0.000 0.338 0.424
## .DISC3 0.300 0.014 21.554 0.000 0.300 0.393
## .DISC4 0.210 0.011 19.752 0.000 0.210 0.292
## .DISC5 0.146 0.009 16.715 0.000 0.146 0.202
## .DISC6 0.327 0.015 22.148 0.000 0.327 0.446
## .JOB1 0.303 0.016 18.781 0.000 0.303 0.189
## .JOB2 0.403 0.020 19.894 0.000 0.403 0.223
## .JOB3 0.224 0.012 18.139 0.000 0.224 0.174
## .JOB4 0.188 0.011 17.188 0.000 0.188 0.156
## .JOB5 21.090 0.880 23.968 0.000 21.090 0.677
## .CARE1 0.047 0.004 12.502 0.000 0.047 0.079
## .CARE2 0.048 0.004 12.608 0.000 0.048 0.080
## .CARE3 0.132 0.006 20.745 0.000 0.132 0.194
## .CARE4 19.465 0.798 24.395 0.000 19.465 0.821
## .RISK1 0.295 0.022 13.148 0.000 0.295 0.312
## .RISK2 0.547 0.031 17.869 0.000 0.547 0.440
## .RISK3 0.526 0.029 18.316 0.000 0.526 0.455
## .SOC1 0.464 0.100 4.647 0.000 0.464 0.293
## .SOC2 0.834 0.096 8.721 0.000 0.834 0.450
## .EMO1 0.592 0.031 19.111 0.000 0.592 0.618
## .EMO2 0.177 0.032 5.495 0.000 0.177 0.224
## .EMO3 1.038 0.045 22.989 0.000 1.038 0.803
## DISC 0.449 0.024 18.908 0.000 1.000 1.000
## JOB 1.297 0.061 21.087 0.000 1.000 1.000
## CARE 0.551 0.024 23.112 0.000 1.000 1.000
## RISK 0.650 0.038 17.260 0.000 1.000 1.000
## SOC 1.119 0.111 10.078 0.000 1.000 1.000
## EMO 0.366 0.031 11.949 0.000 1.000 1.000Notes on interpretation: If p-value > 0.05, the constrained model is equivalent to the unconstrained/free model (the coefficients and intercepts do not vary by group). Thus, it would be fair to analyse the pooled data in a single global model.
If p< 0.05, the free model is significantly different from the constrained model, implying differences in coefficients/intercepts between the two groups.
*Difference between config and metric
anova(config, metric)## Chi-Squared Difference Test
##
## Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
## config 430 151371 152345 1658.5
## metric 447 151597 152473 1919.1 260.58 17 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1*Difference between metric and scalar
anova(metric, scalar)## Chi-Squared Difference Test
##
## Df AIC BIC Chisq Chisq diff Df diff Pr(>Chisq)
## metric 447 151597 152473 1919.1
## scalar 470 152422 153164 2789.5 870.42 23 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1