χ2/df >3,but CFI,TLI,SRMR are good,how to understand it?how to further develop the model?
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Stan Silver
Jul 2, 2020, 10:59:38 AM7/2/20
to lavaan
SRMRÂ 0.037
CFIÂ Â Â Â Â 0.996
TLIÂ Â Â Â Â Â 0.996
Above index looks good,but χ2/df=37711.897/1607,is there any further instruction to develop the model?
>summary(fitres,fit.measures=TRUE,standardized=TRUE)
lavaan 0.6-6 ended normally after 126 iterations
 Estimator                    DWLS
 Optimization method              NLMINB
 Number of free parameters             340
                          Â
 Number of observations              8251
                          Â
Model Test User Model:
                        Standard    Robust
 Test Statistic                37711.897  58244.715
 Degrees of freedom                1607     1607
 P-value (Chi-square)               0.000    0.000
 Scaling correction factor                  0.654
 Shift parameter                      572.806
    simple second-order correction               Â
Model Test Baseline Model:
 Test statistic              8885432.371  907084.853
 Degrees of freedom                1711     1711
 P-value                     0.000    0.000
 Scaling correction factor                  9.812
User Model versus Baseline Model:
 Comparative Fit Index (CFI)           0.996    0.937
 Tucker-Lewis Index (TLI)            0.996    0.933
                                Â
 Robust Comparative Fit Index (CFI)               NA
 Robust Tucker-Lewis Index (TLI)                NA
Root Mean Square Error of Approximation:
 RMSEA                      0.052    0.065
 90 Percent confidence interval - lower     0.052    0.065
 90 Percent confidence interval - upper     0.053    0.066
 P-value RMSEA <= 0.05              0.000    0.000
                                Â
 Robust RMSEA                          NA
 90 Percent confidence interval - lower             NA
 90 Percent confidence interval - upper             NA
Standardized Root Mean Square Residual:
 SRMR                      0.037    0.037
Parameter Estimates:
 Standard errors              Robust.sem
 Information                 Expected
 Information saturated (h1) model     Unstructured
Latent Variables:
          Estimate  Std.Err  z-value  P(>|z|)  Std.lv  Std.all
 f1 =~                                Â
  q10        1.000                0.497   0.497
  q12        1.153   0.024  48.552   0.000   0.573   0.573
  q22        1.804   0.034  53.618   0.000   0.896   0.896
  q23        1.008   0.022  45.311   0.000   0.501   0.501
 f2 =~                                Â
  q11        1.000                0.708   0.708
  q20        1.035   0.011  90.232   0.000   0.733   0.733
  q24        1.164   0.011  104.810   0.000   0.825   0.825
  q26        1.201   0.011  109.928   0.000   0.851   0.851
  q47        1.136   0.011  107.169   0.000   0.805   0.805
  q49        1.170   0.011  105.521   0.000   0.829   0.829
 f3 =~                                Â
  q19        1.000                0.824   0.824
  q21        0.872   0.008  115.178   0.000   0.719   0.719
  q25        0.861   0.008  106.151   0.000   0.710   0.710
  q52        1.017   0.008  135.061   0.000   0.838   0.838
  q50        1.136   0.007  172.257   0.000   0.937   0.937
  q58        1.023   0.007  145.138   0.000   0.843   0.843
 f4 =~                                Â
  q04        1.000                0.853   0.853
  q17        0.968   0.005  179.736   0.000   0.826   0.826
  q18        1.016   0.005  218.253   0.000   0.866   0.866
  q45        0.998   0.005  187.035   0.000   0.851   0.851
  q51        0.625   0.010  64.943   0.000   0.533   0.533
  q59        0.751   0.009  79.700   0.000   0.640   0.640
 f5 =~                                Â
  q02        1.000                0.852   0.852
  q05        1.051   0.005  214.391   0.000   0.895   0.895
  q13        0.852   0.007  122.920   0.000   0.725   0.725
  q14        0.995   0.006  172.507   0.000   0.848   0.848
  q16        0.925   0.006  152.775   0.000   0.788   0.788
  q44        1.033   0.005  194.963   0.000   0.880   0.880
  q57        0.966   0.006  154.096   0.000   0.823   0.823
 f6 =~                                Â
  q06        1.000                0.793   0.793
  q15        1.092   0.006  174.815   0.000   0.865   0.865
  q34        1.062   0.006  164.017   0.000   0.842   0.842
  q43        1.169   0.007  171.993   0.000   0.927   0.927
  q46        1.154   0.007  175.326   0.000   0.915   0.915
  q56        1.124   0.007  166.276   0.000   0.891   0.891
 f7 =~                                Â
  q31        1.000                0.844   0.844
  q33        0.940   0.008  116.628   0.000   0.794   0.794
  q36        0.805   0.009  94.409   0.000   0.680   0.680
  q38        0.964   0.008  128.267   0.000   0.814   0.814
  q40        1.037   0.008  138.088   0.000   0.876   0.876
  q55        0.987   0.007  135.795   0.000   0.834   0.834
  q48        0.932   0.008  118.577   0.000   0.787   0.787
 f8 =~                                Â
  q01        1.000                0.716   0.716
  q08        1.124   0.011  104.085   0.000   0.805   0.805
  q09        1.040   0.011  92.741   0.000   0.745   0.745
  q29        1.073   0.011  96.398   0.000   0.768   0.768
  q39        0.967   0.012  82.528   0.000   0.693   0.693
  q41        1.071   0.011  97.444   0.000   0.767   0.767
 f9 =~                                Â
  q07        1.000                0.802   0.802
  q27        0.998   0.007  150.485   0.000   0.800   0.800
  q32        1.061   0.008  126.345   0.000   0.851   0.851
  q35        0.938   0.009  104.624   0.000   0.752   0.752
  q53        1.029   0.009  118.599   0.000   0.825   0.825
 f10 =~                                Â
  q28        1.000                0.706   0.706
  q30        1.118   0.013  83.485   0.000   0.789   0.789
  q37        1.053   0.013  81.785   0.000   0.743   0.743
  q42        1.078   0.014  76.158   0.000   0.761   0.761
  q54        0.994   0.012  84.200   0.000   0.701   0.701
  q60        0.947   0.012  76.553   0.000   0.668   0.668
Covariances:
          Estimate  Std.Err  z-value  P(>|z|)  Std.lv  Std.all
 f1 ~~                                Â
  f2         0.311   0.007  43.078   0.000   0.885   0.885
  f3         0.329   0.007  45.268   0.000   0.803   0.803
  f4         0.379   0.008  48.627   0.000   0.896   0.896
  f5         0.377   0.008  48.774   0.000   0.891   0.891
  f6         0.359   0.008  46.967   0.000   0.911   0.911
  f7         0.325   0.007  44.460   0.000   0.774   0.774
  f8         0.301   0.007  43.106   0.000   0.845   0.845
  f9         0.332   0.007  45.473   0.000   0.834   0.834
  f10        0.273   0.007  39.996   0.000   0.780   0.780
 f2 ~~                                Â
  f3         0.494   0.006  76.951   0.000   0.847   0.847
  f4         0.590   0.006  92.543   0.000   0.977   0.977
  f5         0.531   0.006  82.561   0.000   0.881   0.881
  f6         0.493   0.006  77.231   0.000   0.879   0.879
  f7         0.451   0.006  69.898   0.000   0.753   0.753
  f8         0.461   0.007  68.936   0.000   0.909   0.909
  f9         0.483   0.007  73.765   0.000   0.850   0.850
  f10        0.439   0.007  65.349   0.000   0.878   0.878
 f3 ~~                                Â
  f4         0.595   0.006  98.592   0.000   0.847   0.847
  f5         0.616   0.006  102.654   0.000   0.877   0.877
  f6         0.567   0.006  93.093   0.000   0.868   0.868
  f7         0.522   0.007  79.945   0.000   0.750   0.750
  f8         0.470   0.007  71.508   0.000   0.796   0.796
  f9         0.545   0.006  84.314   0.000   0.825   0.825
  f10        0.457   0.007  66.561   0.000   0.786   0.786
 f4 ~~                                Â
  f5         0.682   0.005  129.534   0.000   0.939   0.939
  f6         0.620   0.006  108.880   0.000   0.918   0.918
  f7         0.565   0.006  91.525   0.000   0.785   0.785
  f8         0.554   0.007  84.918   0.000   0.908   0.908
  f9         0.584   0.006  94.967   0.000   0.854   0.854
  f10        0.522   0.007  77.622   0.000   0.868   0.868
 f5 ~~                                Â
  f6         0.659   0.006  116.592   0.000   0.975   0.975
  f7         0.594   0.006  98.611   0.000   0.826   0.826
  f8         0.547   0.006  84.487   0.000   0.898   0.898
  f9         0.598   0.006  95.811   0.000   0.875   0.875
  f10        0.470   0.007  69.416   0.000   0.782   0.782
 f6 ~~                                Â
  f7         0.558   0.006  90.545   0.000   0.834   0.834
  f8         0.494   0.006  76.305   0.000   0.870   0.870
  f9         0.546   0.006  87.578   0.000   0.859   0.859
  f10        0.435   0.007  64.413   0.000   0.777   0.777
 f7 ~~                                Â
  f8         0.506   0.006  78.684   0.000   0.837   0.837
  f9         0.544   0.006  85.746   0.000   0.803   0.803
  f10        0.460   0.007  67.107   0.000   0.773   0.773
 f8 ~~                                Â
  f9         0.498   0.007  76.223   0.000   0.868   0.868
  f10        0.442   0.007  64.892   0.000   0.875   0.875
 f9 ~~                                Â
  f10        0.467   0.007  66.817   0.000   0.826   0.826
Intercepts:
          Estimate  Std.Err  z-value  P(>|z|)  Std.lv  Std.all
  .q10        0.000                0.000   0.000
  .q12        0.000                0.000   0.000
  .q22        0.000                0.000   0.000
  .q23        0.000                0.000   0.000
  .q11        0.000                0.000   0.000
  .q20        0.000                0.000   0.000
  .q24        0.000                0.000   0.000
  .q26        0.000                0.000   0.000
  .q47        0.000                0.000   0.000
  .q49        0.000                0.000   0.000
  .q19        0.000                0.000   0.000
  .q21        0.000                0.000   0.000
  .q25        0.000                0.000   0.000
  .q52        0.000                0.000   0.000
  .q50        0.000                0.000   0.000
  .q58        0.000                0.000   0.000
  .q04        0.000                0.000   0.000
  .q17        0.000                0.000   0.000
  .q18        0.000                0.000   0.000
  .q45        0.000                0.000   0.000
  .q51        0.000                0.000   0.000
  .q59        0.000                0.000   0.000
  .q02        0.000                0.000   0.000
  .q05        0.000                0.000   0.000
  .q13        0.000                0.000   0.000
  .q14        0.000                0.000   0.000
  .q16        0.000                0.000   0.000
  .q44        0.000                0.000   0.000
  .q57        0.000                0.000   0.000
  .q06        0.000                0.000   0.000
  .q15        0.000                0.000   0.000
  .q34        0.000                0.000   0.000
  .q43        0.000                0.000   0.000
  .q46        0.000                0.000   0.000
  .q56        0.000                0.000   0.000
  .q31        0.000                0.000   0.000
  .q33        0.000                0.000   0.000
  .q36        0.000                0.000   0.000
  .q38        0.000                0.000   0.000
  .q40        0.000                0.000   0.000
  .q55        0.000                0.000   0.000
  .q48        0.000                0.000   0.000
  .q01        0.000                0.000   0.000
  .q08        0.000                0.000   0.000
  .q09        0.000                0.000   0.000
  .q29        0.000                0.000   0.000
  .q39        0.000                0.000   0.000
  .q41        0.000                0.000   0.000
  .q07        0.000                0.000   0.000
  .q27        0.000                0.000   0.000
  .q32        0.000                0.000   0.000
  .q35        0.000                0.000   0.000
  .q53        0.000                0.000   0.000
  .q28        0.000                0.000   0.000
  .q30        0.000                0.000   0.000
  .q37        0.000                0.000   0.000
  .q42        0.000                0.000   0.000
  .q54        0.000                0.000   0.000
  .q60        0.000                0.000   0.000
  f1         0.000                0.000   0.000
  f2         0.000                0.000   0.000
  f3         0.000                0.000   0.000
  f4         0.000                0.000   0.000
  f5         0.000                0.000   0.000
  f6         0.000                0.000   0.000
  f7         0.000                0.000   0.000
  f8         0.000                0.000   0.000
  f9         0.000                0.000   0.000
  f10        0.000                0.000   0.000
Thresholds:
          Estimate  Std.Err  z-value  P(>|z|)  Std.lv  Std.all
  q10|t1      -0.750   0.015  -48.999   0.000  -0.750  -0.750
  q10|t2       0.152   0.014  10.971   0.000   0.152   0.152
  q10|t3       0.952   0.016  58.282   0.000   0.952   0.952
  q10|t4       1.562   0.022  70.843   0.000   1.562   1.562
  q12|t1      -1.014   0.017  -60.658   0.000  -1.014  -1.014
  q12|t2      -0.367   0.014  -25.931   0.000  -0.367  -0.367
  q12|t3       0.269   0.014  19.231   0.000   0.269   0.269
  q12|t4       0.968   0.016  58.913   0.000   0.968   0.968
  q22|t1      -0.977   0.016  -59.274   0.000  -0.977  -0.977
  q22|t2      -0.403   0.014  -28.332   0.000  -0.403  -0.403
  q22|t3       0.180   0.014  12.950   0.000   0.180   0.180
  q22|t4       0.826   0.016  52.779   0.000   0.826   0.826
  q23|t1      -0.086   0.014  -6.241   0.000  -0.086  -0.086
  q23|t2       0.644   0.015  43.239   0.000   0.644   0.644
  q23|t3       1.202   0.018  66.364   0.000   1.202   1.202
  q23|t4       1.634   0.023  70.742   0.000   1.634   1.634
  q11|t1      -1.364   0.020  -69.434   0.000  -1.364  -1.364
  q11|t2      -0.644   0.015  -43.239   0.000  -0.644  -0.644
  q11|t3       0.374   0.014  26.411   0.000   0.374   0.374
  q11|t4       1.120   0.017  64.182   0.000   1.120   1.120
  q20|t1      -0.223   0.014  -16.026   0.000  -0.223  -0.223
  q20|t2       0.569   0.015  38.859   0.000   0.569   0.569
  q20|t3       1.232   0.018  67.075   0.000   1.232   1.232
  q20|t4       1.713   0.024  70.278   0.000   1.713   1.713
  q24|t1      -0.645   0.015  -43.302   0.000  -0.645  -0.645
  q24|t2       0.066   0.014   4.788   0.000   0.066   0.066
  q24|t3       0.713   0.015  47.038   0.000   0.713   0.713
  q24|t4       1.222   0.018  66.857   0.000   1.222   1.222
  q26|t1      -0.710   0.015  -46.891   0.000  -0.710  -0.710
  q26|t2      -0.071   0.014  -5.162   0.000  -0.071  -0.071
  q26|t3       0.445   0.014  31.075   0.000   0.445   0.445
  q26|t4       0.985   0.017  59.576   0.000   0.985   0.985
  q47|t1      -0.766   0.015  -49.807   0.000  -0.766  -0.766
  q47|t2      -0.015   0.014  -1.068   0.286  -0.015  -0.015
  q47|t3       0.813   0.016  52.128   0.000   0.813   0.813
  q47|t4       1.377   0.020  69.608   0.000   1.377   1.377
  q49|t1      -0.498   0.014  -34.481   0.000  -0.498  -0.498
  q49|t2       0.258   0.014  18.441   0.000   0.258   0.258
  q49|t3       0.889   0.016  55.668   0.000   0.889   0.889
  q49|t4       1.380   0.020  69.647   0.000   1.380   1.380
  q19|t1      -0.908   0.016  -56.456   0.000  -0.908  -0.908
  q19|t2      -0.166   0.014  -11.939   0.000  -0.166  -0.166
  q19|t3       0.489   0.014  33.940   0.000   0.489   0.489
  q19|t4       1.036   0.017  61.446   0.000   1.036   1.036
  q21|t1      -0.166   0.014  -11.961   0.000  -0.166  -0.166
  q21|t2       0.594   0.015  40.360   0.000   0.594   0.594
  q21|t3       1.179   0.018  65.793   0.000   1.179   1.179
  q21|t4       1.590   0.022  70.841   0.000   1.590   1.590
  q25|t1      -0.773   0.015  -50.158   0.000  -0.773  -0.773
  q25|t2       0.109   0.014   7.914   0.000   0.109   0.109
  q25|t3       0.821   0.016  52.535   0.000   0.821   0.821
  q25|t4       1.428   0.020  70.170   0.000   1.428   1.428
  q52|t1      -0.304   0.014  -21.686   0.000  -0.304  -0.304
  q52|t2       0.282   0.014  20.130   0.000   0.282   0.282
  q52|t3       0.816   0.016  52.291   0.000   0.816   0.816
  q52|t4       1.207   0.018  66.485   0.000   1.207   1.207
  q50|t1      -0.910   0.016  -56.574   0.000  -0.910  -0.910
  q50|t2      -0.262   0.014  -18.726   0.000  -0.262  -0.262
  q50|t3       0.277   0.014  19.779   0.000   0.277   0.277
  q50|t4       0.859   0.016  54.292   0.000   0.859   0.859
  q58|t1      -0.295   0.014  -21.051   0.000  -0.295  -0.295
  q58|t2       0.313   0.014  22.300   0.000   0.313   0.313
  q58|t3       0.854   0.016  54.092   0.000   0.854   0.854
  q58|t4       1.297   0.019  68.380   0.000   1.297   1.297
  q04|t1      -0.718   0.015  -47.331   0.000  -0.718  -0.718
  q04|t2      -0.108   0.014  -7.826   0.000  -0.108  -0.108
  q04|t3       0.572   0.015  39.031   0.000   0.572   0.572
  q04|t4       1.162   0.018  65.349   0.000   1.162   1.162
  q17|t1      -1.018   0.017  -60.805   0.000  -1.018  -1.018
  q17|t2      -0.459   0.014  -32.031   0.000  -0.459  -0.459
  q17|t3       0.089   0.014   6.439   0.000   0.089   0.089
  q17|t4       0.686   0.015  45.587   0.000   0.686   0.686
  q18|t1      -0.752   0.015  -49.102   0.000  -0.752  -0.752
  q18|t2      -0.099   0.014  -7.143   0.000  -0.099  -0.099
  q18|t3       0.478   0.014  33.246   0.000   0.478   0.478
  q18|t4       1.031   0.017  61.264   0.000   1.031   1.031
  q45|t1      -0.770   0.015  -50.014   0.000  -0.770  -0.770
  q45|t2      -0.255   0.014  -18.266   0.000  -0.255  -0.255
  q45|t3       0.243   0.014  17.454   0.000   0.243   0.243
  q45|t4       0.786   0.015  50.817   0.000   0.786   0.786
  q51|t1      -0.457   0.014  -31.901   0.000  -0.457  -0.457
  q51|t2       0.200   0.014  14.357   0.000   0.200   0.200
  q51|t3       0.797   0.016  51.372   0.000   0.797   0.797
  q51|t4       1.254   0.019  67.557   0.000   1.254   1.254
  q59|t1       0.136   0.014   9.806   0.000   0.136   0.136
  q59|t2       0.803   0.016  51.638   0.000   0.803   0.803
  q59|t3       1.367   0.020  69.476   0.000   1.367   1.367
  q59|t4       1.819   0.026  69.091   0.000   1.819   1.819
  q02|t1      -1.262   0.019  -67.708   0.000  -1.262  -1.262
  q02|t2      -0.617   0.015  -41.685   0.000  -0.617  -0.617
  q02|t3       0.013   0.014   0.914   0.361   0.013   0.013
  q02|t4       0.727   0.015  47.791   0.000   0.727   0.727
  q05|t1      -0.911   0.016  -56.594   0.000  -0.911  -0.911
  q05|t2      -0.327   0.014  -23.219   0.000  -0.327  -0.327
  q05|t3       0.298   0.014  21.226   0.000   0.298   0.298
  q05|t4       0.994   0.017  59.914   0.000   0.994   0.994
  q13|t1      -0.816   0.016  -52.311   0.000  -0.816  -0.816
  q13|t2      -0.124   0.014  -8.970   0.000  -0.124  -0.124
  q13|t3       0.443   0.014  30.944   0.000   0.443   0.443
  q13|t4       0.962   0.016  58.704   0.000   0.962   0.962
  q14|t1      -0.539   0.015  -37.008   0.000  -0.539  -0.539
  q14|t2      -0.038   0.014  -2.719   0.007  -0.038  -0.038
  q14|t3       0.572   0.015  39.031   0.000   0.572   0.572
  q14|t4       1.057   0.017  62.185   0.000   1.057   1.057
  q16|t1      -0.916   0.016  -56.809   0.000  -0.916  -0.916
  q16|t2      -0.221   0.014  -15.873   0.000  -0.221  -0.221
  q16|t3       0.519   0.014  35.778   0.000   0.519   0.519
  q16|t4       1.119   0.017  64.148   0.000   1.119   1.119
  q44|t1      -0.931   0.016  -57.452   0.000  -0.931  -0.931
  q44|t2      -0.239   0.014  -17.146   0.000  -0.239  -0.239
  q44|t3       0.387   0.014  27.306   0.000   0.387   0.387
  q44|t4       0.974   0.016  59.160   0.000   0.974   0.974
  q57|t1      -0.165   0.014  -11.895   0.000  -0.165  -0.165
  q57|t2       0.259   0.014  18.551   0.000   0.259   0.259
  q57|t3       0.818   0.016  52.372   0.000   0.818   0.818
  q57|t4       1.195   0.018  66.212   0.000   1.195   1.195
  q06|t1      -1.135   0.018  -64.616   0.000  -1.135  -1.135
  q06|t2      -0.413   0.014  -28.985   0.000  -0.413  -0.413
  q06|t3       0.313   0.014  22.300   0.000   0.313   0.313
  q06|t4       1.022   0.017  60.952   0.000   1.022   1.022
  q15|t1      -0.688   0.015  -45.693   0.000  -0.688  -0.688
  q15|t2       0.059   0.014   4.282   0.000   0.059   0.059
  q15|t3       0.725   0.015  47.686   0.000   0.725   0.725
  q15|t4       1.255   0.019  67.570   0.000   1.255   1.255
  q34|t1      -0.551   0.015  -37.762   0.000  -0.551  -0.551
  q34|t2       0.013   0.014   0.936   0.349   0.013   0.013
  q34|t3       0.587   0.015  39.910   0.000   0.587   0.587
  q34|t4       1.034   0.017  61.373   0.000   1.034   1.034
  q43|t1      -1.028   0.017  -61.172   0.000  -1.028  -1.028
  q43|t2      -0.453   0.014  -31.618   0.000  -0.453  -0.453
  q43|t3       0.139   0.014  10.004   0.000   0.139   0.139
  q43|t4       0.756   0.015  49.310   0.000   0.756   0.756
  q46|t1      -0.838   0.016  -53.346   0.000  -0.838  -0.838
  q46|t2      -0.210   0.014  -15.104   0.000  -0.210  -0.210
  q46|t3       0.377   0.014  26.651   0.000   0.377   0.377
  q46|t4       0.939   0.016  57.762   0.000   0.939   0.939
  q56|t1      -0.912   0.016  -56.653   0.000  -0.912  -0.912
  q56|t2      -0.366   0.014  -25.865   0.000  -0.366  -0.366
  q56|t3       0.128   0.014   9.234   0.000   0.128   0.128
  q56|t4       0.672   0.015  44.828   0.000   0.672   0.672
  q31|t1      -1.005   0.017  -60.324   0.000  -1.005  -1.005
  q31|t2      -0.396   0.014  -27.874   0.000  -0.396  -0.396
  q31|t3       0.342   0.014  24.247   0.000   0.342   0.342
  q31|t4       0.928   0.016  57.336   0.000   0.928   0.928
  q33|t1      -0.922   0.016  -57.083   0.000  -0.922  -0.922
  q33|t2      -0.368   0.014  -26.018   0.000  -0.368  -0.368
  q33|t3       0.204   0.014  14.643   0.000   0.204   0.204
  q33|t4       0.749   0.015  48.957   0.000   0.749   0.749
  q36|t1      -0.963   0.016  -58.723   0.000  -0.963  -0.963
  q36|t2      -0.230   0.014  -16.510   0.000  -0.230  -0.230
  q36|t3       0.398   0.014  28.004   0.000   0.398   0.398
  q36|t4       0.930   0.016  57.394   0.000   0.930   0.930
  q38|t1      -0.820   0.016  -52.494   0.000  -0.820  -0.820
  q38|t2      -0.187   0.014  -13.478   0.000  -0.187  -0.187
  q38|t3       0.474   0.014  32.964   0.000   0.474   0.474
  q38|t4       0.912   0.016  56.653   0.000   0.912   0.912
  q40|t1      -0.453   0.014  -31.597   0.000  -0.453  -0.453
  q40|t2       0.107   0.014   7.715   0.000   0.107   0.107
  q40|t3       0.721   0.015  47.477   0.000   0.721   0.721
  q40|t4       1.081   0.017  62.980   0.000   1.081   1.081
  q55|t1      -0.758   0.015  -49.434   0.000  -0.758  -0.758
  q55|t2      -0.162   0.014  -11.653   0.000  -0.162  -0.162
  q55|t3       0.437   0.014  30.596   0.000   0.437   0.437
  q55|t4       0.865   0.016  54.573   0.000   0.865   0.865
  q48|t1      -0.939   0.016  -57.782   0.000  -0.939  -0.939
  q48|t2      -0.369   0.014  -26.106   0.000  -0.369  -0.369
  q48|t3       0.153   0.014  11.059   0.000   0.153   0.153
  q48|t4       0.728   0.015  47.853   0.000   0.728   0.728
  q01|t1      -0.619   0.015  -41.834   0.000  -0.619  -0.619
  q01|t2       0.003   0.014   0.253   0.800   0.003   0.003
  q01|t3       0.682   0.015  45.398   0.000   0.682   0.682
  q01|t4       1.198   0.018  66.288   0.000   1.198   1.198
  q08|t1      -0.373   0.014  -26.368   0.000  -0.373  -0.373
  q08|t2       0.288   0.014  20.547   0.000   0.288   0.288
  q08|t3       0.901   0.016  56.161   0.000   0.901   0.901
  q08|t4       1.356   0.020  69.318   0.000   1.356   1.356
  q09|t1      -0.810   0.016  -52.006   0.000  -0.810  -0.810
  q09|t2      -0.253   0.014  -18.090   0.000  -0.253  -0.253
  q09|t3       0.414   0.014  29.073   0.000   0.414   0.414
  q09|t4       0.955   0.016  58.417   0.000   0.955   0.955
  q29|t1      -0.604   0.015  -40.959   0.000  -0.604  -0.604
  q29|t2       0.162   0.014  11.697   0.000   0.162   0.162
  q29|t3       0.999   0.017  60.119   0.000   0.999   0.999
  q29|t4       1.496   0.021  70.655   0.000   1.496   1.496
  q39|t1      -0.322   0.014  -22.891   0.000  -0.322  -0.322
  q39|t2       0.282   0.014  20.174   0.000   0.282   0.282
  q39|t3       0.893   0.016  55.846   0.000   0.893   0.893
  q39|t4       1.359   0.020  69.361   0.000   1.359   1.359
  q41|t1      -0.595   0.015  -40.402   0.000  -0.595  -0.595
  q41|t2      -0.004   0.014  -0.275   0.783  -0.004  -0.004
  q41|t3       0.613   0.015  41.450   0.000   0.613   0.613
  q41|t4       1.065   0.017  62.452   0.000   1.065   1.065
  q07|t1      -1.157   0.018  -65.221   0.000  -1.157  -1.157
  q07|t2      -0.584   0.015  -39.760   0.000  -0.584  -0.584
  q07|t3       0.058   0.014   4.194   0.000   0.058   0.058
  q07|t4       0.780   0.015  50.550   0.000   0.780   0.780
  q27|t1      -0.915   0.016  -56.790   0.000  -0.915  -0.915
  q27|t2      -0.369   0.014  -26.084   0.000  -0.369  -0.369
  q27|t3       0.239   0.014  17.124   0.000   0.239   0.239
  q27|t4       0.879   0.016  55.211   0.000   0.879   0.879
  q32|t1      -0.591   0.015  -40.188   0.000  -0.591  -0.591
  q32|t2       0.083   0.014   5.999   0.000   0.083   0.083
  q32|t3       0.687   0.015  45.630   0.000   0.687   0.687
  q32|t4       1.237   0.018  67.176   0.000   1.237   1.237
  q35|t1      -0.311   0.014  -22.146   0.000  -0.311  -0.311
  q35|t2       0.345   0.014  24.466   0.000   0.345   0.345
  q35|t3       0.947   0.016  58.090   0.000   0.947   0.947
  q35|t4       1.408   0.020  69.971   0.000   1.408   1.408
  q53|t1      -0.416   0.014  -29.181   0.000  -0.416  -0.416
  q53|t2       0.143   0.014  10.334   0.000   0.143   0.143
  q53|t3       0.694   0.015  46.009   0.000   0.694   0.694
  q53|t4       1.204   0.018  66.425   0.000   1.204   1.204
  q28|t1      -0.727   0.015  -47.812   0.000  -0.727  -0.727
  q28|t2      -0.074   0.014  -5.339   0.000  -0.074  -0.074
  q28|t3       0.558   0.015  38.192   0.000   0.558   0.558
  q28|t4       1.046   0.017  61.808   0.000   1.046   1.046
  q30|t1      -0.244   0.014  -17.520   0.000  -0.244  -0.244
  q30|t2       0.475   0.014  33.029   0.000   0.475   0.475
  q30|t3       1.152   0.018  65.091   0.000   1.152   1.152
  q30|t4       1.578   0.022  70.848   0.000   1.578   1.578
  q37|t1      -0.005   0.014  -0.363   0.716  -0.005  -0.005
  q37|t2       0.661   0.015  44.235   0.000   0.661   0.661
  q37|t3       1.217   0.018  66.739   0.000   1.217   1.217
  q37|t4       1.600   0.023  70.829   0.000   1.600   1.600
  q42|t1       0.019   0.014   1.354   0.176   0.019   0.019
  q42|t2       0.593   0.015  40.274   0.000   0.593   0.593
  q42|t3       1.122   0.017  64.216   0.000   1.122   1.122
  q42|t4       1.484   0.021  70.592   0.000   1.484   1.484
  q54|t1      -0.334   0.014  -23.701   0.000  -0.334  -0.334
  q54|t2       0.395   0.014  27.830   0.000   0.395   0.395
  q54|t3       0.968   0.016  58.932   0.000   0.968   0.968
  q54|t4       1.404   0.020  69.928   0.000   1.404   1.404
  q60|t1      -0.541   0.015  -37.159   0.000  -0.541  -0.541
  q60|t2       0.118   0.014   8.530   0.000   0.118   0.118
  q60|t3       0.829   0.016  52.901   0.000   0.829   0.829
  q60|t4       1.359   0.020  69.361   0.000   1.359   1.359
Variances:
          Estimate  Std.Err  z-value  P(>|z|)  Std.lv  Std.all
  .q10        0.753                0.753   0.753
  .q12        0.672                0.672   0.672
  .q22        0.198                0.198   0.198
  .q23        0.749                0.749   0.749
  .q11        0.498                0.498   0.498
  .q20        0.463                0.463   0.463
  .q24        0.320                0.320   0.320
  .q26        0.276                0.276   0.276
  .q47        0.352                0.352   0.352
  .q49        0.313                0.313   0.313
  .q19        0.321                0.321   0.321
  .q21        0.483                0.483   0.483
  .q25        0.496                0.496   0.496
  .q52        0.298                0.298   0.298
  .q50        0.123                0.123   0.123
  .q58        0.289                0.289   0.289
  .q04        0.273                0.273   0.273
  .q17        0.319                0.319   0.319
  .q18        0.250                0.250   0.250
  .q45        0.276                0.276   0.276
  .q51        0.716                0.716   0.716
  .q59        0.590                0.590   0.590
  .q02        0.275                0.275   0.275
  .q05        0.199                0.199   0.199
  .q13        0.474                0.474   0.474
  .q14        0.281                0.281   0.281
  .q16        0.380                0.380   0.380
  .q44        0.226                0.226   0.226
  .q57        0.323                0.323   0.323
  .q06        0.371                0.371   0.371
  .q15        0.251                0.251   0.251
  .q34        0.292                0.292   0.292
  .q43        0.141                0.141   0.141
  .q46        0.162                0.162   0.162
  .q56        0.206                0.206   0.206
  .q31        0.287                0.287   0.287
  .q33        0.370                0.370   0.370
  .q36        0.538                0.538   0.538
  .q38        0.338                0.338   0.338
  .q40        0.233                0.233   0.233
  .q55        0.305                0.305   0.305
  .q48        0.381                0.381   0.381
  .q01        0.487                0.487   0.487
  .q08        0.352                0.352   0.352
  .q09        0.445                0.445   0.445
  .q29        0.410                0.410   0.410
  .q39        0.520                0.520   0.520
  .q41        0.412                0.412   0.412
  .q07        0.357                0.357   0.357
  .q27        0.360                0.360   0.360
  .q32        0.277                0.277   0.277
  .q35        0.434                0.434   0.434
  .q53        0.319                0.319   0.319
  .q28        0.502                0.502   0.502
  .q30        0.378                0.378   0.378
  .q37        0.448                0.448   0.448
  .q42        0.421                0.421   0.421
  .q54        0.508                0.508   0.508
  .q60        0.554                0.554   0.554
  f1         0.247   0.009  27.957   0.000   1.000   1.000
  f2         0.502   0.009  56.717   0.000   1.000   1.000
  f3         0.679   0.007  93.757   0.000   1.000   1.000
  f4         0.727   0.006  119.899   0.000   1.000   1.000
  f5         0.725   0.007  110.361   0.000   1.000   1.000
  f6         0.629   0.007  87.101   0.000   1.000   1.000
  f7         0.713   0.008  87.161   0.000   1.000   1.000
  f8         0.513   0.009  56.849   0.000   1.000   1.000
  f9         0.643   0.008  83.129   0.000   1.000   1.000
  f10        0.498   0.010  52.240   0.000   1.000   1.000
Scales y*:
          Estimate  Std.Err  z-value  P(>|z|)  Std.lv  Std.all
  q10        1.000                1.000   1.000
  q12        1.000                1.000   1.000
  q22        1.000                1.000   1.000
  q23        1.000                1.000   1.000
  q11        1.000                1.000   1.000
  q20        1.000                1.000   1.000
  q24        1.000                1.000   1.000
  q26        1.000                1.000   1.000
  q47        1.000                1.000   1.000
  q49        1.000                1.000   1.000
  q19        1.000                1.000   1.000
  q21        1.000                1.000   1.000
  q25        1.000                1.000   1.000
  q52        1.000                1.000   1.000
  q50        1.000                1.000   1.000
  q58        1.000                1.000   1.000
  q04        1.000                1.000   1.000
  q17        1.000                1.000   1.000
  q18        1.000                1.000   1.000
  q45        1.000                1.000   1.000
  q51        1.000                1.000   1.000
  q59        1.000                1.000   1.000
  q02        1.000                1.000   1.000
  q05        1.000                1.000   1.000
  q13        1.000                1.000   1.000
  q14        1.000                1.000   1.000
  q16        1.000                1.000   1.000
  q44        1.000                1.000   1.000
  q57        1.000                1.000   1.000
  q06        1.000                1.000   1.000
  q15        1.000                1.000   1.000
  q34        1.000                1.000   1.000
  q43        1.000                1.000   1.000
  q46        1.000                1.000   1.000
  q56        1.000                1.000   1.000
  q31        1.000                1.000   1.000
  q33        1.000                1.000   1.000
  q36        1.000                1.000   1.000
  q38        1.000                1.000   1.000
  q40        1.000                1.000   1.000
  q55        1.000                1.000   1.000
  q48        1.000                1.000   1.000
  q01        1.000                1.000   1.000
  q08        1.000                1.000   1.000
  q09        1.000                1.000   1.000
  q29        1.000                1.000   1.000
  q39        1.000                1.000   1.000
  q41        1.000                1.000   1.000
  q07        1.000                1.000   1.000
  q27        1.000                1.000   1.000
  q32        1.000                1.000   1.000
  q35        1.000                1.000   1.000
  q53        1.000                1.000   1.000
  q28        1.000                1.000   1.000
  q30        1.000                1.000   1.000
  q37        1.000                1.000   1.000
  q42        1.000                1.000   1.000
  q54        1.000                1.000   1.000
  q60        1.000                1.000   1.000
Patrick (Malone Quantitative)
Jul 2, 2020, 11:07:55 AM7/2/20
to lav...@googlegroups.com
Stan,
Don't rely on chi-squared/df. It's never been established as having a
widely usable cutoff and can be considered obsolete.
Hope that helps,
Pat
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Patrick S. Malone, Ph.D., Malone Quantitative
NEW Service Models: http://malonequantitative.com
He/Him/His
Don't rely on chi-squared/df. It's never been established as having a
widely usable cutoff and can be considered obsolete.
Hope that helps,
Pat
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Patrick S. Malone, Ph.D., Malone Quantitative
NEW Service Models: http://malonequantitative.com
He/Him/His
Brian Peña Calero
Jul 2, 2020, 11:54:09 AM7/2/20
to lavaan
Stan,
Most of the time when there are more than 3 factors in the model, χ2 / df will be higher than the classic cuts. It is not a valid measure to validate the fit of the model.
You have a 10 factor model. The fit it shows is excellent.
You have a 10 factor model. The fit it shows is excellent.
Stan Silver
Jul 2, 2020, 12:00:16 PM7/2/20
to lavaan
Thanks for your reply.
But robust CFI is only 0.937,and P-value RMSEA <= 0.05Â is 0.000,is that a problem?
Stan Silver
Jul 2, 2020, 12:00:56 PM7/2/20
to lavaan
Is that going to be a problem
...
Patrick (Malone Quantitative)
Jul 2, 2020, 12:38:38 PM7/2/20
to lav...@googlegroups.com
It's hard to get an excellent fit with such a large model, and the
p-value for RMSEA reflects the large sample size--focus on the RMSEA
point estimate in this case because the confidence interval width is
essentially zero.
Most likely the lack of fit you do have is from omitted
cross-loadings, probably small. Frankly, with 60 items, 1700 df and a
simple structure, I'd be quite pleased with what you got.
p-value for RMSEA reflects the large sample size--focus on the RMSEA
point estimate in this case because the confidence interval width is
essentially zero.
Most likely the lack of fit you do have is from omitted
cross-loadings, probably small. Frankly, with 60 items, 1700 df and a
simple structure, I'd be quite pleased with what you got.
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Stan Silver
Jul 2, 2020, 1:20:31 PM7/2/20
to lavaan
Hi Patrick,
 Allow me ask a further question about `cross-loadings` you mentioned.Â
How to set `cross-loadings` in lavaan model?
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Patrick (Malone Quantitative)
Jul 2, 2020, 1:38:06 PM7/2/20
to lav...@googlegroups.com
The direct way would be to just add an item with a suspected
cross-loading to the measurement on a second factor. If that doesn't
mean much to you, hit an SEM textbook--it's pretty fundamental.
But don't let it be a fishing expedition for cross-loadings. As Brian
and I have both said, you've got a good fit.
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cross-loading to the measurement on a second factor. If that doesn't
mean much to you, hit an SEM textbook--it's pretty fundamental.
But don't let it be a fishing expedition for cross-loadings. As Brian
and I have both said, you've got a good fit.
> To view this discussion on the web visit https://groups.google.com/d/msgid/lavaan/ded39a04-1279-404a-b811-4d2e705a5be7o%40googlegroups.com.
Paul Joseph
Jul 2, 2020, 5:24:30 PM7/2/20
to lav...@googlegroups.com
Hi Patrick my estimation below gave me negative variance in one of the variables. what those that mean? How do i interpret threshold please. the mediation result with categorical variables is attached. thank you
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Brian Peña Calero
Jul 2, 2020, 9:20:41 PM7/2/20
to lavaan
It's hard difficult you can get a p-value of RMSEA > .05. The sample size influence directly in this and X2 value (and p-value of this).
If you want really to improve your values fits, you can try some of this ideas/options:
- Try to exclude some items with loadings below of 0.5 or 0.6. Be careful don't affect the sense and kernel of construct factor.
- Get the modification indices of your cfa model with this command: `lavaan::modindices(fit, sort. = TRUE, maximum.number = 20)` . This output allow you see cross-loadings on items or suggestions of correlations between error variance.
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