[Feature Request]: please add DWLS to EFA - needs switch to lavaan

[amda-cyber]

Description

I need DWLS as an option to EFA since WLS underperforms when samples are low.

Purpose

To estimate the factors better in EFA, with ordinal data DWLS is recommended (also WLSMV is better than WLS)

Use-case

No response

Is your feature request related to a problem?

yes, the factoring methods are insufficient in EFA. Most data are ordinal. And you only have WLS as an option. Research says that DWLS or WLSMV performs better than WLS.

Is your feature request related to a JASP module?

Factor

Describe the solution you would like

Either DWLS or WLSMV as an option in Exploratory Factor Analysis

Describe alternatives that you have considered

WLSMV

Additional context

See research provided for my arguments:
Rogers, P. (2024). Best practices for your confirmatory factor analysis: A JASP and lavaan tutorial. Behavior Research Methods, 1-21.

Li, C. H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavior research methods, 48, 936-949.

[tomtomme]

@amda-cyber
Thanks for the request. Its certainly a reasonable one but may take a while until implemented.

[juliuspfadt]

@tomtomme is correct, this will take a while. From a first glance at the references, these seem to mention only CFA not EFA. You happen to know any R-packages that implement DWLS for EFA?

[brianmsm]

@juliuspfadt From lavaan you can use the WLSMV estimator by means of the efa()function:

library(lavaan)
#> This is lavaan 0.6-18
#> lavaan is FREE software! Please report any bugs.
# remotes::install_github("cddesja/hemp")
data(HSQ, package = "hemp")
tibble::tibble(HSQ)
#> # A tibble: 1,070 × 32
#>       Q1    Q2    Q3    Q4    Q5    Q6    Q7    Q8    Q9   Q10   Q11   Q12   Q13
#>    <dbl> <int> <int> <int> <int> <int> <dbl> <int> <dbl> <int> <int> <int> <int>
#>  1     4     2     3     1     4     5     2     3     2     3     3     1     5
#>  2     4     3     2     2     4     4     2     3     2     3     4     3     3
#>  3     3     4     3     3     4     4     3     1     4     4     3     2     4
#>  4     3     3     3     4     3     5     2     3    NA     4     2     4     4
#>  5     5     4     2     2     3     5     2     1     2     4     2     2     5
#>  6     3     3     3     2     3     3     2     2     4     1     3     3     4
#>  7     2     1     2     4     2     3     3     3     2     4     4     1     2
#>  8     4     4     4     1     5     5     2     3     4     4     3     3     5
#>  9     4     2     1     1     3     4     3     1     3     3     2     2     5
#> 10     2     2     4     1     3     5     2     2     3     1     5     3     1
#> # ℹ 1,060 more rows
#> # ℹ 19 more variables: Q14 <int>, Q15 <dbl>, Q16 <dbl>, Q17 <dbl>, Q18 <int>,
#> #   Q19 <int>, Q20 <int>, Q21 <int>, Q22 <dbl>, Q23 <dbl>, Q24 <int>,
#> #   Q25 <dbl>, Q26 <int>, Q27 <int>, Q28 <int>, Q29 <dbl>, Q30 <int>,
#> #   Q31 <dbl>, Q32 <int>


fit <- efa(data      = HSQ,
           nfactors  = 4,
           rotation  = "oblimin",
           ordered   = TRUE,
           estimator = "WLSMV")

summary(fit, fs.determinacy = TRUE)
#> This is lavaan 0.6-18 -- running exploratory factor analysis
#> 
#>   Estimator                                       DWLS
#>   Rotation method                      OBLIMIN OBLIQUE
#>   Oblimin gamma                                      0
#>   Rotation algorithm (rstarts)                GPA (30)
#>   Standardized metric                             TRUE
#>   Row weights                                     None
#> 
#>                                                   Used       Total
#>   Number of observations                           993        1070
#> 
#> Fit measures:
#>                   chisq  df pvalue   cfi rmsea
#>   nfactors = 4 1641.741 374      0 0.933 0.058
#> 
#> Eigenvalues correlation matrix:
#> 
#>     ev1     ev2     ev3     ev4     ev5     ev6     ev7     ev8     ev9    ev10 
#>   7.442   3.752   3.037   2.403   1.225   1.063   1.027   0.884   0.800   0.757 
#>    ev11    ev12    ev13    ev14    ev15    ev16    ev17    ev18    ev19    ev20 
#>   0.724   0.674   0.643   0.601   0.568   0.556   0.525   0.495   0.465   0.454 
#>    ev21    ev22    ev23    ev24    ev25    ev26    ev27    ev28    ev29    ev30 
#>   0.433   0.421   0.414   0.379   0.358   0.342   0.330   0.319   0.283   0.244 
#>    ev31    ev32 
#>   0.211   0.172 
#> 
#> Standardized loadings: (* = significant at 1% level)
#> 
#>         f1      f2      f3      f4       unique.var   communalities
#> Q1   0.706*                                   0.481           0.519
#> Q2        *  0.618*                           0.578           0.422
#> Q3       .*          0.538*      .*           0.605           0.395
#> Q4                           0.654*           0.562           0.438
#> Q5   0.658*                                   0.527           0.473
#> Q6       .*  0.460*                           0.616           0.384
#> Q7       .*          0.631*                   0.607           0.393
#> Q8                           0.817*           0.326           0.674
#> Q9   0.529*                      .*           0.684           0.316
#> Q10       *  0.818*               *           0.346           0.654
#> Q11      .*       *  0.581*                   0.669           0.331
#> Q12      .*               *  0.667*           0.529           0.471
#> Q13  0.751*                                   0.390           0.610
#> Q14      .*  0.655*                           0.446           0.554
#> Q15                  0.712*                   0.475           0.525
#> Q16       *              .*  0.582*           0.611           0.389
#> Q17  0.805*                                   0.334           0.666
#> Q18      .*  0.830*                           0.369           0.631
#> Q19      .*      .*  0.453*      .*           0.629           0.371
#> Q20       *               *  0.846*           0.277           0.723
#> Q21  0.763*              .*      .*           0.379           0.621
#> Q22       *  0.371*       *                   0.811           0.189
#> Q23       *          0.524*                   0.702           0.298
#> Q24      .*                  0.532*           0.702           0.298
#> Q25  0.824*                       *           0.307           0.693
#> Q26       *  0.683*                           0.461           0.539
#> Q27                  0.576*                   0.667           0.333
#> Q28      .*      .*      .*      .*           0.766           0.234
#> Q29  0.618*              .*      .*           0.586           0.414
#> Q30          0.522*              .*           0.712           0.288
#> Q31       *          0.720*                   0.476           0.524
#> Q32       *                  0.698*           0.471           0.529
#> 
#>                               f1    f4    f2    f3  total
#> Sum of sq (obliq) loadings 4.649 3.659 3.527 3.064 14.899
#> Proportion of total        0.312 0.246 0.237 0.206  1.000
#> Proportion var             0.145 0.114 0.110 0.096  0.466
#> Cumulative var             0.145 0.260 0.370 0.466  0.466
#> 
#> Factor correlations: (* = significant at 1% level)
#> 
#>        f1      f2      f3      f4 
#> f1  1.000                         
#> f2  0.385*  1.000                 
#> f3  0.188*  0.098*  1.000         
#> f4  0.151*  0.213*  0.189*  1.000 
#> 
#> Correlation regression factor scores and factors (determinacy):
#> 
#>    f1    f2    f3    f4 
#> 0.969 0.950 0.921 0.955 
#> 
#> R2 regression factor scores (= squared correlations):
#> 
#>    f1    f2    f3    f4 
#> 0.939 0.903 0.849 0.913

fit <- efa(data      = HSQ,
           nfactors  = 4,
           rotation  = "oblimin",
           ordered   = TRUE,
           estimator = "WLSMV",
           output    = "lavaan")

summary(fit, fit.measures = TRUE, standardized = TRUE)
#> lavaan 0.6-18 ended normally after 42 iterations
#> 
#>   Estimator                                       DWLS
#>   Optimization method                           NLMINB
#>   Number of model parameters                       262
#>   Row rank of the constraints matrix                12
#> 
#>   Rotation method                      OBLIMIN OBLIQUE
#>   Oblimin gamma                                      0
#>   Rotation algorithm (rstarts)                GPA (30)
#>   Standardized metric                             TRUE
#>   Row weights                                     None
#> 
#>                                                   Used       Total
#>   Number of observations                           993        1070
#> 
#> Model Test User Model:
#>                                               Standard      Scaled
#>   Test Statistic                               905.159    1641.741
#>   Degrees of freedom                               374         374
#>   P-value (Chi-square)                           0.000       0.000
#>   Scaling correction factor                                  0.594
#>   Shift parameter                                          117.040
#>     simple second-order correction                                
#> 
#> Model Test Baseline Model:
#> 
#>   Test statistic                             47102.936   19315.122
#>   Degrees of freedom                               496         496
#>   P-value                                        0.000       0.000
#>   Scaling correction factor                                  2.477
#> 
#> User Model versus Baseline Model:
#> 
#>   Comparative Fit Index (CFI)                    0.989       0.933
#>   Tucker-Lewis Index (TLI)                       0.985       0.911
#>                                                                   
#>   Robust Comparative Fit Index (CFI)                            NA
#>   Robust Tucker-Lewis Index (TLI)                               NA
#> 
#> Root Mean Square Error of Approximation:
#> 
#>   RMSEA                                          0.038       0.058
#>   90 Percent confidence interval - lower         0.035       0.056
#>   90 Percent confidence interval - upper         0.041       0.061
#>   P-value H_0: RMSEA <= 0.050                    1.000       0.000
#>   P-value H_0: RMSEA >= 0.080                    0.000       0.000
#>                                                                   
#>   Robust RMSEA                                                  NA
#>   90 Percent confidence interval - lower                        NA
#>   90 Percent confidence interval - upper                        NA
#>   P-value H_0: Robust RMSEA <= 0.050                            NA
#>   P-value H_0: Robust RMSEA >= 0.080                            NA
#> 
#> Standardized Root Mean Square Residual:
#> 
#>   SRMR                                           0.038       0.038
#> 
#> Parameter Estimates:
#> 
#>   Parameterization                               Delta
#>   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 =~ efa                                                             
#>     Q1                0.706    0.021   34.100    0.000    0.706    0.706
#>     Q2                0.073    0.028    2.629    0.009    0.073    0.073
#>     Q3                0.133    0.030    4.478    0.000    0.133    0.133
#>     Q4               -0.001    0.029   -0.025    0.980   -0.001   -0.001
#>     Q5                0.658    0.024   27.399    0.000    0.658    0.658
#>     Q6                0.275    0.035    7.951    0.000    0.275    0.275
#>     Q7               -0.168    0.028   -6.071    0.000   -0.168   -0.168
#>     Q8                0.022    0.021    1.049    0.294    0.022    0.022
#>     Q9                0.529    0.028   19.107    0.000    0.529    0.529
#>     Q10              -0.080    0.020   -4.013    0.000   -0.080   -0.080
#>     Q11              -0.123    0.031   -3.922    0.000   -0.123   -0.123
#>     Q12               0.129    0.027    4.796    0.000    0.129    0.129
#>     Q13               0.751    0.023   32.341    0.000    0.751    0.751
#>     Q14               0.198    0.026    7.589    0.000    0.198    0.198
#>     Q15               0.027    0.024    1.128    0.259    0.027    0.027
#>     Q16               0.086    0.027    3.144    0.002    0.086    0.086
#>     Q17               0.805    0.017   46.953    0.000    0.805    0.805
#>     Q18              -0.116    0.020   -5.747    0.000   -0.116   -0.116
#>     Q19               0.193    0.030    6.526    0.000    0.193    0.193
#>     Q20              -0.077    0.022   -3.556    0.000   -0.077   -0.077
#>     Q21               0.763    0.022   34.628    0.000    0.763    0.763
#>     Q22               0.098    0.034    2.887    0.004    0.098    0.098
#>     Q23               0.089    0.031    2.901    0.004    0.089    0.089
#>     Q24              -0.209    0.034   -6.145    0.000   -0.209   -0.209
#>     Q25               0.824    0.020   40.427    0.000    0.824    0.824
#>     Q26               0.099    0.025    3.913    0.000    0.099    0.099
#>     Q27              -0.065    0.032   -2.043    0.041   -0.065   -0.065
#>     Q28               0.119    0.033    3.554    0.000    0.119    0.119
#>     Q29               0.618    0.026   23.958    0.000    0.618    0.618
#>     Q30               0.057    0.035    1.648    0.099    0.057    0.057
#>     Q31               0.074    0.024    3.020    0.003    0.074    0.074
#>     Q32               0.093    0.025    3.671    0.000    0.093    0.093
#>   f2 =~ efa                                                             
#>     Q1                0.007    0.025    0.288    0.773    0.007    0.007
#>     Q2                0.618    0.024   25.889    0.000    0.618    0.618
#>     Q3                0.018    0.031    0.587    0.557    0.018    0.018
#>     Q4                0.030    0.027    1.082    0.279    0.030    0.030
#>     Q5                0.036    0.029    1.229    0.219    0.036    0.036
#>     Q6                0.460    0.032   14.400    0.000    0.460    0.460
#>     Q7                0.013    0.029    0.456    0.648    0.013    0.013
#>     Q8                0.007    0.020    0.337    0.736    0.007    0.007
#>     Q9               -0.013    0.032   -0.405    0.685   -0.013   -0.013
#>     Q10               0.818    0.017   47.026    0.000    0.818    0.818
#>     Q11               0.100    0.031    3.260    0.001    0.100    0.100
#>     Q12              -0.000    0.026   -0.014    0.989   -0.000   -0.000
#>     Q13               0.067    0.029    2.283    0.022    0.067    0.067
#>     Q14               0.655    0.022   29.247    0.000    0.655    0.655
#>     Q15              -0.046    0.026   -1.802    0.072   -0.046   -0.046
#>     Q16              -0.033    0.029   -1.157    0.247   -0.033   -0.033
#>     Q17              -0.018    0.022   -0.818    0.413   -0.018   -0.018
#>     Q18               0.830    0.018   46.811    0.000    0.830    0.830
#>     Q19               0.139    0.030    4.561    0.000    0.139    0.139
#>     Q20              -0.024    0.021   -1.139    0.255   -0.024   -0.024
#>     Q21               0.042    0.029    1.464    0.143    0.042    0.042
#>     Q22               0.371    0.031   12.106    0.000    0.371    0.371
#>     Q23               0.018    0.031    0.586    0.558    0.018    0.018
#>     Q24               0.058    0.033    1.733    0.083    0.058    0.058
#>     Q25               0.033    0.027    1.234    0.217    0.033    0.033
#>     Q26               0.683    0.022   30.804    0.000    0.683    0.683
#>     Q27               0.025    0.033    0.758    0.448    0.025    0.025
#>     Q28               0.195    0.033    6.002    0.000    0.195    0.195
#>     Q29              -0.044    0.031   -1.428    0.153   -0.044   -0.044
#>     Q30               0.522    0.031   16.714    0.000    0.522    0.522
#>     Q31              -0.058    0.024   -2.442    0.015   -0.058   -0.058
#>     Q32               0.048    0.024    1.976    0.048    0.048    0.048
#>   f3 =~ efa                                                             
#>     Q1                0.015    0.025    0.580    0.562    0.015    0.015
#>     Q2                0.026    0.026    0.991    0.322    0.026    0.026
#>     Q3                0.538    0.025   21.262    0.000    0.538    0.538
#>     Q4                0.006    0.025    0.237    0.813    0.006    0.006
#>     Q5                0.033    0.027    1.227    0.220    0.033    0.033
#>     Q6                0.060    0.031    1.923    0.054    0.060    0.060
#>     Q7                0.631    0.026   24.582    0.000    0.631    0.631
#>     Q8               -0.006    0.018   -0.340    0.734   -0.006   -0.006
#>     Q9                0.013    0.030    0.431    0.666    0.013    0.013
#>     Q10              -0.001    0.021   -0.038    0.970   -0.001   -0.001
#>     Q11               0.581    0.025   23.129    0.000    0.581    0.581
#>     Q12              -0.072    0.025   -2.885    0.004   -0.072   -0.072
#>     Q13               0.028    0.029    0.961    0.337    0.028    0.028
#>     Q14              -0.010    0.024   -0.403    0.687   -0.010   -0.010
#>     Q15               0.712    0.023   31.257    0.000    0.712    0.712
#>     Q16               0.104    0.026    4.030    0.000    0.104    0.104
#>     Q17               0.032    0.023    1.395    0.163    0.032    0.032
#>     Q18              -0.011    0.022   -0.490    0.624   -0.011   -0.011
#>     Q19               0.453    0.027   16.710    0.000    0.453    0.453
#>     Q20               0.078    0.020    3.866    0.000    0.078    0.078
#>     Q21              -0.149    0.027   -5.630    0.000   -0.149   -0.149
#>     Q22               0.084    0.032    2.653    0.008    0.084    0.084
#>     Q23               0.524    0.027   19.141    0.000    0.524    0.524
#>     Q24              -0.023    0.030   -0.756    0.450   -0.023   -0.023
#>     Q25               0.017    0.025    0.672    0.502    0.017    0.017
#>     Q26              -0.013    0.024   -0.530    0.596   -0.013   -0.013
#>     Q27               0.576    0.027   21.408    0.000    0.576    0.576
#>     Q28               0.181    0.031    5.829    0.000    0.181    0.181
#>     Q29               0.158    0.029    5.403    0.000    0.158    0.158
#>     Q30               0.018    0.032    0.562    0.574    0.018    0.018
#>     Q31               0.720    0.021   34.339    0.000    0.720    0.720
#>     Q32              -0.023    0.025   -0.947    0.344   -0.023   -0.023
#>   f4 =~ efa                                                             
#>     Q1                0.047    0.025    1.894    0.058    0.047    0.047
#>     Q2               -0.017    0.025   -0.675    0.500   -0.017   -0.017
#>     Q3                0.142    0.028    5.046    0.000    0.142    0.142
#>     Q4                0.654    0.022   30.048    0.000    0.654    0.654
#>     Q5                0.044    0.028    1.550    0.121    0.044    0.044
#>     Q6               -0.070    0.031   -2.213    0.027   -0.070   -0.070
#>     Q7                0.029    0.027    1.073    0.283    0.029    0.029
#>     Q8                0.817    0.016   52.521    0.000    0.817    0.817
#>     Q9                0.133    0.029    4.545    0.000    0.133    0.133
#>     Q10               0.075    0.021    3.582    0.000    0.075    0.075
#>     Q11              -0.036    0.026   -1.425    0.154   -0.036   -0.036
#>     Q12               0.667    0.021   31.678    0.000    0.667    0.667
#>     Q13              -0.029    0.028   -1.028    0.304   -0.029   -0.029
#>     Q14              -0.036    0.023   -1.605    0.108   -0.036   -0.036
#>     Q15               0.050    0.024    2.116    0.034    0.050    0.050
#>     Q16               0.582    0.022   26.033    0.000    0.582    0.582
#>     Q17               0.059    0.023    2.565    0.010    0.059    0.059
#>     Q18               0.010    0.020    0.485    0.627    0.010    0.010
#>     Q19               0.110    0.027    4.039    0.000    0.110    0.110
#>     Q20               0.846    0.016   54.218    0.000    0.846    0.846
#>     Q21               0.114    0.027    4.249    0.000    0.114    0.114
#>     Q22              -0.012    0.031   -0.372    0.710   -0.012   -0.012
#>     Q23              -0.029    0.029   -0.999    0.318   -0.029   -0.029
#>     Q24               0.532    0.026   20.779    0.000    0.532    0.532
#>     Q25              -0.070    0.025   -2.813    0.005   -0.070   -0.070
#>     Q26               0.034    0.023    1.480    0.139    0.034    0.034
#>     Q27               0.036    0.027    1.318    0.188    0.036    0.036
#>     Q28               0.259    0.030    8.580    0.000    0.259    0.259
#>     Q29              -0.177    0.029   -6.137    0.000   -0.177   -0.177
#>     Q30              -0.173    0.032   -5.456    0.000   -0.173   -0.173
#>     Q31              -0.052    0.021   -2.474    0.013   -0.052   -0.052
#>     Q32               0.698    0.019   35.870    0.000    0.698    0.698
#> 
#> Covariances:
#>                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
#>   f1 ~~                                                                 
#>     f2                0.385    0.028   13.828    0.000    0.385    0.385
#>     f3                0.188    0.031    6.124    0.000    0.188    0.188
#>     f4                0.151    0.030    5.075    0.000    0.151    0.151
#>   f2 ~~                                                                 
#>     f3                0.098    0.031    3.189    0.001    0.098    0.098
#>     f4                0.213    0.029    7.312    0.000    0.213    0.213
#>   f3 ~~                                                                 
#>     f4                0.189    0.031    6.045    0.000    0.189    0.189
#> 
#> Thresholds:
#>                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
#>     Q1|t1            -1.878    0.079  -23.646    0.000   -1.878   -1.878
#>     Q1|t2            -1.239    0.053  -23.308    0.000   -1.239   -1.239
#>     Q1|t3            -0.613    0.043  -14.382    0.000   -0.613   -0.613
#>     Q1|t4             0.314    0.041    7.758    0.000    0.314    0.314
#>     Q2|t1            -1.577    0.064  -24.567    0.000   -1.577   -1.577
#>     Q2|t2            -0.777    0.044  -17.471    0.000   -0.777   -0.777
#>     Q2|t3             0.044    0.040    1.110    0.267    0.044    0.044
#>     Q2|t4             1.045    0.049   21.417    0.000    1.045    1.045
#>     Q3|t1            -1.261    0.054  -23.470    0.000   -1.261   -1.261
#>     Q3|t2            -0.490    0.042  -11.778    0.000   -0.490   -0.490
#>     Q3|t3             0.291    0.040    7.190    0.000    0.291    0.291
#>     Q3|t4             1.212    0.052   23.098    0.000    1.212    1.212
#>     Q4|t1            -1.094    0.050  -21.977    0.000   -1.094   -1.094
#>     Q4|t2            -0.212    0.040   -5.293    0.000   -0.212   -0.212
#>     Q4|t3             0.539    0.042   12.836    0.000    0.539    0.539
#>     Q4|t4             1.395    0.058   24.210    0.000    1.395    1.395
#>     Q5|t1            -1.796    0.075  -24.067    0.000   -1.796   -1.796
#>     Q5|t2            -1.080    0.049  -21.827    0.000   -1.080   -1.080
#>     Q5|t3            -0.218    0.040   -5.420    0.000   -0.218   -0.218
#>     Q5|t4             0.822    0.045   18.238    0.000    0.822    0.822
#>     Q6|t1            -2.195    0.104  -21.049    0.000   -2.195   -2.195
#>     Q6|t2            -1.503    0.061  -24.511    0.000   -1.503   -1.503
#>     Q6|t3            -0.855    0.046  -18.762    0.000   -0.855   -0.855
#>     Q6|t4             0.113    0.040    2.822    0.005    0.113    0.113
#>     Q7|t1            -1.151    0.051  -22.558    0.000   -1.151   -1.151
#>     Q7|t2            -0.110    0.040   -2.759    0.006   -0.110   -0.110
#>     Q7|t3             0.753    0.044   17.054    0.000    0.753    0.753
#>     Q7|t4             1.495    0.061   24.498    0.000    1.495    1.495
#>     Q8|t1            -0.753    0.044  -17.054    0.000   -0.753   -0.753
#>     Q8|t2             0.095    0.040    2.379    0.017    0.095    0.095
#>     Q8|t3             0.688    0.043   15.849    0.000    0.688    0.688
#>     Q8|t4             1.568    0.064   24.567    0.000    1.568    1.568
#>     Q9|t1            -1.343    0.056  -23.974    0.000   -1.343   -1.343
#>     Q9|t2            -0.691    0.043  -15.909    0.000   -0.691   -0.691
#>     Q9|t3            -0.130    0.040   -3.266    0.001   -0.130   -0.130
#>     Q9|t4             0.892    0.046   19.336    0.000    0.892    0.892
#>     Q10|t1           -1.067    0.049  -21.675    0.000   -1.067   -1.067
#>     Q10|t2           -0.283    0.040   -7.001    0.000   -0.283   -0.283
#>     Q10|t3            0.461    0.041   11.153    0.000    0.461    0.461
#>     Q10|t4            1.343    0.056   23.974    0.000    1.343    1.343
#>     Q11|t1           -0.938    0.047  -20.013    0.000   -0.938   -0.938
#>     Q11|t2           -0.004    0.040   -0.095    0.924   -0.004   -0.004
#>     Q11|t3            0.487    0.042   11.715    0.000    0.487    0.487
#>     Q11|t4            1.337    0.056   23.942    0.000    1.337    1.337
#>     Q12|t1           -1.067    0.049  -21.675    0.000   -1.067   -1.067
#>     Q12|t2           -0.333    0.041   -8.200    0.000   -0.333   -0.333
#>     Q12|t3            0.357    0.041    8.767    0.000    0.357    0.357
#>     Q12|t4            1.266    0.054   23.509    0.000    1.266    1.266
#>     Q13|t1           -2.254    0.110  -20.421    0.000   -2.254   -2.254
#>     Q13|t2           -1.759    0.073  -24.217    0.000   -1.759   -1.759
#>     Q13|t3           -1.212    0.052  -23.098    0.000   -1.212   -1.212
#>     Q13|t4           -0.306    0.040   -7.569    0.000   -0.306   -0.306
#>     Q14|t1           -1.325    0.055  -23.875    0.000   -1.325   -1.325
#>     Q14|t2           -0.580    0.042  -13.703    0.000   -0.580   -0.580
#>     Q14|t3            0.080    0.040    1.998    0.046    0.080    0.080
#>     Q14|t4            0.837    0.045   18.471    0.000    0.837    0.837
#>     Q15|t1           -0.530    0.042  -12.650    0.000   -0.530   -0.530
#>     Q15|t2            0.034    0.040    0.856    0.392    0.034    0.034
#>     Q15|t3            0.568    0.042   13.456    0.000    0.568    0.568
#>     Q15|t4            1.313    0.055   23.806    0.000    1.313    1.313
#>     Q16|t1           -1.071    0.049  -21.726    0.000   -1.071   -1.071
#>     Q16|t2           -0.202    0.040   -5.040    0.000   -0.202   -0.202
#>     Q16|t3            0.436    0.041   10.589    0.000    0.436    0.436
#>     Q16|t4            1.349    0.056   24.006    0.000    1.349    1.349
#>     Q17|t1           -1.796    0.075  -24.067    0.000   -1.796   -1.796
#>     Q17|t2           -1.233    0.053  -23.267    0.000   -1.233   -1.233
#>     Q17|t3           -0.675    0.043  -15.605    0.000   -0.675   -0.675
#>     Q17|t4            0.125    0.040    3.139    0.002    0.125    0.125
#>     Q18|t1           -1.011    0.048  -20.996    0.000   -1.011   -1.011
#>     Q18|t2           -0.153    0.040   -3.836    0.000   -0.153   -0.153
#>     Q18|t3            0.571    0.042   13.518    0.000    0.571    0.571
#>     Q18|t4            1.436    0.059   24.356    0.000    1.436    1.436
#>     Q19|t1           -1.266    0.054  -23.509    0.000   -1.266   -1.266
#>     Q19|t2           -0.542    0.042  -12.898    0.000   -0.542   -0.542
#>     Q19|t3            0.082    0.040    2.061    0.039    0.082    0.082
#>     Q19|t4            0.953    0.047   20.235    0.000    0.953    0.953
#>     Q20|t1           -0.338    0.041   -8.326    0.000   -0.338   -0.338
#>     Q20|t2            0.553    0.042   13.146    0.000    0.553    0.553
#>     Q20|t3            1.122    0.050   22.272    0.000    1.122    1.122
#>     Q20|t4            1.893    0.080   23.557    0.000    1.893    1.893
#>     Q21|t1           -2.288    0.114  -20.059    0.000   -2.288   -2.288
#>     Q21|t2           -1.759    0.073  -24.217    0.000   -1.759   -1.759
#>     Q21|t3           -1.136    0.051  -22.416    0.000   -1.136   -1.136
#>     Q21|t4           -0.199    0.040   -4.977    0.000   -0.199   -0.199
#>     Q22|t1           -1.176    0.052  -22.788    0.000   -1.176   -1.176
#>     Q22|t2           -0.301    0.040   -7.443    0.000   -0.301   -0.301
#>     Q22|t3            0.387    0.041    9.459    0.000    0.387    0.387
#>     Q22|t4            1.217    0.053   23.141    0.000    1.217    1.217
#>     Q23|t1           -1.356    0.056  -24.037    0.000   -1.356   -1.356
#>     Q23|t2           -0.542    0.042  -12.898    0.000   -0.542   -0.542
#>     Q23|t3            0.176    0.040    4.407    0.000    0.176    0.176
#>     Q23|t4            1.041    0.049   21.365    0.000    1.041    1.041
#>     Q24|t1           -0.791    0.045  -17.708    0.000   -0.791   -0.791
#>     Q24|t2            0.192    0.040    4.787    0.000    0.192    0.192
#>     Q24|t3            0.942    0.047   20.069    0.000    0.942    0.942
#>     Q24|t4            1.586    0.065   24.566    0.000    1.586    1.586
#>     Q25|t1           -2.223    0.107  -20.750    0.000   -2.223   -2.223
#>     Q25|t2           -1.736    0.071  -24.298    0.000   -1.736   -1.736
#>     Q25|t3           -1.250    0.053  -23.390    0.000   -1.250   -1.250
#>     Q25|t4           -0.270    0.040   -6.685    0.000   -0.270   -0.270
#>     Q26|t1           -1.577    0.064  -24.567    0.000   -1.577   -1.577
#>     Q26|t2           -0.945    0.047  -20.124    0.000   -0.945   -0.945
#>     Q26|t3           -0.179    0.040   -4.470    0.000   -0.179   -0.179
#>     Q26|t4            0.757    0.044   17.113    0.000    0.757    0.757
#>     Q27|t1           -0.354    0.041   -8.704    0.000   -0.354   -0.354
#>     Q27|t2            0.373    0.041    9.145    0.000    0.373    0.373
#>     Q27|t3            0.829    0.045   18.355    0.000    0.829    0.829
#>     Q27|t4            1.487    0.061   24.484    0.000    1.487    1.487
#>     Q28|t1           -1.136    0.051  -22.416    0.000   -1.136   -1.136
#>     Q28|t2           -0.498    0.042  -11.965    0.000   -0.498   -0.498
#>     Q28|t3            0.075    0.040    1.871    0.061    0.075    0.075
#>     Q28|t4            0.880    0.046   19.165    0.000    0.880    0.880
#>     Q29|t1           -1.526    0.062  -24.542    0.000   -1.526   -1.526
#>     Q29|t2           -0.942    0.047  -20.069    0.000   -0.942   -0.942
#>     Q29|t3           -0.317    0.041   -7.821    0.000   -0.317   -0.317
#>     Q29|t4            0.580    0.042   13.703    0.000    0.580    0.580
#>     Q30|t1           -1.992    0.087  -22.868    0.000   -1.992   -1.992
#>     Q30|t2           -1.228    0.053  -23.225    0.000   -1.228   -1.228
#>     Q30|t3           -0.619    0.043  -14.505    0.000   -0.619   -0.619
#>     Q30|t4            0.283    0.040    7.001    0.000    0.283    0.283
#>     Q31|t1           -1.266    0.054  -23.509    0.000   -1.266   -1.266
#>     Q31|t2           -0.450    0.041  -10.902    0.000   -0.450   -0.450
#>     Q31|t3            0.176    0.040    4.407    0.000    0.176    0.176
#>     Q31|t4            0.826    0.045   18.296    0.000    0.826    0.826
#>     Q32|t1           -0.918    0.047  -19.733    0.000   -0.918   -0.918
#>     Q32|t2           -0.267    0.040   -6.621    0.000   -0.267   -0.267
#>     Q32|t3            0.464    0.041   11.215    0.000    0.464    0.464
#>     Q32|t4            1.337    0.056   23.942    0.000    1.337    1.337
#> 
#> Variances:
#>                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
#>    .Q1                0.481                               0.481    0.481
#>    .Q2                0.578                               0.578    0.578
#>    .Q3                0.605                               0.605    0.605
#>    .Q4                0.562                               0.562    0.562
#>    .Q5                0.527                               0.527    0.527
#>    .Q6                0.616                               0.616    0.616
#>    .Q7                0.607                               0.607    0.607
#>    .Q8                0.326                               0.326    0.326
#>    .Q9                0.684                               0.684    0.684
#>    .Q10               0.346                               0.346    0.346
#>    .Q11               0.669                               0.669    0.669
#>    .Q12               0.529                               0.529    0.529
#>    .Q13               0.390                               0.390    0.390
#>    .Q14               0.446                               0.446    0.446
#>    .Q15               0.475                               0.475    0.475
#>    .Q16               0.611                               0.611    0.611
#>    .Q17               0.334                               0.334    0.334
#>    .Q18               0.369                               0.369    0.369
#>    .Q19               0.629                               0.629    0.629
#>    .Q20               0.277                               0.277    0.277
#>    .Q21               0.379                               0.379    0.379
#>    .Q22               0.811                               0.811    0.811
#>    .Q23               0.702                               0.702    0.702
#>    .Q24               0.702                               0.702    0.702
#>    .Q25               0.307                               0.307    0.307
#>    .Q26               0.461                               0.461    0.461
#>    .Q27               0.667                               0.667    0.667
#>    .Q28               0.766                               0.766    0.766
#>    .Q29               0.586                               0.586    0.586
#>    .Q30               0.712                               0.712    0.712
#>    .Q31               0.476                               0.476    0.476
#>    .Q32               0.471                               0.471    0.471
#>     f1                1.000                               1.000    1.000
#>     f2                1.000                               1.000    1.000
#>     f3                1.000                               1.000    1.000
#>     f4                1.000                               1.000    1.000

^{Created on 2024-09-14 with reprex v2.1.1}

[juliuspfadt]

Thanks. It is a good request, but it will likely involve changing the underlying R-package from psych to lavaan at least for this function. At the moment one can choose to use the polychoric instead of the Pearson correlation matrix for ordinal data. I wonder if the polychoric matrix approach is worse performance wise than DWLS?

[TarandeepKang]

Hi all, Tentatively, and based upon my reading of this lavaan forum discussion thread, we may have some initial evidence that DWLS is to be preferred, but it still seems to be an open question. Https://groups.google.com/g/lavaan/c/c2V9Fhz3JDk

[juliuspfadt]

thanks :) yes, this reads like we should switch to lavaan for the analysis in general.

[TarandeepKang]

No problem, glad I could help! And for what it's worth, I do agree. I just wasn't feeling quite bold enough to suggest a project that would be perhaps quite so much work :-)

[TarandeepKang]

Hi @amda-cyber, Apologies for the delay, I'm not a member of the development team, just a PhD student with something of an interest in psychological statistics and methodology. As you might tell from this discussion above (and others another poster started somewhere else) this is quite a big topic. But, there does exist another piece of point-and-click software with the capability to use DWLS in EFA: https://psico.fcep.urv.cat/utilitats/factor/index.html