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Dear Muthen & Muthen, I notice that the DIFFTEST option is not available in a multilevel CFA. My analysis uses a saturated within-level model with a 4 factor measurement model fit to the between level. The estimator is WLSMV with categorical observables. So that I may assess the improvement in fit for my between level model when compared to the same between level model with an error covariance freed, is there some way that I can do the DIFFTEST manually without being exposed to any complicated mathmatics or horrible equations? Kind regards, Jonahton |
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I am afraid it involves complicated statistics. The easiest way out is to use WLSM instead of WLSMV. |
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Cheers for this Bengt. When you say that the easiest way out is to use WLSM instead of WLSMV, am I correct in assuming that when using WLSM that a comparison of nested models is simply a matter of computing the difference between the chi-square and degrees of freedom for the two models in the same way that you would for normal theory ML? Jonathon |
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Right. |
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Ok this is a little confusing Bengt, After reading page 367 of the User manual and the standard MPLUS output that is printed below: "The chi-square value for MLM, MLMV, MLR, ULSMV, WLSM and WLSMV cannot be used for chi-square difference tests. MLM, MLR and WLSM chi-square difference testing is described in the Mplus Technical Appendices at www.statmodel.com. See chi-square difference testing in the index of the Mplus User's Guide" Can you re-read this thread and my questions and explain this contradiction for me. You answered "right" to my question which read "am I correct in assuming that when using WLSM that a comparison of nested models is simply a matter of computing the difference between the chi-square and degrees of freedom for the two models in the same way that you would for normal theory ML?" Regards, Jonathon |
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You need to take the scaling correction factor into account when doing difference testing for WLSM. See Chi-Sqare Difference Test for MLM and MLR on the website. This applies also to WLSM. |
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