Can we run Melton and Liang's GEE approach In MPlus, (mine is MPlus version 3.12), the reason I'm asking so because in your 1997 article, u have done a comparative study of ur proposed estimator in comparison to their GEE ... if we can then how
In my model, indicator variables are all ordered categorical?
Dear Proffesor ... In connection to my earlier message ... I forgot to mention the main reason why I'm looking for Melton and Young's(M&Y) GEE approach ... in ur 97 article, page 24, you have mentioned M&Y's approach performed better than Robust WLS particularly when the sample size is small ... I have two sample size, one is 240 and the other one is 139 (my models are SEM with covariates and categorical indicator outcomes variables)
No, Mplus does not use the GEE approach. We don't feel there is enough of an advantage over robust WLSMV. We also have full-information maximum likelihood for categorical outcomes which theoretically should perform as well if not better than GEE.
what should be our estimator choice in order to run full-information ML for Categorical Outcome ... is it ML, MLR or MLF (page 366, MPlus manual)
I suppose my understanding could be wrong, please correct it if it so.... isnít the case that we use Limited Information ML (I mean separate equation wise) for the first two-stages of 3-stage estimation procedure propounded by Dr. Muthen (1983,1984)