In reading 'Asparouhov & Muthen (2007) - Computationally efficient estimation of multilevel high-dimensional latent variable models', I observe that WLSM performed well in the two-level case when compared to ML for balanced group sizes.
To what extent can these results be assumed to hold for WLSMV also?
For a two level CFA with unbalanced group sizes (ranging from 1 to 100) and categorical data is there any basis on which to favour one type of estimator (either WLSMV, WLSM) over another?
And is there any reason to worry that either of these two estimators may prove unreliable in the unbalanced senario?
It was really the performance of either WLSM or WLSMV in the senario of unbalanced group sizes that I was more concerned with. I have seen nothing in the literature about the use of either of these estimates in the unbalanced senario - are they appropriate for two-level models with clusters of different sizes?