is there a way to obtain model fit indices like BIC when using CFA with the categorical and/or weight option? (as reported in muthen b., addiction 2006, "should substance use disorders be considered as categorical or dimensional?", table 1; binary items are used).
is there a way to use the MIXED procedure to get that by suppressing latent classes? (because mixed when used for hybrid analysis reports these indices).
You can do this in two ways. You can use TYPE=MIXTURE; with one class, CLASSES= c(1); Or you can estimate the model using maximum likelihood, ESTIMATOR=MLR; instead of the default of weighted least squares.