To expand on the issue I'm having a bit:
I am trying to build a latent class model. The dataset I am working with contains some scales related to shopping habits, plus several demographic items (age, race, income, etc.).
When I try to build the model with all variables added, it cannot converge. I am able to get convergence with a model (5 classes) that just includes the shopping habit scales, but I would still like to see the demographic differences between each class.
Would it be OK for me to take the classes I have developed and use them as predictors in a series of chi-square analyses or ANOVAs or something to examine how each of the 5 classes differ on race, income, age, etc? Or would this not be methodologically sound?
Alternatively, does anyone have any general advice on how to deal with a model when you can't seem to get it to converge? Thanks!