Hi, I am working with a LCA model with two latent variables each with two categories. The model looks good and the categories makes a lot of sense and look like what I had expected. I wanted to use auxiliary variables in 3step process to check their effect on latent classes. However 3 step does not seem to work with the models with more than one latent variable. When I run a LCA model with one variable and 4 categories instead of having two variables with two categories I get different classes which don't look as good as two variable categories. So is there a way to constrain LCA model with one latent variable (4 categories) in a way that it will have the same categories as the model with two variables? In this case I would have the categories I want and still use 3step for multinomial regression.
I encounter a problem that did not occur when I modelled only one categorical latent variable. Now that I model a two categorical latent variable multiple group LCA, I always get the following error message:
*** ERROR in MODEL command Unknown class label in MODEL : %CCYCLE#1.CC#1%
However, CYCLE has been introduced in the names command and further:
This worked with only one categorical latent variable, and I had assumed I could introduce similar restrictions in a multiple group LCA with two latent variables. If not so, how can I fix the conditional response probabilities (and class sizes) to be the same in both (known) groups?