LCA with multiple latent variabels an... PreviousNext
Mplus Discussion > Latent Variable Mixture Modeling >
 Dato Tsabutashvili posted on Friday, April 18, 2014 - 2:42 pm
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.

Thank you very much!
 Linda K. Muthen posted on Saturday, April 19, 2014 - 4:42 pm
See the LTA example in Web Note 15.
 Frank Reichert posted on Tuesday, March 31, 2015 - 11:49 am

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 :

However, CYCLE has been introduced in the names command and further:

knownclass = CCycle (Cycle = 1 Cycle = 2);
classes = CCycle(2) CC(4) CS(4);

In my model command, I state:

CC CS ON CCycle;

[P333a$1] (1);
[P333b$1] (2);
[P333c$1] (3);
[P333d$1] (4);
[P333e$1] (5);

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?

Thank you!
 Bengt O. Muthen posted on Wednesday, April 01, 2015 - 12:46 am
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