

LCA with multiple latent variabels an... 

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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. Thank you very much! 


See the LTA example in Web Note 15. 


Hi, 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: knownclass = CCycle (Cycle = 1 Cycle = 2); classes = CCycle(2) CC(4) CS(4); In my model command, I state: %OVERALL% CC CS ON CCycle; %CCycle#1.CC#1% [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! 


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