I have a question that I can't find the answer to. I have a latent class model with covariates, essentially a "1-step" model that approximates a multinomial logistic regression with the latent classes as dependent variable categories. So far so good.

What I would like to be able to do is then use post estimation commands to generate predicted probabilities for some specific categories of variables. If I was doing a multinomial logistic regression, I would do this with Long and Freese's

Is it possible to do something like this for the model here? If so, does anyone know how? I can't figure it out. (The margins command does run after the model, but returns probabilities for each of the input variables, not for the latent classes).

Code:

gsem (inputvar1 inputvar2 inputvar3 inputvar4 inputvar5 <- ) /// (C <- income age male white, logit) /// [pweight=weightvar], logit startvalues(randomid, draws(8) seed(54321)) em(iter(5)) lclass(C 4)

**mtable**command as below, or simply with**margins**. In the present case I would like to be able to do something similar for predicted probabilities of class membership as in the model.Code:

mtable, at (male(1 0) white(1 0)) atmeans ci

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