Excuse me if this is a silly qn. I am proposing a study where I want to use LCA to identify sub-groups of problem gamblers based on 5 continuous latent class indicators. However, I want to specify a 'non-problem gambler' class (a zero class) a priori. Is this possible, and if so, can you direct me to where I can find more information on how to do it. Im thinking it may be possible using the training variable command, but I cant find any information it.
I have done it before in a different analysis with LCGA but not by using the training command (instead I specified a zero class with I s q @ 0 and then defining high thresholds so that the probabilities of exceeding these high thresholds are zero)
It is hard to specify a zero class with continuous indicators because it implies zero variance for them, which results in singularity. Perhaps the continuous variables have a lower censoring point at zero in which case maybe specifying them as censored or two-part opens up a way to do it.