I am conducting a Bayesian LCA with three indicators and two distal outcomes. Since MODEL TEST and the AUXILIARY approach are not available for ESTIMATOR = BAYES, I use the "old" approach and look at the variation of the outcomes across classes.
The model runs fine, the chains are mixing good and converging, and I get a reasonable class-solution. However, I am stuck at assigning individuals to classes. I do not know how to assign individuals to classes; with ESTIMATOR = ML, you just use SAVE = CPROB to obtain most likely class-membership. With ESTIMATOR = BAYES, this option is not available. When I use SAVE = FSCORES, the plausible values for most likely class membership never match the number of individuals in the respective groups.
I feel like I am missing an obvious point here, but could somebody kindly tell me how (i.e. based on what output/part of the output) to assign individuals to classes in Bayesian LCA?