Hello, I ran a longitudinal LCA and have selected a 4 class model and now want to look at covariates. Can you tell me how Mplus handles missing data on the indicators when using R3step? My indicators do have missing data, but when I ran the unconditional model, I used FIML and all of my cases were used. However, when I ran the conditional model, I lost several cases. Is there a special way to invoke FIML when using R3step?
The reason for the deleted cases is missing data in the covariates (not the indicators). You can use the manual R3step, see section 3 http://statmodel.com/download/webnotes/webnote15.pdf where you can include a model for the covariates. Instead of C on X; you would use C on X; X;
My question is regarding FIML and dealing with missing data when adding covariates to an LCA model. Has there been any new developments regarding handling missing data when using the automatic R3STEP (I believe the default is listwise deletion), or the recommended method still the manual R3STEP to avoid losing the cases that have missing in one or more of the covariates?
To avoid listwise deletion, we are trying to conduct a manual R3STEP analysis for a model in which we are regressing a latent variable (c) on covariates. Webnote 15 details how to regress a distal outcome on a latent variable with very useful syntax. I cannot, however, locate example syntax for our analyses, and we are having difficulty adapting the syntax from Webnote 15. Is there available sample syntax for the manual R3STEP that includes a latent variable regressed on covariates?