I am trying to run a Poisson longitudinal multilevel model using Mplus. I know how to do it in HLM, and I am trying to compare both programs to make sure that I did everything correctly. However, I am running into some issues:
1. HLM gives unit specific estimates and population average estimates. However, Mplus only provides one and based on a random intercept model I am assuming it is unit-specific estimates, is this correct?
2. When I introduce random slope on time, I get quite a different variance terms and the fixed effect for the intercept is vastly different from HLM.
I understand that the estimators can play a role in the difference. I ran a full PQL in HLM and ML in Mplus. Had all the estimates been approximately close to one on another I would proceed with Mplus and used MLR since I want to use FIML for my missing data.
Here is the code for the random slope on time model for reference:
missing = all(-9999); cluster is CASEID_1979; count is ACT_WMIN (p);
within is t; usevariables are t ACT_WMIN;
Analysis: estimator is ML; type is twolevel; !random
It sounds like HLM does not do ML. First, make sure your model has the same number of parameters in both software so they are comparable (also check sample size).
I don't know what you mean by unit-specific estimates. The model you specified has parameters which are estimated. It also has random effects (intercept and slope) which can be estimated for each subject using FSCORES.