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 Frank Alexander Rojas posted on Friday, November 17, 2017 - 11:14 am
Hi,

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

model:
%within%
s | ACT_WMIN on t;

%between%
ACT_WMIN;
s with ACT_WMIN;
 Bengt O. Muthen posted on Friday, November 17, 2017 - 12:21 pm
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.
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