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I’m looking at some longitudinal data with binary outcomes. These are all observed variables (various health problems such as cancer, heart disease, etc.), so no latent variables will be included. Covariates will be included (sex, age race). I would like to compare M/F adjusting for age and race. Is a growth mixture model appropriate? I only have two time points so I can’t fit quadratic effects but I can still perform the analysis in Mplus, correct? I’d also be interested in the probabilities of switching categories between time 1 and 2. I can conduct a latent transition analysis as well, right? |
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I would not do growth modeling or growth mixture modeling with two time points and binary indicators. You can consider LTA. |
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