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 Seniz Celimli posted on Thursday, May 29, 2014 - 9:35 am
I am working on fitting a multivariate mixture model in Mplus (fully unconstrained MVN mixture model) and having a problem that I am struggling with. There are 5 variables in my dataset. They are all in the same continuous scale. The lowest score possible is 55 in all variables and one variable has quite a few cases with the lowest score (~10%). While the 2-class solution converges without problems, the 3-class solution doesn't converge due to the problematic cases that I just described. All of those cases (with the same lowest score in that variable) were assigned into one of the 3 classes which results in no variability in the estimates for that variable. Since there is no variability for one variable, the model is having convergence problems we believe. Is there any way that I can solve this problem? Thanks! Seniz
 Bengt O. Muthen posted on Thursday, May 29, 2014 - 1:11 pm
Can't say for sure without looking at your runs and data. But you can try the new skew-t distribution option in Mplus Version 7.2 which allows a class with a heavily censored distribution.
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