LCA, count variables, overdispersion PreviousNext
Mplus Discussion > Latent Variable Mixture Modeling >
 John G. Orme posted on Thursday, December 15, 2011 - 10:25 am
I want to estimate a latent class model with count variables and for each variable the variance is much larger than the mean. I donít think that the overdispersion is due to an excess of zeros. So, it doesnít seem that the Poisson model available in Mplus would be appropriate. What would the best option be in this situation?

Thanks for any help you can give me with this, and thank you for your answer to my earlier question concerning relaxation of the local independence assumption with count variables.
 Bengt O. Muthen posted on Thursday, December 15, 2011 - 11:14 am
I think a mixture Poisson is perfect for such a situation - and that is what you are doing when doing LCA and specifying the DVs as counts.
 Scott R. Colwell posted on Thursday, December 17, 2015 - 3:50 pm
I just wanted to check something regarding the output with a zero inflated Poisson mixture model.

The means in the output are log means and would need to be exponentiated in order to interpret them as means. This would imply that extreme values like -15 would indicate a mean of 0.

Is this correct?

 Bengt O. Muthen posted on Sunday, December 20, 2015 - 5:24 pm
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