Going out on a limb here, but if you fit the repeated nature as a G-side matrix in PROC GLIMMIX, and use method=laplace or method=quad, you will get quasi-likelihood information criteria, which could be used to rank the distributions, provided there is no difference in the fixed effects part of the model AND an identical link function is used. This would work for comparing Poisson to negative binomial. Unfortunately, the zero inflated models aren't easily fit in GLIMMIX, and this method probably isn't a good method to compare them in any case, as they are truly mixture models, so the resulting quasi-likelihood won't reflect the same "data".
Something more general using PROC NLMIXED could probably be done, but my brain is turning to mush and I don't have a link to that right at hand.
Steve Denham
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