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st: Modeling Options Overdispersion and "excess zeros"

Subject   st: Modeling Options Overdispersion and "excess zeros"
Date   Thu, 13 Jul 2006 23:03:36 -0400

I am working with data that gives clear evidence of both overdispersion and excess zeros. Accordingly, I have been examining the viability of modelling it using zero-inflated models (ZIP and ZINB) as well as negative binomial regression (NBRM). Vuong tests tell me that ZIP is preferred to the standard Poisson; on the other hand, ZINB does not give a significant improvement over NBRM, implying (as I understand it) that either a zero-inflating process or between-subject heterogeneity may account for both the overdispersion and the excess zeros in the raw data. At the same time (and similar to the the example given in David Dukker's reponse to an issue like this in FAQ), standard errors for ZINB are large, suggesting a poor fit of this model. Subsequently, I followed that procedures given in Long and Freese (2e: 2003, pp. 283-84) and graphed the differences between the observed probabilities and mean predictions for the different models. The results indicate that NBRM performing more poorly than ZIP, with ZIP and ZINB performing in an almost identical manner. Subsequently (and again following Long and Freese) I have compared the models using BIC', with ZIP emerging as overall best. From this, I have concluded that ZIP is my best option. At the same time, it also fits with where I am at substantively with these data. To those who actually have knowledge of the underlying processes associate with this, does all this seem reasonable? Have I left something out or made a leap I shouldn't have? Thanks.
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