Modelling Count Responses with Overdispersion Jeong, Kwang Mo;
We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.
Clustered data;overdispersion;quasi-likelihood;dispersion parameter;zero-inflated Poisson;negative binomial;generalized linear mixed model;