Goodness-of-fit tests for discrete response models with covariates

Abstract We propose goodness-of-fit tests for models of count responses with covariates. Our main focus is on the null hypothesis that the observed data come from a Poisson, a negative binomial, or a binomial regression model, but the method is fairly general allowing for the responses to follow, conditionally on covariates, any given discrete distribution. The test criteria are formulated by using the probability generating function and they are convenient from a computational point of view. Asymptotic as well as Monte Carlo results are presented. Applications on real data are also reported.