%0 Journal Article %A B. Rizzato, Fernanda %A A. Leandro, Roseli %A G.B. Demétrio, Clarice %A Molenberghs, Geert %D 2016 %T A Bayesian approach to analyse overdispersed longitudinal count data %U https://tandf.figshare.com/articles/journal_contribution/A_Bayesian_approach_to_analyse_overdispersed_longitudinal_count_data/1629352 %R 10.6084/m9.figshare.1629352.v1 %2 https://ndownloader.figshare.com/files/2615471 %K Bayesian analysis %K Bayesian model assessment %K count data %K generalized linear mixed model %K over dispersion %X

In this paper, we consider a model for repeated count data, with within-subject correlation and/or overdispersion. It extends both the generalized linear mixed model and the negative-binomial model. This model, proposed in a likelihood context [17,18] is placed in a Bayesian inferential framework. An important contribution takes the form of Bayesian model assessment based on pivotal quantities, rather than the often less adequate DIC. By means of a real biological data set, we also discuss some Bayesian model selection aspects, using a pivotal quantity proposed by Johnson [12].

%I Taylor & Francis