10.6084/m9.figshare.1629352.v1
Fernanda B. Rizzato
Fernanda
B. Rizzato
Roseli A. Leandro
Roseli
A. Leandro
Clarice G.B. Demétrio
Clarice
G.B. Demétrio
Geert Molenberghs
Geert
Molenberghs
A Bayesian approach to analyse overdispersed longitudinal count data
Taylor & Francis Group
2016
Bayesian analysis
Bayesian model assessment
count data
generalized linear mixed model
over dispersion
2016-01-05 14:53:06
Journal contribution
https://tandf.figshare.com/articles/journal_contribution/A_Bayesian_approach_to_analyse_overdispersed_longitudinal_count_data/1629352
<p>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 [<a href="#CIT0017" target="_blank">17</a>,<a href="#CIT0018" target="_blank">18</a>] 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 [<a href="#CIT0012" target="_blank">12</a>].</p>