A Bayesian approach to analyse overdispersed longitudinal count data |
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Authors: | Fernanda B Rizzato Roseli A Leandro Clarice GB Demétrio |
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Institution: | 1. Statistics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil;2. ESALQ-USP, S?o Paulo, Brazil;3. ESALQ-USP, S?o Paulo, Brazil |
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Abstract: | 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 G. Molenberghs, G. Verbeke, and C.G.B. Demétrio, An extended random-effects approach to modeling repeated, overdispersion count data, Lifetime Data Anal. 13 (2007), pp. 457–511.Web of Science ®] , Google Scholar],18 G. Molenberghs, G. Verbeke, C.G.B. Demétrio, and A. Vieira, A family of generalized linear models for repeated measures with normal and conjugate random effects, Statist. Sci. 25 (2010), pp. 325–347. doi: 10.1214/10-STS328Crossref], Web of Science ®] , Google Scholar]] 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 V.E. Johnson, Bayesian model assessment using pivotal quantities, Bayesian Anal. 2 (2007), pp. 719–734. doi: 10.1214/07-BA229Crossref], Web of Science ®] , Google Scholar]]. |
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Keywords: | Bayesian analysis Bayesian model assessment count data generalized linear mixed model over dispersion |
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