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|Title: ||A Bayesian approach to analyse overdispersed longitudinal count data|
|Authors: ||Rizzato, F.B.|
|Issue Date: ||2016|
|Citation: ||Journal of applied statistics, 43(11), p. 2085-2109|
|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 [17,18] 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 .|
|Notes: ||Rizzato, FB (reprint author), Univ Fed Parana, Stat, Curitiba, Parana, Brazil.
|ISI #: ||000382570500009|
|Type: ||Journal Contribution|
|Validation: ||ecoom, 2017|
|Appears in Collections: ||Research publications|
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