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Longitudinal Poisson modeling: an application for CD4 counting in HIV-infected patients

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  • Emilio Augusto Coelho-Barros
  • Jorge Alberto Achcar
  • Josmar Mazucheli

Abstract

In this paper, we present different “frailty” models to analyze longitudinal data in the presence of covariates. These models incorporate the extra-Poisson variability and the possible correlation among the repeated counting data for each individual. Assuming a CD4 counting data set in HIV-infected patients, we develop a hierarchical Bayesian analysis considering the different proposed models and using Markov Chain Monte Carlo methods. We also discuss some Bayesian discrimination aspects for the choice of the best model.

Suggested Citation

  • Emilio Augusto Coelho-Barros & Jorge Alberto Achcar & Josmar Mazucheli, 2010. "Longitudinal Poisson modeling: an application for CD4 counting in HIV-infected patients," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(5), pages 865-880.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:5:p:865-880
    DOI: 10.1080/02664760902914466
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    References listed on IDEAS

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    Cited by:

    1. Fernanda B. Rizzato & Roseli A. Leandro & Clarice G.B. Demétrio & Geert Molenberghs, 2016. "A Bayesian approach to analyse overdispersed longitudinal count data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(11), pages 2085-2109, August.

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