Computational Statistics

, Volume 18, Issue 1, pp 39–55 | Cite as

Regression Models for Correlated Biliary Data with Random Effects Assuming a Mixture of Normal Distributions

  • Jorge Alberto Achcar
  • Vanderly Janeiro
  • Josmar Mazucheli


Binary responses are correlated when the sampling units are clustered or when repeated binary responses are taken on the same experiment unit. In this paper we present a Bayesian analysis of logistic regression models for correlated binary data with random effects. We assume that the random effects, namely αi, i = 1, …, n are draw from a mixture of normal distributions. This assumption gives a great flexibility of fit by correlated binary data. Considering Gibbs sampling with Metropolis-Hastings algorithms, we obtain Monte Carlo estimates for the posterior quantities of interest


correlated binary data logistic regression model random effects mixture of normal distributions 



The authors are thankful to the referees for some useful suggestions which improved the paper.


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Copyright information

© Physica-Verlag 2003

Authors and Affiliations

  • Jorge Alberto Achcar
    • 1
  • Vanderly Janeiro
    • 2
  • Josmar Mazucheli
    • 2
  1. 1.ICMCUniversity of São PauloSão CarlosBrazil
  2. 2.Department of StatisticState University of MaringaMaringaBrazil

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