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http://hdl.handle.net/1942/2038
Title: | A hierarchical binomial-poisson model for the analysis of a crossover design for correlated binary data when the number of trials is dose-dependent | Authors: | SHKEDY, Ziv MOLENBERGHS, Geert Van Craenendonck, Hansfried BIJNENS, Luc Steckler, Thomas |
Issue Date: | 2005 | Publisher: | TAYLOR & FRANCIS INC | Source: | JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 15(2). p. 225-239 | Abstract: | The differential reinforcement of a low-rate 72-seconds schedule (DRL-72) is a standard behavioral test procedure for screening a potential antidepressant compound. The data analyzed in the article are binary outcomes from a crossover design for such an experiment. Recently, Shkedy et al. ( 2004) proposed to estimate the treatments effect using either generalized linear mixed models (GLMM) or generalized estimating equations ( GEE) for clustered binary data. The models proposed by Shkedy et al. ( 2004) assumed the number of responses at each binomial observation is fixed. This might be an unrealistic assumption for a behavioral experiment such as the DRL-72 because the number of responses ( the number of trials in each binomial observation) is expected to be influenced by the administered dose level. In this article, we extend the model proposed by Shkedy et al. ( 2004) and propose a hierarchical Bayesian binomial-Poisson model, which assumes the number of responses to be a Poisson random variable. The results obtained from the GLMM and the binomial-Poisson models are comparable. However, the latter model allows estimating the correlation between the number of successes and number of trials. | Notes: | Limburgs Univ Ctr, Ctr Stat Biostat, B-3590 Diepenbeek, Belgium. Janssen Pharmaceut, Johnson & Johnson Pharmaceut Res & Dev, B-2340 Beerse, Belgium.Shkedy, Z, Limburgs Univ Ctr, Ctr Stat Biostat, Univ Campus, B-3590 Diepenbeek, Belgium.ziv.shkedy@luc.ac.be | Keywords: | Binomial-Poisson model; correlated binary data; cross-over design; generalized estimation equation; generalized linear mixed models; hierarchical Bayesian Models; odds ratio;binomial-Poisson model; correlated binary data; cross-over design; generalized estimation equation; generalized linear mixed models; hierarchical Bayesian Models; odds ratio | Document URI: | http://hdl.handle.net/1942/2038 | ISSN: | 1054-3406 | e-ISSN: | 1520-5711 | DOI: | 10.1081/BIP-200049825 | ISI #: | 000236232300004 | Rights: | © Taylor & Francis, Inc | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2007 |
Appears in Collections: | Research publications |
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