This paper applies a Bayesian approach to ecological-type inference in matched-pair studies because traditional methods that assume parallel tables are not directly applicable. The proposed procedure is based on a hierarchical Bayes structure which models information about the within-pair association. The proposed algorithm relies on Markov chain Monte Carlo simulation, recovers the full table, and reports its accuracy in terms of credible sets for the cell counts. This methodology is motivated and illustrated with examples from split-mouth designs assessing the effectiveness of dental sealant materials and cross-over trials comparing two forms of insulin. Published in 2011 by John Wiley & Sons, Ltd.
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