JSM 2005 Online Program

Abstract #303485

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Activity Number:	258
Type:	Topic Contributed
Date/Time:	Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Bayesian Statistical Science
Abstract - #303485
Title:	Bayesian Sample Size Determination for Case-control Studies
Author(s):	Cyr Emile M'Lan*+
Companies:	University of Connecticut
Address:	Dept of Statistics, STORRS, CT, 06269, United States
Keywords:	Case-control studies ; Sample size determination ; Highest posterior density intervals ; Odds ratio ; Optimal control to case ratio
Abstract:	One of the most important statistical issues at the planning stage of a case-control study is the choice of sample size. For example, one might wish to select a sample size that ensures sufficient accuracy in estimating the odds ratio. In this talk, we show how sample size determination for estimating the odds ratio can be addressed within the Bayesian paradigm. We focus on the average length criterion (ALC). Basically, this method proposes that the sample size be selected that guarantees a prespecified length for a marginal posterior credible interval of predetermined coverage, averaged over the predictive distribution of the data. he solution, while easy to define, is technically challenging to carry out in practice. We discuss three methods for finding the optimal sample size, including approximate sample-size formula, a crude Monte Carlo approach, and regression-based Monte Carlo approach.

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