There has been increased interest of late in the Bayesian approach to multiple testing (often called the multiple comparisons problem), motivated by the need to analyze DNA microarray data in which it is desired to learn which of potentially several thousand genes are activated by a particular stimulus. We study the issue of prior specification for such multiple tests; computation of key posterior quantities; and useful ways to display these quantities. A decision-theoretic approach is also considered.
Keywords: multiple hypothesis testing; DNA microarrays; Bayesian model selection.
The final paper appeared as: Scott, James G. and Berger, James O. "An Exploration of Aspects of Bayesian Multiple Testing." Journal of Statistical Planning and Inference 136.7 (2006): 2144-2162. A more detailed version is available in manuscript form as a PDF file.