Department of Statistics Unitmark
Dietrich College of Humanities and Social Sciences

Bayesian Frequentist Multiple Testing

Publication Date

April, 2002

Publication Type

Tech Report

Author(s)

Christopher Genovese and Larry Wasserman

Abstract

We introduce a Bayesian approach to multiple testing. The method is an extension of the false discovery rate (FDR) method due to Benjamini and Hochberg (1995). We also examine the empirical Bayes approach to simultaneous inference proposed by Efron, Tibshirani, Storey and Tusher (2001). We show that, in contrast to the single hypothesis case - where Bayes and frequentist tests do not agree even asymptotically - in the multiple testing case we do have asymptotic agreement.