A note on multiple testing for composite null hypotheses

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• 作者：Stefano Cabras
• 关键词：Composite null hypothesis ; Elimination of nuisance parameters ; False discovery rate ; Partial posterior predictive p-values ; Positive false discovery rate
• 刊名：Journal of Statistical Planning and Inference
• 出版年：2010
• 出版时间：March 2010
• 年：2010
• 卷：140
• 期：3
• 页码：659-666
• 全文大小：819 K

文摘

Multiple hypothesis testing literature has recently experienced a growing development with particular attention to the control of the false discovery rate (FDR) based on p-values. While these are not the only methods to deal with multiplicity, inference with small samples and large sets of hypotheses depends on the specific choice of the p-value used to control the FDR in the presence of nuisance parameters. In this paper we propose to use the partial posterior predictive p-value [Bayarri, M.J., Berger, J.O., 2000. p-values for composite null models. J. Amer. Statist. Assoc. 95, 1127–1142] that overcomes this difficulty. This choice is motivated by theoretical considerations and examples. Finally, an application to a controlled microarray experiment is presented.