Incorporating the Empirical Null Hypothesis into the Benjamini-Hochberg Procedure

Ghosh Debashis
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Ghosh Debashis: Penn State University

Statistical Applications in Genetics and Molecular Biology, 2012, vol. 11, issue 4, 21

Abstract: For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. We show how the B-H procedure can be interpreted as a test based on the spacings corresponding to the p-value distributions. This interpretation leads to the incorporation of the empirical null hypothesis, a term coined by Efron (2004). We develop a mixture modelling approach for the empirical null hypothesis for the B-H procedure and demonstrate some theoretical results regarding both finite-sample as well as asymptotic control of the false discovery rate. The methodology is illustrated with application to two high-throughput datasets as well as to simulated data.

Keywords: false discovery rate; familywise error; mixture model; multiple comparisons; simultaneous inference (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1515/1544-6115.1735

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