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Incorporating the Empirical Null Hypothesis into the Benjamini-Hochberg Procedure

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  • Ghosh Debashis

    (Penn State University)

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.

Suggested Citation

  • Ghosh Debashis, 2012. "Incorporating the Empirical Null Hypothesis into the Benjamini-Hochberg Procedure," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-21, July.
    • Handle: RePEc:bpj:sagmbi:v:11:y:2012:i:4:n:11
    DOI: 10.1515/1544-6115.1735
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    References listed on IDEAS

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