On false discovery control under dependence

On false discovery control under dependence

Wei Biao Wu

Source: Ann. Statist. Volume 36, Number 1 (2008), 364-380.

Abstract

A popular framework for false discovery control is the random effects model in which the null hypotheses are assumed to be independent. This paper generalizes the random effects model to a conditional dependence model which allows dependence between null hypotheses. The dependence can be useful to characterize the spatial structure of the null hypotheses. Asymptotic properties of false discovery proportions and numbers of rejected hypotheses are explored and a large-sample distributional theory is obtained.

Primary Subjects: 62H15

Secondary Subjects: 62G10

Keywords: False discovery rate; Markov random field; multiple testing; dependence; p-value

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Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aos/1201877305
Digital Object Identifier: doi:10.1214/009053607000000730
Mathematical Reviews number (MathSciNet): MR2387975
Zentralblatt MATH identifier: 1139.62040

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