Open Access
February 2008 On false discovery control under dependence
Wei Biao Wu
Ann. Statist. 36(1): 364-380 (February 2008). DOI: 10.1214/009053607000000730


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.


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Wei Biao Wu. "On false discovery control under dependence." Ann. Statist. 36 (1) 364 - 380, February 2008.


Published: February 2008
First available in Project Euclid: 1 February 2008

zbMATH: 1139.62040
MathSciNet: MR2387975
Digital Object Identifier: 10.1214/009053607000000730

Primary: 62H15
Secondary: 62G10

Keywords: Dependence , False discovery rate , Markov random field , multiple testing , p-value

Rights: Copyright © 2008 Institute of Mathematical Statistics

Vol.36 • No. 1 • February 2008
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