The Annals of Statistics

On false discovery control under dependence

Wei Biao Wu

Full-text: Open access

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.

Article information

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

Dates
First available in Project Euclid: 1 February 2008

Permanent link to this document
https://projecteuclid.org/euclid.aos/1201877305

Digital Object Identifier
doi:10.1214/009053607000000730

Mathematical Reviews number (MathSciNet)
MR2387975

Zentralblatt MATH identifier
1139.62040

Subjects
Primary: 62H15: Hypothesis testing
Secondary: 62G10: Hypothesis testing

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

Citation

Wu, Wei Biao. On false discovery control under dependence. Ann. Statist. 36 (2008), no. 1, 364--380. doi:10.1214/009053607000000730. https://projecteuclid.org/euclid.aos/1201877305


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