The Benjamini-Hochberg Method in the Case of Discrete Test Statistics

We present a reformulation of the Benjamini-Hochberg method that is useful in 'large-scale' multiple testing problems based on discrete test statistics and derive its basic asymptotic (as the number of hypotheses tends to infinity) properties, subsuming earlier results. A set of gene expression data is used to illustrate the workings of the method in a multiple testing problem based on Kolmogorov-Smirnov and Mann-Whitney statistics.

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Year of publication:	2007
Authors:	Ferreira, José
Published in:	International Journal of Biostatistics. - Berkeley Electronic Press. - Vol. 3.2007, 1, p. 1065-1065
Publisher:	Berkeley Electronic Press
Subject:	multiple testing \| false discovery rate \| average power \| non-parametric tests

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Extent:	application/pdf
Type of publication:	Article
Notes:	oai:bepress:ijb-1065
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005246580