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

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Author Info

  • José A. Ferreira

    (Vrije University Medical Centre, Amsterdam)

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    Abstract

    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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    File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1065&context=ijb
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    Bibliographic Info

    Article provided by De Gruyter in its journal The International Journal of Biostatistics.

    Volume (Year): 3 (2007)
    Issue (Month): 1 ()
    Pages: 11

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    Handle: RePEc:bpj:ijbist:v:3:y:2007:i:1:n:11

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    Web page: http://www.degruyter.com

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    Web: http://www.degruyter.com/view/j/ijb

    Related research

    Keywords: Microarrays; Statistical Theory and Methods; multiple testing; false discovery rate; average power; non-parametric tests;

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