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Malgorzata Bogdan

Professor

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On the empirical bayes approach to the problem of multiple testing

Författare

  • Malgorzata Bogdan
  • Jayanta K. Ghosh
  • Aleksandra Ochman
  • Surya T. Tokdar

Summary, in English

We discuss the Empirical Bayes approach to the problem of multiple testing and compare it with a very popular frequentist method of Benjamini and Hochberg aimed at controlling the false discovery rate. Our main focus is the 'sparse mixture' case, when only a small proportion of tested hypotheses is expected to be false. The specific parametric model we consider is motivated by the application to detecting genes responsible for quantitative traits, but it can be used in a variety of other applications. We define some Parametric Empirical Bayes procedures for multiple testing and compare them with the Benjamini and Hochberg method using computer simulations. We explain some similarities between these two approaches by placing them within the same framework of threshold tests with estimated critical values.

Publiceringsår

2007-10

Språk

Engelska

Sidor

727-739

Publikation/Tidskrift/Serie

Quality and Reliability Engineering International

Volym

23

Issue

6

Dokumenttyp

Artikel i tidskrift

Förlag

John Wiley & Sons Inc.

Ämne

  • Probability Theory and Statistics

Nyckelord

  • Empirical Bayes
  • False discovery rate
  • Multiple testing

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 0748-8017