Malgorzata Bogdan
Professor
On the empirical bayes approach to the problem of multiple testing
Författare
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