A multivariate version of the Benjamini-Hochberg method

JA Ferreira, Stephen Nyangoma

Research output: Contribution to journalArticle

5 Citations (Scopus)


We propose a multivariate method for combining results from independent studies about the same 'large scale' multiple testing problem. The method works asymptotically in the number of hypotheses and consists of applying the Benjamini-Hochberg procedure to the p-values of each study separately by determining the 'individual false discovery rates' which maximize power subject to a restriction on the (global) false discovery rate. We show how to obtain solutions to the associated optimization problem, provide both theoretical and numerical examples, and compare the method with univariate ones. (C) 2008 Elsevier Inc. All rights reserved.
Original languageEnglish
Pages (from-to)2108-2124
Number of pages17
JournalJournal of Multivariate Analysis
Issue number9
Publication statusPublished - 1 Oct 2008


  • Empirical distributions
  • Multiple testing
  • Average power
  • False discovery rate


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