Parametric and nonparametric FDR estimation revisited

Baolin Wu, Zhong Guan, Hongyu Zhao

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Nonparametric and parametric approaches have been proposed to estimate false discovery rate under the independent hypothesis testing assumption. The parametric approach has been shown to have better performance than the nonparametric approaches. In this article, we study the nonparametric approaches and quantify the underlying relations between parametric and nonparametric approaches. Our study reveals the conservative nature of the nonparametric approaches, and establishes the connections between the empirical Bayes method and p-value-based nonparametric methods. Based on our results, we advocate using the parametric approach, or directly modeling the test statistics using the empirical Bayes method.

Original languageEnglish (US)
Pages (from-to)735-744+953
JournalBiometrics
Volume62
Issue number3
DOIs
StatePublished - Sep 1 2006

Keywords

  • Empirical Bayes method
  • False discovery rate
  • Microarray
  • Multiple comparisons
  • Multiple hypothesis testing
  • Simultaneous inference

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