The Benjamini-Hochberg method with infinitely many contrasts in linear models

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Benjamini and Hochberg's method for controlling the false discovery rate is applied to the problem of testing infinitely many contrasts in linear models. Exact, easily calculated critical values are derived, defining a new multiple comparisons method for testing contrasts in linear models. The method is adaptive, depending on the data through the F-statistic, like the Waller-Duncan Bayesian multiple comparisons method. Comparisons with Scheffé's method are given, and the method is extended to the simultaneous confidence intervals of Benjamini and Yekutieli.

Original languageEnglish
Pages (from-to)709-719
Number of pages11
JournalBiometrika
Volume95
Issue number3
DOIs
StatePublished - Sep 2008

Keywords

  • False coverage rate
  • False discovery rate
  • Multiple comparisons
  • Multiple testing
  • Scheffé's method
  • Waller-Duncan method

Fingerprint Dive into the research topics of 'The Benjamini-Hochberg method with infinitely many contrasts in linear models'. Together they form a unique fingerprint.

  • Cite this