On fuzzy familywise error rate and false discovery rate procedures for discrete distributions

Kulinskaya, Elena and Lewin, Alex (2009) On fuzzy familywise error rate and false discovery rate procedures for discrete distributions. Biometrika, 96 (1). pp. 201-211. ISSN 1464-3510

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Abstract

Fuzzy multiple comparisons procedures are introduced as a solution to the problem of multiple comparisons for discrete test statistics. The critical function of the randomized p-values is proposed as a measure of evidence against the null hypotheses. The classical concept of randomized tests is extended to multiple comparisons. This approach makes all theory of multiple comparisons developed for continuously distributed statistics automatically applicable to the discrete case. Examples of familywise error rate and false discovery rate procedures are discussed and an application to linkage disequilibrium testing is given. Software for implementing the procedures is available.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Norwich Epidemiology Centre
Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
Faculty of Science > Research Groups > Data Science and Statistics
Faculty of Medicine and Health Sciences > Research Centres > Business and Local Government Data Research Centre
Depositing User: Vishal Gautam
Date Deposited: 11 Mar 2011 16:23
Last Modified: 22 Apr 2023 00:46
URI: https://ueaeprints.uea.ac.uk/id/eprint/23072
DOI: 10.1093/biomet/asn061

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