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

Elena Kulinskaya, Alex Lewin

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)201-211
Number of pages11
Issue number1
Publication statusPublished - 2009

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