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On the False Discovery Rate and Expected Type I Errors
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References
2001
Year
Computational Complexity TheoryEngineeringStatistical FoundationComputational ComplexityData ScienceData MiningFamilywise Error RateBiostatisticsBayesian MethodsFalse Discovery RatePublic HealthKolmogorov ComplexityStatisticsFdr ConceptLower BoundAutomated ReasoningFdr-controlling ProceduresTime ComplexityStatistical InferenceProperty Testing
The paper is concerned with expected type I errors of some stepwise multiple test procedures based on independent p-values controlling the so-called false discovery rate (FDR). We derive an asymptotic result for the supremum of the expected type I error rate(EER) when the number of hypotheses tends to infinity. Among others, it will be shown that when the original Benjamini-Hochberg step-up procedure controls the FDR at level α, its EER may approach a value being slightly larger than α/4 when the number of hypotheses increases. Moreover, we derive some least favourable parameter configuration results, some bounds for the FDR and the EER as well as easily computable formulae for the familywise error rate (FWER) of two FDR-controlling procedures. Finally, we discuss some undesirable properties of the FDR concept, especially the problem of cheating.