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

On adaptive procedures controlling the familywise error rate

The idea of modifying, and potentially improving, classical multiple testing methods controlling the familywise error rate (FWER) via an estimate of the unknown number of true null hypotheses has been around for a long time without a formal answer to the question whether or not such adaptive methods ultimately maintain the strong control of FWER, until Finner and Gontscharuk (2009) and Guo (200...

Examining Multiple Comparison Procedures According to Error Rate, Power Type and False Discovery Rate

Procedures controlling generalized false discovery rate

Procedures controlling error rates measuring at least k false rejections, instead of at least one, can potentially increase the ability of a procedure to detect false null hypotheses in situations where one seeks to control k or more false rejections having tolerated a few of them. The k-FWER, which is the probability of at least k false rejections and generalizes the usual familywise error rat...

Generalizations of the Familywise Error Rate

Consider the problem of simultaneously testing null hypotheses H1, . . . ,Hs. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly if s is large, one might be willing to tolerate more than one false rejection provided the nu...

Familywise Error Rate Control via Knockoffs

We present a novel method for controlling the k-familywise error rate (k-FWER) in the linear regression setting using the knockoffs framework first introduced by Barber and Candès. Our procedure, which we also refer to as knockoffs, can be applied with any design matrix with at least as many observations as variables, and does not require knowing the noise variance. Unlike other multiple testin...