Simultaneous false discovery proportion bounds via knockoffs and closed testing
成果类型：
Article
署名作者：
Li, Jinzhou; Maathuis, Marloes H.; Goeman, Jelle J.
署名单位：
Stanford University; Swiss Federal Institutes of Technology Domain; ETH Zurich; Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC
刊物名称：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
ISSN/ISSBN：
1369-7412
DOI：
10.1093/jrsssb/qkae012
发表日期：
2024
页码：
966-986
关键词：
摘要：
We propose new methods to obtain simultaneous false discovery proportion bounds for knockoff-based approaches. We first investigate an approach based on Janson and Su's k-familywise error rate control method and interpolation. We then generalize it by considering a collection of k values, and show that the bound of Katsevich and Ramdas is a special case of this method and can be uniformly improved. Next, we further generalize the method by using closed testing with a multi-weighted-sum local test statistic. This allows us to obtain a further uniform improvement and other generalizations over previous methods. We also develop an efficient shortcut for its implementation. We compare the performance of our proposed methods in simulations and apply them to a data set from the UK Biobank.