ON A GENERALIZED FALSE DISCOVERY RATE

• 成果类型: Article
• 署名作者: Sarkar, Sanat K.; Guo, Wenge
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS)
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/08-AOS617
• 发表日期: 2009
• 页码: 1545-1565
• 关键词: multiple testing procedures; Familywise Error Rate; stepup procedures; PROPORTION; number; NULL; fdr

摘要

The concept of k-FWER has received much attention lately as an appropriate error rate for multiple testing when one seeks to control at least k false rejections, for some fixed k >= 1. A less conservative notion, the k-FDR, has been introduced very recently by Sarkar [Ann. Statist. 34 (2006) 394-415], generalizing the false discovery rate of Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300]. In this article, we bring newer insight to the k-FDR considering a mixture model involving independent p-values before motivating the developments of some new procedures that control it. We prove the k-FDR control of the proposed methods under a slightly weaker condition than in the mixture model. We provide numerical evidence of the proposed methods' superior power performance over some k-FWER and k-FDR methods. Finally, we apply our methods to a real data set.