On a generalized false discovery rate

Sarkar, Sanat K. ; Guo, Wenge

Ann. Statist., Tome 37 (2009) no. 1, p. 1545-1565 / Harvested from Project Euclid

Résumé

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.

Détail

Publié le : 2009-06-15
Classification:  Average power,  gene expression,  generalized FDR,  generalized FWER,  multiple hypothesis testing,  oracle k-FDR procedure,  stepup procedures,  62J15,  62H99