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On a Generalized False Discovery Rate
by
Sarkar, Sanat K.
, Guo, Wenge
in
62H99
/ 62J15
/ Average power
/ Critical values
/ Data sampling
/ Error rates
/ Errors
/ Exact sciences and technology
/ gene expression
/ General topics
/ generalized FDR
/ generalized FWER
/ Logical givens
/ Mathematical procedures
/ Mathematics
/ multiple hypothesis testing
/ Null hypothesis
/ oracle k-FDR procedure
/ Oracles
/ P values
/ Point estimators
/ Probability
/ Probability and statistics
/ Random variables
/ Sciences and techniques of general use
/ Statistics
/ stepup procedures
/ Studies
2009
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On a Generalized False Discovery Rate
by
Sarkar, Sanat K.
, Guo, Wenge
in
62H99
/ 62J15
/ Average power
/ Critical values
/ Data sampling
/ Error rates
/ Errors
/ Exact sciences and technology
/ gene expression
/ General topics
/ generalized FDR
/ generalized FWER
/ Logical givens
/ Mathematical procedures
/ Mathematics
/ multiple hypothesis testing
/ Null hypothesis
/ oracle k-FDR procedure
/ Oracles
/ P values
/ Point estimators
/ Probability
/ Probability and statistics
/ Random variables
/ Sciences and techniques of general use
/ Statistics
/ stepup procedures
/ Studies
2009
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On a Generalized False Discovery Rate
by
Sarkar, Sanat K.
, Guo, Wenge
in
62H99
/ 62J15
/ Average power
/ Critical values
/ Data sampling
/ Error rates
/ Errors
/ Exact sciences and technology
/ gene expression
/ General topics
/ generalized FDR
/ generalized FWER
/ Logical givens
/ Mathematical procedures
/ Mathematics
/ multiple hypothesis testing
/ Null hypothesis
/ oracle k-FDR procedure
/ Oracles
/ P values
/ Point estimators
/ Probability
/ Probability and statistics
/ Random variables
/ Sciences and techniques of general use
/ Statistics
/ stepup procedures
/ Studies
2009
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Journal Article
On a Generalized False Discovery Rate
2009
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Overview
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.
Publisher
Institute of Mathematical Statistics,The Institute of Mathematical Statistics
Subject
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