A Holm-type procedure controlling the false discovery rate

Yongchao Ge, Stuart C. Sealfon, Chi-Hong Tseng and Terence P. Speed

Statistics & Probability Letters, 2007, vol. 77, issue 18, 1756-1762

Abstract: Benjamini and Hochberg [1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Statist. Soc. Ser. B 57, 289-300] proposed a step-up procedure controlling the false discovery rate (FDR) under the assumption that test statistics are independent. Benjamini and Yekutieli [2001. The control of false discovery rate in multiple hypothesis testing under dependency. Ann. Statist. 29 (4) 1165-1188] further developed a conservative procedure without this assumption. This paper proposes a Holm-type procedure controlling the FDR. This simple step-down procedure can be more powerful than the Benjamini and Yekutieli (2001) procedure when the number of rejected hypotheses is smaller than ln(m), where m is the total number of hypotheses.

Keywords: Multiple; testing; Holm; False; discovery; rate; Bonferroni; Dependent; data (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(07)00164-2
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:77:y:2007:i:18:p:1756-1762

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().