FURTHER RESULTS ON CONTROLLING THE FALSE DISCOVERY PROPORTION

Citation
Wenge Guo et al., FURTHER RESULTS ON CONTROLLING THE FALSE DISCOVERY PROPORTION, Annals of statistics , 42(3), 2014, pp. 1070-1101
Journal title
ISSN journal
00905364
Volume
42
Issue
3
Year of publication
2014
Pages
1070 - 1101
Database
ACNP
SICI code
Abstract
Institute of Mathematical Statistics logo Journal Article FURTHER RESULTS ON CONTROLLING THE FALSE DISCOVERY PROPORTION Wenge Guo, Li He and Sanat K. Sarkar The Annals of Statistics The Annals of Statistics Vol. 42, No. 3 (June 2014), pp. 1070-1101 (32 pages) Published by: Institute of Mathematical Statistics Previous Item Next Item Stable URL https://www.jstor.org/stable/43556315 Remote Access URL https://www.ezproxy.unibo.it/login?url=https://www.jstor.org/stable /43556315 Abstract The probability of false discovery proportion (FDP) exceeding .. [0,1), defined as .-FDP, has received much attention as a measure of false discoveries in multiple testing. Although this measure has received acceptance due to its relevance under dependency, not much progress has been made yet advancing its theory under such dependency in a nonasymptotic setting, which motivates our research in this article. We provide a larger class of procedures containing the stepup analog of, and hence more powerful than, the stepdown procedure in Lehmann and Romano [Ann. Statist. 33 (2005) 1138-1154] controlling the .-FDP under similar positive dependence condition assumed in that paper. We offer better alternatives of the stepdown and stepup procedures in Romano and Shaikh [IMS Lecture Notes Monogr. Ser. 49 (2006a) 33-50, Ann. Statist. 34 (2006b) 1850-1873] using pairwise joint distributions of the null p-values. We generalize the notion of .-FDP making it appropriate in situations where one is willing to tolerate a few false rejections or, due to high dependency, some false rejections are inevitable, and provide methods that control this generalized .-FDP in two different scenarios: (i) only the marginal p-values are available and (ii) the marginal p-values as well as the common pairwise joint distributions of the null p-values are available, and assuming both positive dependence and arbitrary dependence conditions on the p-values in each scenario. Our theoretical findings are being supported through numerical studies.