False discovery proportion estimation by permutations: confidence for significance analysis of microarrays
成果类型：
Article
署名作者：
Hemerik, Jesse; Goeman, Jelle J.
署名单位：
Leiden University - Excl LUMC; Leiden University; Leiden University Medical Center (LUMC)
刊物名称：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
ISSN/ISSBN：
1369-7412
DOI：
10.1111/rssb.12238
发表日期：
2018
页码：
137-155
关键词：
摘要：
Significance analysis of microarrays (SAM) is a highly popular permutation-based multiple-testing method that estimates the false discovery proportion (FDP): the fraction of false positive results among all rejected hypotheses. Perhaps surprisingly, until now this method had no known properties. This paper extends SAM by providing 1- upper confidence bounds for the FDP, so that exact confidence statements can be made. As a special case, an estimate of the FDP is obtained that underestimates the FDP with probability at most 0.5. Moreover, using a closed testing procedure, this paper decreases the upper bounds and estimates in such a way that the confidence level is maintained. We base our methods on a general result on exact testing with random permutations.
来源URL：