title: Statistical properties of an early stopping rule for resampling-based multiple testing.
abstract: Resampling-based methods for multiple hypothesis testing often lead to long run times when the number of tests is large. This paper presents a simple rule that substantially reduces computation by allowing resampling to terminate early on a subset of tests. We prove that the method has a low probability of obtaining a set of rejected hypotheses different from those rejected without early stopping, and obtain error bounds for multiple hypothesis testing. Simulation shows that our approach saves more computation than other available procedures.
authors.affiliation: Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, Michigan 48109, U.S.A. , jianghui@umich.edu.
authors.forename: Hui
authors.initials: H
authors.lastname: Jiang
authors.forename: Julia
authors.initials: J
authors.lastname: Salzman
keywords: Bootstrap; Early stopping; False discovery rate control; Multiple hypothesis testing; Resampling