E-values: Calibration, combination, and applications
Forthcoming in the Annals of Statistics
48 Pages Posted: 1 Jan 2020 Last revised: 22 Sep 2020
Date Written: December 14, 2019
Abstract
Multiple testing of a single hypothesis and testing multiple hypotheses are usually done in terms of p-values. In this paper we replace p-values with their natural competitor, e-values, which are closely related to betting, Bayes factors, and likelihood ratios. We demonstrate that e-values are often mathematically more tractable; in particular, in multiple testing of a single hypothesis, e-values can be merged simply by averaging them. This allows us to develop ecient procedures using e-values for testing multiple hypotheses.
Keywords: Hypothesis testing, multiple hypothesis testing, Bayes factor, test martingale, admissible decisions
JEL Classification: C12
Suggested Citation: Suggested Citation