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 efficient procedures using e-values for testing multiple hypotheses.
| Original language | English |
|---|---|
| Pages (from-to) | 1736-1754 |
| Number of pages | 19 |
| Journal | The Annals of Statistics |
| Volume | 49 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 9 Aug 2021 |
Keywords
- hypothesis testing
- multiple hypothesis testing
- global null
- admissible decisions
- test martingale
- Bayes factor