Multiple conditional randomization tests for lagged and spillover treatment effects
Abstract
We consider the problem of constructing multiple independent conditional randomization tests using a single dataset. Because the tests are independent, the randomization p-values can be interpreted individually and combined using standard methods for multiple testing. We give a simple, sequential construction of such tests, and then discuss its application to three problems: Rosenbaum's evidence factors for observational studies, lagged treatment effect in stepped-wedge trials, and spillover effect in randomized trials with interference. We compare the proposed approach with some existing methods using simulated and real datasets. Finally, we establish a more general sufficient condition for independent conditional randomization tests.
Cite
@article{arxiv.2104.10618,
title = {Multiple conditional randomization tests for lagged and spillover treatment effects},
author = {Yao Zhang and Qingyuan Zhao},
journal= {arXiv preprint arXiv:2104.10618},
year = {2024}
}
Comments
43 pages, 7 figures; Part of the original version of this paper can be found at arXiv:2203.10980; To appear in Biometrika