Multiple conditional randomization tests for lagged and spillover treatment effects
成果类型：
Article
署名作者：
Zhang, Yao; Zhao, Qingyuan
署名单位：
Stanford University; University of Cambridge
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asae042
发表日期：
2024
关键词：
摘要：
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 effects in stepped-wedge trials, and spillover effects 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.