Multiple conditional randomization tests for lagged and spillover treatment effects

Yao Zhang and Qingyuan Zhao

Biometrika, 2025, vol. 112, issue 1, 3-16

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 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.

Keywords: Causal inference; Conditioning; Evidence factor; Interference; Randomization test; Stepped-wedge design (search for similar items in EconPapers)
Date: 2025
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