A0758
Title: Interaction tests with covariate-adaptive randomization
Authors: Likun Zhang - Renmin University of China (China)
Wei Ma - Renmin University of China (China) [presenting]
Abstract: Treatment-covariate interaction tests are commonly applied by researchers to examine whether the treatment effect varies across patient subgroups defined by baseline characteristics. The objective is to explore treatment-covariate interaction tests involving covariate-adaptive randomization. Without assuming a parametric data-generating model, usual interaction tests are investigated and it is observed that they tend to be conservative. Specifically, their limiting rejection probabilities under the null hypothesis do not exceed the nominal level and are typically strictly lower than it. Modifications are proposed to the usual tests to obtain corresponding valid tests to address this problem. Moreover, a novel class of stratified-adjusted interaction tests are introduced that are simple, more powerful than the usual and modified tests, and broadly applicable to most covariate-adaptive randomization methods. The results encompass two types of interaction tests: one involving stratification covariates and the other involving additional covariates that are not used for randomization. The application of interaction tests in clinical trials is clarified, and valuable tools are offered to reveal treatment heterogeneity, which is crucial for advancing personalized medicine.
