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Published on: October 23, 2020
Inference on treatment-covariate interaction based on a nonparametric measure of treatment effects and censored
Shan Jiang1, Bingshu Chen2, Dongshengn Tu2
1Department of Mathematics and Statistics, Queen's University, Kingston, Ontario, Canada.
Abstract:
The investigation of the treatment-covariate interaction is of considerable interest in the design and analysis of clinical trials. With potentially censored data observed, non-parametric and semi-parametric estimates and associated confidence intervals are proposed in this paper to quantify the interactions between the treatment and a binary covariate. In addition, comparison of interactions between the treatment and two covariates are also considered. The proposed approaches are evaluated and compared by Monte Carlo simulations and applied to a real data set from a cancer clinical trial. Copyright © 2016 John Wiley & Sons, Ltd.
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