Inference on treatment‐covariate interaction based on a nonparametric measure of treatment effects and censored survival data |
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| Authors: | Shan Jiang Bingshu Chen Dongshengn Tu |
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| Affiliation: | 1. Department of Mathematics and Statistics, Queen's University, Kingston, Ontario, Canada;2. Canadian Cancer Trials Group, Queen's University, Kingston, Ontario, Canada |
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| 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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| Keywords: | biomarker clinical trial confidence interval density ratio model empirical likelihood interaction non‐parametric inference |
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