5 papers
Shape-Preserving Covariate Adjustment via Empirical Likelihood in Randomized Experiment
Zhilan Lou, Jun Shao, Yuhan Qian +4
Covariate adjustment improves estimation efficiency in randomized experiments, but standard calibration and augmentation methods, when applied to distribution or survival functions…
Robust and Data-Adaptive Integration of Nonconcurrent Data in Platform Trials via Gaussian Processes
Yuhan Qian, Yu Du, Jingning Zhang +3
A platform trial is an innovative clinical trial design that enables simultaneous and continuous evaluation of multiple treatments within a single master protocol. Existing robust…
The RobinCar Family: R Tools for Robust Covariate Adjustment in Randomized Clinical Trials
Marlena Bannick, Yuanyuan Bian, Gregory Chen +6
Purpose: Covariate adjustment is a powerful statistical technique that can increase efficiency in clinical trials. Recent guidance from the U.S. FDA provided recommendations and be…
From Estimands to Robust Inference of Treatment Effects in Master Protocol Trials
Yuhan Qian, Yifan Yi, Jun Shao +5
Master protocol trials use a single overarching protocol to evaluate multiple interventions, diseases, or disease subtypes, where individuals are often randomized to different subs…
Clarifying the Role of the Mantel-Haenszel Risk Difference Estimator in Randomized Clinical Trials
Xiaoyu Qiu, Yuhan Qian, Jaehwan Yi +4
The Mantel-Haenszel (MH) risk difference estimator, commonly used in randomized clinical trials for binary outcomes, calculates a weighted average of stratum-specific risk differen…