6 papers · 1 filter
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…
Evolving Longitudinal Patient Histories and Re-enrollment in Master Protocol Trials
Shiyu Wan, Yuhan Qian, Yanyao Yi +3
A master protocol trial uses a single overarching protocol to test multiple therapies, often across several diseases or subtypes. Although such trials offer considerable flexibilit…
Proximal Learning for Trials With External Controls: A Case Study in HIV Prevention
Yilin Song, Yinxiang Wu, Raphael J. Landovitz +9
With the advent of effective pre-exposure prophylaxis agents, active-controlled HIV prevention trials have become a common study design. Nevertheless, estimating absolute efficacy…
Covariate Adjustment for Wilcoxon Two Sample Statistic and Test
Zhilan Lou, Jun Shao, Ting Ye +3
We apply covariate adjustment to the Wincoxon two sample statistic and Wincoxon-Mann-Whitney test in comparing two treatments. The covariate adjustment through calibration not only…
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…