10 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…
Estimating treatment effects with competing intercurrent events in randomized controlled trials
Sizhu Lu, Yanyao Yi, Yongming Qu +3
The analysis of randomized controlled trials is often complicated by intercurrent events (IEs) -- events that occur after treatment initiation and affect either the interpretation…
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…
Improve the Precision of Area Under the Curve Estimation for Recurrent Events Through Covariate Adjustment
Jiren Sun, Tuo Wang, Yanyao Yi +3
The area under the curve (AUC) of the mean cumulative function (MCF) has recently been introduced as a novel estimand for evaluating treatment effects in recurrent event settings,…
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…