15 citations · 22 across the 15 of their papers we have counts for
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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…
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…
A General Form of Covariate Adjustment in Randomized Clinical Trials
Marlena S. Bannick, Jun Shao, Jingyi Liu +3
In randomized clinical trials, adjusting for baseline covariates can improve credibility and efficiency for demonstrating and quantifying treatment effects. This article studies th…
Robust Variance Estimation for Covariate-Adjusted Unconditional Treatment Effect in Randomized Clinical Trials with Binary Outcomes
Ting Ye, Marlena Bannick, Yanyao Yi +1
To improve precision of estimation and power of testing hypothesis for an unconditional treatment effect in randomized clinical trials with binary outcomes, researchers and regulat…
A matching design for augmenting a randomized clinical trial with external control
Jianghao Li, Yu Du, Huayu Liu +1
The use of information from real world to assess the effectiveness of medical products is becoming increasingly popular and more acceptable by regulatory agencies. According to a s…
Testing for Treatment Effect Twice Using Internal and External Controls in Clinical Trials
Yanyao Yi, Ying Zhang, Yu Du +1
Leveraging external controls -- relevant individual patient data under control from external trials or real-world data -- has the potential to reduce the cost of randomized control…
Covariate-Adjusted Log-Rank Test: Guaranteed Efficiency Gain and Universal Applicability
Ting Ye, Jun Shao, Yanyao Yi
Nonparametric covariate adjustment is considered for log-rank type tests of treatment effect with right-censored time-to-event data from clinical trials applying covariate-adaptive…
Toward Better Practice of Covariate Adjustment in Analyzing Randomized Clinical Trials
Ting Ye, Jun Shao, Yanyao Yi +1
In randomized clinical trials, adjustments for baseline covariates at both design and analysis stages are highly encouraged by regulatory agencies. A recent trend is to use a model…
Inference on Average Treatment Effect under Minimization and Other Covariate-Adaptive Randomization Methods
Ting Ye, Yanyao Yi, Jun Shao
Covariate-adaptive randomization schemes such as the minimization and stratified permuted blocks are often applied in clinical trials to balance treatment assignments across progno…