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…
-DPO: Direct Preference Optimization via Ratio Reward Margin
Zhengyuan Fan, Zhonghua Wu, Yuxuan Du +1
Reference-free preference optimization has emerged as an efficient alternative to reinforcement learning from human feedback, with Simple Preference Optimization(SimPO) demonstrati…
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…