3 citations · 3 across the 6 of their papers we have counts for
6 papers
Bridging Balancing Weights and Augmentation in Covariate-adjusted Analyses with Time-to-Event Endpoints: Theory and Practical Recommendations
Baoshan Zhang, Yi Chen, Yu Du +1
Covariate adjustment improves the efficiency of treatment-effect analyses in randomized clinical trials, provided the adjustment targets the correct quantity. For time-to-event end…
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…
Using Targeted Maximum Likelihood Estimation to Estimate Treatment Effect with Longitudinal Continuous or Binary Data: A Systematic Evaluation of 28 Diabetes Clinical Trials
Lingjing Jiang, Michael Rosenblum, Yu Du
The primary analysis of clinical trials in diabetes therapeutic area often involves a mixed-model repeated measure (MMRM) approach to estimate the average treatment effect for long…
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…
Improving the mixed model for repeated measures to robustly increase precision in randomized trials
Bingkai Wang, Yu Du
In randomized trials, repeated measures of the outcome are routinely collected. The mixed model for repeated measures (MMRM) leverages the information from these repeated outcome m…