题目： A multi-stage design for optimizing treatment assignment in randomized clinical trials

报告人：张维副研究员（中国科学院数学与系统科学）

摘要：The treatment assignment mechanism in a randomized clinical trial can be optimized for statistical efficiency within a specified class of randomization mechanisms. Optimal designs of this type have been characterized in terms of the variances of potential outcomes conditional on baseline covariates. Approximating these optimal designs requires information about the conditional variance functions, which is often unavailable or unreliable at the design stage. As a practical solution to this dilemma, we propose a multi-stage adaptive design that allows the treatment assignment mechanism to be modified at interim analyses based on accruing information about the conditional variance functions. This adaptation has profound implications on the distribution of trial data, which need to be accounted for in treatment effect estimation. We consider a class of treatment effect estimators that are consistent and asymptotically normal, identify the most efficient estimator within this class, and approximate the most efficient estimator by substituting estimates of unknown quantities. Simulation results indicate that, when there is little or no prior information available, the proposed design can bring substantial efficiency gains over conventional one-stage designs based on the same prior information. The methodology is illustrated with real data from a completed trial in stroke.

报告人简介：张维，中国科学院数学与系统科学研究院副研究员。2016博士毕业于中国科学院数学与系统科学研究院，2016-2017年在美国耶鲁大学和2017-2020年在美国国家卫生研究院从事博士后研究。研究方向包括临床试验、诊断医学、分组检测及遗传关联分析中的统计理论、方法和应用。发表SCI论文40余篇，ESI高被引论文1篇。

报告时间：2024年12月17日（周二）上午9:30-10:30

报告地点：腾讯会议396212288

联系人：胡涛