Multi-arm covariate-adaptive randomization  

作　　者：Feifang Hu Xiaoqing Ye Li-Xin Zhang 

机构地区：[1]Department of Statistics,The George Washington University,Washington,DC 20052,USA [2]Institute of Statistics and Big Data,Renmin University of China,Beijing 100872,China [3]School of Mathematical Sciences,Zhejiang University,Hangzhou 310058,China

出　　处：《Science China Mathematics》2023年第1期163-190,共28页中国科学：数学（英文版）

基　　金：supported by the National Key R&D Program of China (Grant No.2018YFC2000302);National Natural Science Foundation of China (Grant Nos.11731012,11731011 and 12031005);Ten Thousands Talents Plan of Zhejiang Province (Grant No.2018R52042);the Fundamental Research Funds for the Central Universities。

摘　　要：Simultaneously investigating multiple treatments in a single study achieves considerable efficiency in contrast to the traditional two-arm trials.Balancing treatment allocation for influential covariates has become increasingly important in today’s clinical trials.The multi-arm covariate-adaptive randomized clinical trial is one of the most powerful tools to incorporate covariate information and multiple treatments in a single study.Pocock and Simon’s procedure has been extended to the multi-arm case.However,the theoretical properties of multi-arm covariate-adaptive randomization have remained largely elusive for decades.In this paper,we propose a general framework for multi-arm covariate-adaptive designs which also includes the two-arm case,and establish the corresponding theory under widely satisfied conditions.The theoretical results provide new insights into the balance properties of covariate-adaptive randomization procedures and make foundations for most existing statistical inferences under two-arm covariate-adaptive randomization.Furthermore,these open a door to study the theoretical properties of statistical inferences for clinical trials based on multi-arm covariateadaptive randomization procedures.

关 键 词：multiple treatment balancing covariate clinical trial marginal balance Markov chain Hu and Hu’s general procedure Pocock and Simon’s procedure stratified permuted block design 

分 类 号：O211.6[理学—概率论与数理统计]