Multi-arm covariate-adaptive randomization

被引:0
作者
Feifang Hu
Xiaoqing Ye
Li-Xin Zhang
机构
[1] The George Washington University,Department of Statistics
[2] Renmin University of China,Institute of Statistics and Big Data
[3] Zhejiang University,School of Mathematical Sciences
来源
Science China Mathematics | 2023年 / 66卷
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; 60F05; 60F10; 60F15; 62G10;
D O I
暂无
中图分类号
学科分类号
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 covariate-adaptive randomization procedures.
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页码:163 / 190
页数:27
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