对“协变量自适应随机化后的推理:方法论和理论方面”的评论

IF 0.7 Q3 STATISTICS & PROBABILITY
Wei Ma, Li-Xin Zhang, F. Hu
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引用次数: 0

摘要

在过去的十年中,在协变量自适应随机化下的推理方面取得了重大进展。我们感谢邵教授及时回顾了有关该主题的越来越多的文献。本文的重点是最重要和最常用的一类协变量自适应随机化方法,即那些平衡离散协变量的方法。重点讨论了鲁棒推理的最新进展。介绍了几种类型的结果,例如连续数据和时间到事件数据。在这里,我们从以下五个角度提供一些额外的最新结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comment on ‘Inference after covariate-adaptive randomisation: aspects of methodology and theory’
In the past decade, significant progress has been made regarding inference under covariate-adaptive randomisation. We thank Prof. Shao for a timely review of the growing literature about the topic. The paper is focused on the most important and commonly used class of covariate-adaptive randomisation methods, i.e., those balancing discrete covariates. The recent advances in robust inference are emphasised anddiscussed in detail. Several types of outcomes, such as continuous and time-to-event data, are covered. We here provide some additional recent results from the following five perspectives.
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来源期刊
CiteScore
0.90
自引率
20.00%
发文量
21
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