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对Chen和Heitjan所著《不完全依从性临床试验中估计量的敏感性》的评论

Comments on "sensitivity of estimands in clinical trials with imperfect compliance" by Chen and Heitjan.

作者信息

Baker Stuart G, Lindeman Karen S

机构信息

National Cancer Institute, Bethesda, MD, 20892-9789, USA.

Department of Anesthesiology, Johns Hopkins Medical Institutions, Baltimore, USA.

出版信息

Int J Biostat. 2024 Jul 29;20(2):435-436. doi: 10.1515/ijb-2023-0127. eCollection 2024 Nov 1.

Abstract

Chen and Heitjan (Sensitivity of estimands in clinical trials with imperfect compliance. Int J Biostat. 2023) used linear extrapolation to estimate the population average causal effect (PACE) from the complier average causal effect (CACE) in multiple randomized trials with all-or-none compliance. For extrapolating from CACE to PACE in this setting and in the paired availability design involving different availabilities of treatment among before-and-after studies, we recommend the sensitivity analysis in Baker and Lindeman (J Causal Inference, 2013) because it is not restricted to a linear model, as it involves various random effect and trend models.

摘要

陈和海特扬(《不完全依从性临床试验中估计量的敏感性。国际生物统计学杂志》,2023年)在多项全有或全无依从性的随机试验中,使用线性外推法从依从者平均因果效应(CACE)估计总体平均因果效应(PACE)。对于在此情形下以及在前后研究中涉及不同治疗可及性的配对可及性设计中从CACE外推到PACE,我们推荐贝克和林德曼(《因果推断杂志》,2013年)中的敏感性分析,因为它不限于线性模型,它涉及各种随机效应和趋势模型。

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