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观察性研究中的估计目标:ICH E9(R1)之外的一些考虑因素。

Estimands in observational studies: Some considerations beyond ICH E9 (R1).

机构信息

Division of Biostatistics, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.

Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.

出版信息

Pharm Stat. 2022 Sep;21(5):835-844. doi: 10.1002/pst.2196. Epub 2022 Feb 6.

Abstract

The document ICH E9 (R1) has brought much attention to the concept of estimand in the clinical trials community. ICH stands for International Conference for Harmonization. In this article, we draw attention to one facet of estimand that is not discussed in that document but is crucial in the context of observational studies, namely weighting for covariate balance. How weighting schemes are connected to estimand, or more specifically to one of its five attributes identified in ICH E9 (R1), the attribute of population, is illustrated using the Rubin Causal Model. Three estimands are examined from both theoretical and practical perspectives. Factors that may be considered in choosing among these estimands are discussed.

摘要

ICH E9(R1) 文档引起了临床试验界对估计目标概念的关注。ICH 是国际协调会议的缩写。本文提请关注该文档未讨论但在观察性研究中至关重要的估计目标的一个方面,即协变量平衡的加权。使用 Rubin 因果模型说明了加权方案如何与估计目标相关联,或者更具体地说,与 ICH E9(R1) 中确定的其五个属性之一,即人群属性相关联。从理论和实践两个角度检查了三个估计目标。讨论了在这些估计目标中进行选择时可能考虑的因素。

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