Bespoke Instruments: A new tool for addressing unmeasured confounders.
Bespoke Instruments: A new tool for addressing unmeasured confounders.
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定制仪器：解决无法测量的混杂因素的新工具。
DOI：
10.1093/aje/kwab288
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发表时间：
2022
影响因子：
5
通讯作者：
TchetgenTchetgen,EricJ
中科院分区：
文献类型：
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作者：
Richardson,DavidB;TchetgenTchetgen,EricJ
假设研究者对量化暴露-疾病因果关系感兴趣，在此环境中，暴露、疾病和相关的一些潜在混杂因素已经被测量过。然而，仍然存在对未测量混杂因素的残留混杂的关注。我们提出了一种方法来解释由于未测量混杂因素造成的残留偏倚。所提出的方法使用一个测量的混杂因素来得出一个“定制的”工具变量，该变量是为研究人群量身定制的，用于控制由残留混杂因素引起的偏差。该方法可以为评估和解释残留混淆引起的偏差提供有用的工具。我们提供了一个正式的描述，以确定因果关系的条件，说明使用模拟的方法，并提供了一个关于日本原子弹幸存者死亡率的经验例子。
Suppose that an investigator is interested in quantifying an exposure-disease causal association in a setting where the exposure, disease, and some potential confounders of the association of interest have been measured. However, there remains concern about residual confounding of the association of interest by unmeasured confounders. We propose an approach to account for residual bias due to unmeasured confounders. The proposed approach uses a measured confounder to derive a “bespoke” instrumental variable that is tailored to the study population and is used to control for bias due to residual confounding. The approach may provide a useful tool for assessing and accounting for bias due to residual confounding. We provide a formal description of the conditions for identification of causal effects, illustrate the method using simulations, and provide an empirical example concerning mortality among Japanese atomic bomb survivors.