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Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators

机译:消除两级工具变量估算中的幸存者偏差

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摘要

Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.
机译:孟德利安随机化研究通常关注老年人口。这使得这些研究对幸存者偏置敏感的仪器变量分析,一种选择偏差。特别令人担忧的是,即使在源人群对源人口有效时,仪器变化条件也可能被侵犯,以便在研究开始生存的人群中。这可能非常损害,因为已知孟德利安随机化研究由于甚至缺乏仪器变量条件而导致的偏差敏感。有趣的是,当仪器和未测量的混淆对暴露产生添加剂影响时,乐器变量条件继续持有仍然活着的某些风险集中的人类仍然存在于给定年龄的人中,而且,暴露和未测量的混乱对危害产生添加剂影响死亡。在本文中,我们将利用此属性来得出两级仪器变量估算,用于暴露于死亡率的影响,这与在这些添加性假设下的上述选择偏压下绝缘。

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