Two robust tools for inference about causal effects with invalid instruments
Two robust tools for inference about causal effects with invalid instruments
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DOI：
10.1111/biom.13415
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发表时间：
2020-12-17
期刊：
影响因子：
1.9
通讯作者：
Small, Dylan S.
中科院分区：
文献类型：
--
作者：
Kang, Hyunseung;Lee, Youjin;Small, Dylan S.
工具变量已被广泛用于估计治疗对结果的因果影响。基于工具变量的因果效应的现有置信区间假设所有假定的工具变量都是有效的;有效的工具变量是仅通过影响治疗而影响结局的变量，与未测量的混杂因素无关。然而，在实践中，一些假定的工具变量可能是无效的。本文提出了两种工具进行有效的推理和测试，在存在无效的仪器。首先，我们提出了一个简单而通用的方法来构造置信区间的基础上采取工会的知名的置信区间。其次，我们提出了一种新的测试的零因果效应的基础上对撞机偏见。我们的两个建议优于传统的工具变量置信区间时，无效的工具，也可以用作敏感性分析时，有担心工具变量的假设被违反。新方法适用于孟德尔随机化研究的因果关系，低密度脂蛋白对球蛋白水平。
Instrumental variables have been widely used to estimate the causal effect of a treatment on an outcome. Existing confidence intervals for causal effects based on instrumental variables assume that all of the putative instrumental variables are valid; a valid instrumental variable is a variable that affects the outcome only by affecting the treatment and is not related to unmeasured confounders. However, in practice, some of the putative instrumental variables are likely to be invalid. This paper presents two tools to conduct valid inference and tests in the presence of invalid instruments. First, we propose a simple and general approach to construct confidence intervals based on taking unions of well-known confidence intervals. Second, we propose a novel test for the null causal effect based on a collider bias. Our two proposals outperform traditional instrumental variable confidence intervals when invalid instruments are present and can also be used as a sensitivity analysis when there is concern that instrumental variables assumptions are violated. The new approach is applied to a Mendelian randomization study on the causal effect of low-density lipoprotein on globulin levels.