论文标题
G-估计器对无效仪器变量的敏感性分析
Sensitivity Analysis of G-estimators to Invalid Instrumental Variables
论文作者
论文摘要
仪器变量回归是一种在观察数据分析中常用的工具。仪器变量用于在存在未衡量的混杂因子的情况下对某个暴露的影响进行因果推断。有效的仪器变量是与暴露相关的变量，仅通过暴露（排除标准）影响结果，并且与结果（外生性）不混淆。这些假设通常是无法测试的，并且依赖于主题知识。因此，需要进行灵敏度分析，以评估违反假设对估计参数的影响。在本文中，我们提出并展示了一种新的对因果线性和非线性模型中G-静态器的敏感性分析的方法。我们在仪器变量研究中介绍了灵敏度分析的两个新方面。第一个是单个灵敏度参数，该参数捕获了排除和外生性假设的违规。第二个是该方法对非线性模型的应用。引入的框架在理论上是合理的，并通过模拟研究进行了说明。最后，我们通过应用于现实世界数据来说明该方法，并为从业者提供有关进行灵敏度分析的指南。
Instrumental variables regression is a tool that is commonly used in the analysis of observational data. The instrumental variables are used to make causal inference about the effect of a certain exposure in the presence of unmeasured confounders. A valid instrumental variable is a variable that is associated with the exposure, affects the outcome only through the exposure (exclusion criterion), and is not confounded with the outcome (exogeneity). These assumptions are generally untestable and rely on subject-matter knowledge. Therefore, a sensitivity analysis is desirable to assess the impact of assumptions violation on the estimated parameters. In this paper, we propose and demonstrate a new method of sensitivity analysis for G-estimators in causal linear and non-linear models. We introduce two novel aspects of sensitivity analysis in instrumental variables studies. The first is a single sensitivity parameter that captures violations of exclusion and exogeneity assumptions. The second is an application of the method to non-linear models. The introduced framework is theoretically justified and is illustrated via a simulation study. Finally, we illustrate the method by application to real-world data and provide practitioners with guidelines on conducting sensitivity analysis.
