A review of instrumental variables estimation of treatment effects in the applied health sciences

被引：25

作者：

Grootendorst P. ^{[1
,2
]}

机构：

[1] Faculty of Pharmacy, University of Toronto, Toronto, ON M5S 3M2

[2] Department of Economics, McMaster University, Hamilton, ON

来源：

Health Services and Outcomes Research Methodology | 2007年 / 7卷 / 3-4期

关键词：

Health outcomes; Instrumental variables; Observational data; Treatment effects;

D O I：

10.1007/s10742-007-0023-6

中图分类号：

学科分类号：

摘要：

Health scientists often use observational data to estimate treatment effects when controlled experiments are not feasible. A limitation of observational research is non-random selection of subjects into different treatments, potentially leading to selection bias. The two commonly used solutions to this problem-covariate adjustment and fully parametric models-are limited by strong and untestable assumptions. Instrumental variables (IV) estimation can be a viable alternative. In this paper, I review examples of the application of IV in the health sciences, I show how the IV estimator works, I discuss the factors that affect its performance, I review how the interpretation of the IV estimator changes when treatment effects vary by individual, and consider the application of IV to nonlinear models. © Springer Science+Business Media, LLC 2007.

引用

页码：159 / 179

页数：20

共 25 条

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