Doubly Robust Estimation of Causal Effects
Doubly Robust Estimation of Causal Effects
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DOI：
10.1093/aje/kwq439
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发表时间：
2011-04-01
影响因子：
5
通讯作者：
Davidian, Marie
中科院分区：
文献类型：
--
作者：
Funk, Michele Jonsson;Westreich, Daniel;Davidian, Marie
双重稳健估计将一种形式的结果回归与暴露模型相结合（即，倾向分数）来估计暴露对结果的因果影响。当单独用于估计因果效应时，结果回归和倾向评分方法只有在正确指定统计模型时才是无偏的。双重稳健估计量结合了这两种方法，使得仅需要正确指定2个模型中的1个来获得无偏效应估计量。在这个介绍双重稳健估计，作者提出了一个概念性的概述双重稳健估计，一个简单的工作例子，结果从模拟研究的估计和自举标准误差的性能，并讨论了这种方法的潜在优势和局限性。这篇论文的补充材料张贴在《日刊》的网站上（http：//aje.oupjournals.org/），包括双重鲁棒性的演示（网络附录1）和SAS宏的描述（SAS Institute，Inc.，卡里，北卡罗来纳州）进行双稳健估计，可从http://www.unc.edu/similar下载到mfunk/dr/。
Doubly robust estimation combines a form of outcome regression with a model for the exposure (i.e., the propensity score) to estimate the causal effect of an exposure on an outcome. When used individually to estimate a causal effect, both outcome regression and propensity score methods are unbiased only if the statistical model is correctly specified. The doubly robust estimator combines these 2 approaches such that only 1 of the 2 models need be correctly specified to obtain an unbiased effect estimator. In this introduction to doubly robust estimators, the authors present a conceptual overview of doubly robust estimation, a simple worked example, results from a simulation study examining performance of estimated and bootstrapped standard errors, and a discussion of the potential advantages and limitations of this method. The supplementary material for this paper, which is posted on the Journal's Web site (http://aje.oupjournals.org/), includes a demonstration of the doubly robust property (Web Appendix 1) and a description of a SAS macro (SAS Institute, Inc., Cary, North Carolina) for doubly robust estimation, available for download at http://www.unc.edu/similar to mfunk/dr/.