Instrumental Variable Estimators for Binary Outcomes
Instrumental Variable Estimators for Binary Outcomes
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DOI：
10.1080/01621459.2012.734171
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发表时间：
2012-12-01
影响因子：
3.7
通讯作者：
Windmeijer, Frank
中科院分区：
文献类型：
--
作者：
Clarke, Paul S.;Windmeijer, Frank
工具变量（IV）可用于构建暴露效应的估计量的研究结果的影响，不可替代的选择的暴露。未能调整不可重复选择效应的估计量将是有偏的和不一致的。这种情况通常出现在观察性研究中，但也是一个问题，随机实验受不可解释的不遵守。在这篇文章中，我们回顾了IV估计的研究，其中的结果是二进制的，并考虑在统计和计量经济学文献中开发的不同方法之间的联系。在我们的框架内突出显示和比较每种方法所做的隐含假设。我们通过对一项随机安慰剂对照试验的重新分析来说明我们的发现，并强调了这一领域未来工作的重要方向。
Instrumental variables (IVs) can be used to construct estimators of exposure effects on the outcomes of studies affected by nonignorable selection of the exposure. Estimators that fail to adjust for the effects of nonignorable selection will be biased and inconsistent. Such situations commonly arise in observational studies, but are also a problem for randomized experiments affected by nonignorable noncompliance. In this article, we review IV estimators for studies in which the outcome is binary, and consider the links between different approaches developed in the statistics and econometrics literatures. The implicit assumptions made by each method are highlighted and compared within our framework. We illustrate our findings through the reanalysis of a randomized placebo-controlled trial, and highlight important directions for future work in this area.