Instrumental Variables in Sociology and the Social Sciences
Instrumental Variables in Sociology and the Social Sciences
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DOI：
10.1146/annurev-soc-081309-150141
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发表时间：
2012-01-01
期刊：
影响因子：
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通讯作者：
Bollen, Kenneth A.
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文献类型：
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作者：
Bollen, Kenneth A.
工具变量（IV）方法提供了一个强大的，但未充分利用的工具，以解决许多常见的问题与观察社会学数据。其成功使用的关键是具有与方程的扰动不相关并且与有问题的内源协变量足够强相关的IV。本文简要介绍了IV的定义，总结了它们的起源，并介绍了它们在多元回归，联立方程模型，因子分析，潜变量结构方程模型和有限因变量模型中的应用。定义并比较了三种选择IV的方法：辅助工具变量、模型隐含工具变量和随机工具变量。它提供了过度识别测试和弱IV诊断作为评估IV质量的方法。我回顾使用IV模型，假设异质因果效应。另一部分总结了当代社会学出版物中IV的使用情况。结论提出了改进静脉注射使用的方法，并表明静脉注射在社会学研究中可以在许多领域得到有益的应用。
Instrumental variable (IV) methods provide a powerful but underutilized tool to address many common problems with observational sociological data. Key to their successful use is having IVs that are uncorrelated with an equation's disturbance and that are sufficiently strongly related to the problematic endogenous covariates. This review briefly defines IVs, summarizes their origins, and describes their use in multiple regression, simultaneous equation models, factor analysis, latent variable structural equation models, and limited dependent variable models. It defines and contrasts three methods of selecting IVs: auxiliary instrumental variable, model implied instrumental variable, and randomized instrumental variable. It provides overidentification tests and weak IV diagnostics as methods to evaluate the quality of IVs. I review the use of IVs in models that assume heterogeneous causal effects. Another section summarizes the use of IVs in contemporary sociological publications. The conclusion suggests ways to improve the use of IVs and suggests that there are many areas in which IVs could be profitably used in sociological research.