INSTRUMENTAL VARIABLE ESTIMATION IN BINARY REGRESSION MEASUREMENT ERROR MODELS
INSTRUMENTAL VARIABLE ESTIMATION IN BINARY REGRESSION MEASUREMENT ERROR MODELS
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DOI：
10.2307/2291065
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发表时间：
1995-06-01
影响因子：
3.7
通讯作者：
BUZAS, JS
中科院分区：
文献类型：
--
作者：
STEFANSKI, LA;BUZAS, JS
我们描述了二元回归测量误差模型中工具变量估计的两种方法。这些方法需要构建二元响应的近似平均模型，作为测量的预测变量、仪器和模型中任何协变量的函数。估计值是通过利用回归参数之间的关系来获得的，就像线性工具变量估计一样。在推导近似均值模型的过程中，我们获得了线性测量误差模型中工具变量估计的另一种表征。
We describe two approaches to instrumental variable estimation in binary regression measurement error models. The methods entail constructing approximate mean models for the binary response as a function of the measured predictor, the instrument, and any covariates in the model. Estimates are obtained by exploiting relationships between regression parameters, just as in linear instrumental variable estimation. In the course of deriving the approximate mean models, we obtain an alternative characterization of instrumental variable estimation in linear measurement error models.