Instrumental Variable Estimation in Generalized Linear Measurement Error Models
研究了广义线性测量误差模型中的工具变量估计，推导了典范链接函数下的无偏估计方程，并以逻辑回归为例，结合弗拉明汉心脏研究数据进行了模拟分析。
Abstract Instrumental variable estimation in generalized linear measurement error models are studied. For models with canonical link functions, unbiased estimating equations are derived. The maximum likelihood estimator for the normal theory, structural linear instrumental variable model is shown to be a solution to the estimating equations derived herein. Logistic regression is studied in detail. An example is given and a simulation study described for the logistic model based on the Framingham Heart Study data.