Instrument Assisted Regression for Errors in Variables Models with Binary Response

被引：10

作者：

Xu, Kun ^{[1
]}

Ma, Yanyuan ^{[1
]}

Wang, Liqun ^{[2
]}

机构：

[1] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

[2] Univ Manitoba, Dept Stat, Winnipeg, MB R3T 2N2, Canada

来源：

SCANDINAVIAN JOURNAL OF STATISTICS | 2015年 / 42卷 / 01期

基金：

加拿大自然科学与工程研究理事会; 美国国家科学基金会;

关键词：

binary response; conditional scores; consistency; errors in variables; generalized linear models; instrumental variables; logistic regression; measurement error; semiparametric efficiency; ESTIMATORS;

D O I：

10.1111/sjos.12097

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We study errors-in-variables problems when the response is binary and instrumental variables are available. We construct consistent estimators through taking advantage of the prediction relation between the unobservable variables and the instruments. The asymptotic properties of the new estimator are established and illustrated through simulation studies. We also demonstrate that the method can be readily generalized to generalized linear models and beyond. The usefulness of the method is illustrated through a real data example.

引用

页码：104 / 117

页数：14

共 20 条

[1] Instrumental variable approach to covariate measurement error in generalized linear models [J].