Estimation of generalized partially linear models with measurement error using sufficiency scores

被引:1
|
作者
Liu, Lian [1 ]
机构
[1] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA
关键词
logistic regression; measurement error; partially linear model; semiparametric regression; sufficiency scores;
D O I
10.1016/j.spl.2007.03.039
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 the partially linear model in logistic and other types of canonical exponential family regression when the explanatory variable is measured with independent normal error. We develop a backfitting estimation procedure to this model based upon the parametric idea of sufficiency scores so that no assumptions are made about the latent variable measured with error. We derive the method's asymptotic properties and present a numerical example and a simulation study. (c) 2007 Elsevier B.V. All rights reserved.
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页码:1580 / 1588
页数:9
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