Open Access
October 2020 Generalized partially linear single index model with measurement error, instruments and binary response
Guangren Yang, Qianqian Wang, Xia Cui, Yanyuan Ma
Braz. J. Probab. Stat. 34(4): 770-794 (October 2020). DOI: 10.1214/19-BJPS463

Abstract

Partially linear generalized single index models are widely used and have attracted much attention in the literature. However, when the covariates are subject to measurement error, the problem is much less studied. On the other hand, instrumental variables are important elements in studying many errors-in-variables problems. We use the relation between the unobservable variables and the instruments to devise consistent estimators for partially linear generalized single index models with binary response. We establish the consistency, asymptotic normality of the estimator and illustrate the numerical performance of the method through simulation studies and a data example. Despite the connection to (Scand. J. Statist. 42 (2015) 104–117) in its general layout, the mathematical derivations are much more challenging in the context studied here.

Citation

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Guangren Yang. Qianqian Wang. Xia Cui. Yanyuan Ma. "Generalized partially linear single index model with measurement error, instruments and binary response." Braz. J. Probab. Stat. 34 (4) 770 - 794, October 2020. https://doi.org/10.1214/19-BJPS463

Information

Received: 1 August 2018; Accepted: 1 October 2019; Published: October 2020
First available in Project Euclid: 25 September 2020

MathSciNet: MR4153641
Digital Object Identifier: 10.1214/19-BJPS463

Keywords: errors in variables , generalized linear models , instrumental variables , Measurement errors , partially linear models , single index models

Rights: Copyright © 2020 Brazilian Statistical Association

Vol.34 • No. 4 • October 2020
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