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Instrumental variable approach to covariate measurement error in generalized linear models

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Abstract

The paper presents the method of moments estimation for generalized linear measurement error models using the instrumental variable approach. The measurement error has a parametric distribution that is not necessarily normal, while the distributions of the unobserved covariates are nonparametric. We also propose simulation-based estimators for the situation where the closed forms of the moments are not available. The proposed estimators are strongly consistent and asymptotically normally distributed under some regularity conditions. Finite sample performances of the estimators are investigated through simulation studies.

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Authors and Affiliations

  1. Department of Statistics, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada

    Taraneh Abarin & Liqun Wang

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  1. Taraneh Abarin
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  2. Liqun Wang
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Correspondence to Liqun Wang.

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Abarin, T., Wang, L. Instrumental variable approach to covariate measurement error in generalized linear models. Ann Inst Stat Math 64, 475–493 (2012). https://doi.org/10.1007/s10463-010-0319-0

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  • DOI: https://doi.org/10.1007/s10463-010-0319-0

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