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Estimation in Linear Models with Random Effects and Errors-in-Variables

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Abstract

The independent variables of linear mixed models are subject to measurement errors in practice. In this paper, we present a unified method for the estimation in linear mixed models with errors-in-variables, based upon the corrected score function of Nakamura (1990, Biometrika, 77, 127–137). Asymptotic normality properties of the estimators are obtained. The estimators are shown to be consistent and convergent at the order of n −1/2. The performance of the proposed method is studied via simulation and the analysis of a data set on hedonic housing prices.

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Zhong, XP., Fung, WK. & Wei, BC. Estimation in Linear Models with Random Effects and Errors-in-Variables. Annals of the Institute of Statistical Mathematics 54, 595–606 (2002). https://doi.org/10.1023/A:1022467212133

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