AISM 54, 595-606
© 2002 ISM

Estimation in linear models with random effects and errors-in-variables

Xu-Ping Zhong1, Wing-Kam Fung2 and Bo-Cheng Wei1

1Department of Mathematics, Southeast University, Nanjing 210018, China, e-mail:
2Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong, China, e-mail:

(Received July 18, 2000; revised March 29, 2001)

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.

Key words and phrases:    Corrected score function, errors-in-variable, fixed effects, random effects, measurement errors.

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