A revisit to the application of weighted mixed regression estimation in linear models with missing data

A revisit to the application of weighted mixed regression estimation in linear models with missing data

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Article ID: iaor2004873
Country: United States
Volume: 22
Issue: 3/4
Start Page Number: 281
End Page Number: 301
Publication Date: Jan 2002
Journal: American Journal of Mathematical and Management Sciences
Authors: ,
Abstract:

This paper deals with the application of the weighted mixed regression estimation of the coefficients in a linear model when some values of some of the regressors are missing. Taking the weight factor as an arbitrary scalar, the performance of weighted mixed regression estimator in relation to the conventional least squares and mixed regression estimators is analyzed and the choice of scalar is discussed. Then taking the weight factor as a specific matrix, a family of estimators is proposed and its performance properties under the criteria of bias vector and mean squared error matrix are analyzed.

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