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On the Accuracy of Efficiency of Estimating Equation Approach
Author(s) -
Sutradhar Brajendra C.,
Das Kalyan
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.00622.x
Subject(s) - mathematics , covariate , estimator , generalized estimating equation , statistics , regression analysis , estimating equations , regression , econometrics , linear regression
Summary. Liang and Zeger (1986, Biometrika 73 , 13–22) introduced a generalized estimating equation (GEE) approach based on a working correlation matrix to obtain efficient estimators of regression parameters in the class of generalized linear models for repeated measures data. As demonstrated by Crowder (1995, Biometrika 82 , 407–410), because of uncertainty of the definition of the working correlation matrix, the Liang‐Zeger approach may, in some cases, lead to a complete breakdown of the estimation of the regression parameters. After taking this comment of Crowder into account, recently Sutradhar and Das (1999, Biometrika 86 , 459–465) examined the loss of efficiency of the regression estimators due to misspecification of the correlation structures. But their study was confined to the regression estimation with cluster‐level covariates, as in the original paper of Liang and Zeger. In this paper, we study this efficiency loss problem for the generalized regression models with within‐cluster covariates by utilizing the approach of Sutsadhar and Das (1999).