Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/244436 
Year of Publication: 
2007
Series/Report no.: 
Working Paper No. 14/2007
Publisher: 
Örebro University School of Business, Örebro
Abstract: 
In this paper we discuss how a regression model, with a non-continuous response variable, that allows for dependency between observations should be estimated when observations are clustered and there are repeated measurements on the subjects. The cluster sizes are assumed to be large. We …nd that the conventional estimation technique suggested by the literature on Generalized Linear Mixed Models (GLMM) is slow and often fails due to non-convergence and lack of memory on standard PCs. We suggest to estimate the random e¤ects as …xed e¤ects by GLM and derive the covariance matrix from these estimates. A simulation study shows that our proposal is feasible in terms of Mean-Square Error and computation time. We recommend that our proposal be implemented in the software of GLMM techniques so that the estimation procedure can switch between the conventional technique and our proposal depending on the size of the clusters.
Subjects: 
Monte-Carlo simulations
large sample
interdependence
cluster error
JEL: 
C13
C15
C25
C63
Document Type: 
Working Paper

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