Arbeitspapier
Computationally feasible estimation of the covariance structure in Generalized linear mixed models(GLMM)
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.
- Language
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Englisch
- Bibliographic citation
-
Series: Working Paper ; No. 14/2007
- Classification
-
Wirtschaft
Estimation: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
Computational Techniques; Simulation Modeling
- Subject
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Monte-Carlo simulations
large sample
interdependence
cluster error
- Event
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Geistige Schöpfung
- (who)
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Carling, Kenneth
Alam, Moudud
- Event
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Veröffentlichung
- (who)
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Örebro University School of Business
- (where)
-
Örebro
- (when)
-
2007
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
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Object type
- Arbeitspapier
Associated
- Carling, Kenneth
- Alam, Moudud
- Örebro University School of Business
Time of origin
- 2007
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