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A Quasi-Score Marginal Approach in Generalized Linear Mixed Models

Catherine Trottier 1
1 IS2 - Statistical Inference for Industry and Health
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : This report deals with the problem of parameter estimation in generalized linear mixed models. Gilmour, Anderson, et Rae (1985) proposed a method of estimation in a probit link model for binomial data. Foulley et Im (1993) adapted this method to Poisson data in a log link model. We propose a unifying formal description including also the case of exponentia- l data in a log link model. This approach enables us to consider other cases such as logit link model for binomial data. Numerical examples are given to illustrate the method.
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https://hal.inria.fr/inria-00073162
Contributor : Rapport de Recherche Inria <>
Submitted on : Wednesday, May 24, 2006 - 12:01:51 PM
Last modification on : Monday, February 10, 2020 - 4:36:45 PM
Long-term archiving on: : Sunday, April 4, 2010 - 11:36:31 PM

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  • HAL Id : inria-00073162, version 1

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Catherine Trottier. A Quasi-Score Marginal Approach in Generalized Linear Mixed Models. RR-3522, INRIA. 1998. ⟨inria-00073162⟩

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