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
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.
Type de document :
Rapport
RR-3522, INRIA. 1998
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https://hal.inria.fr/inria-00073162
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Soumis le : mercredi 24 mai 2006 - 12:01:51
Dernière modification le : jeudi 28 juin 2018 - 14:36:44
Document(s) archivé(s) le : dimanche 4 avril 2010 - 23:36:31

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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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