Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: A marginal quasi-likelihood approach to the analysis of Poisson variables with generalized linear mixed models | 101 Genet Sei Evol 1993 25 101-107 Elsevier INRA Note A marginal quasi-likelihood approach to the analysis of Poisson variables with generalized linear mixed models JL Foulley s Im2 1 INRA Institut National de la Recherche Agronomique Station de Génétique Quantitative et Appliquée 78352 Jouy-en-Josas Cedex 2 INRA Station de Biométrie et d Intelligence Artificielle 31326 Castanet Tolosan Cedex France Received 19 June 1992 accepted 16 November 1992 Summary - This paper extends to Poisson variables the approach of Gilmour Anderson and Rae 1985 for estimating fixed effects by maximum quasi-likelihood in the analysis of threshold discrete data with a generalized linear mixed model. discrete variable I Poisson distribution generalized linear mixed model quasilikelihood Resume - Une approche de quasi-vraisemblance pour 1 analyse de variables de Poisson en modèle linéaire mixte generalise. Cet article generalise à des variables de Poisson I approche de Gilmour Anderson et Rae 1985 destinée à I estimation par maximum de quasi-vraisemblance des effets fixes lors de I analyse de variables discretes à seuils sous un modèle mixte. variables discrètes distribution de Poisson modèle linéaire mixte généralisé INTRODUCTION As shown by Ducrocq 1990 there has been recently some interest in non linear statistical procedures of genetic evaluation. Examples of such modelling procedures involve the threshold liability model for categorical data Gianola and Foulley 1983 Harville and Mee 1984 and for ranking data in competitions Tavernier Correspondence and reprints 102 JL Foulley s Im 1991 2 Cox s proportional hazard model for survival data Ducrocq et al 1988 and 3 a Poisson model for reproductive traits Foulley et al 1987 In FGI estimation of fixed P and random u effects involved in the model is based on the mode of the joint posterior distribution of those parameters. As discussed by Foulley and Manfredi 1991 this procedure is likely to have some drawbacks regarding estimation of fixed
