tailieunhanh - báo cáo khoa học: "Genetic evaluation for Ina multiple binary response"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Genetic evaluation for Ina multiple binary response | Génét. Sél. Evol. 1986 18 3 299-320 299 Genetic evaluation for multiple binary responses Ina HÔSCHELE . FOULLEY . COLLEAU and D. GIANOLA University Hohenheim Institut 470 Haustiergenetik D 7000 Stuttgart 70 . Station de Génétique Quantitative et Appliquée Centre de Recherches Zootechniques F 78350 Jouy-en-Josas Department of Animal Sciences University of Illinois Urbana Illinois 61801 . Summary A method of genetic evaluation for multiple binary responses is presented. An underlying multivariate normal distribution is rendered discrete in m dimensions via a set of m fixed thresholds. There are 2m categories of response and the probability of response in a given category is modeled with an m-dimensional multivariate normal integral. The argument of this integral follows a multivariate mixed linear model. The randomness of some elements in the model is taken into account using a Bayesian argument. Assuming that the variance-covariance structure is known the mode of the joint posterior distribution of the fixed and random effects is taken as a point estimator. The problem is non-linear and iteration is required. The resulting equations indicate that the approach falls in the class of generalized linear models with additional generalization stemming from the accommodation of random effects. A remarkable similarity with multiple trait evaluation via mixed linear models is observed. Important numerical issues arise in the implementation of the procedure and these are discussed in detail. An application of the method to data on calving preparation calving difficulties and calf viability is presented. Key words Multiple trait evaluation all-or-none responses Bayesian methods. Résumé Estimation de la valeur génétique à partir de réponses binaires multidimensionnelles Cet article présente une méthode d evaluation génétique multidimensionnelle de caractères binaires. La distribution multinormale sous-jacente est discrétisée en m dimensions par le biais de m .