%0 Generic
%J Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, 13-18 August, 2006
%D 2006
%T Joint quantitative genetic analysis of survival, linear Gaussian and ordered categorical traits.
%A Damgaard, L. H.
%K animals
%K Artiodactyla
%K Bayesian theory
%K Bos
%K Bovidae
%K calving
%K cattle
%K Chordata
%K culling
%K dairy cattle
%K Danish Landrace
%K eukaryotes
%K genetic analysis
%K genetic correlation
%K genetic effects
%K genotype environment interaction
%K hazards
%K longevity
%K mammals
%K pigs
%K quantitative genetics
%K reproduction
%K risk analysis
%K ruminants
%K sows
%K statistical analysis
%K Suidae
%K Suiformes
%K survival
%K Sus
%K Sus scrofa
%K ungulates
%K vertebrates
%X In this paper we consider two extensions of the proportional hazards model for survival data. (i) A semiparametric proportional hazards model that allow for time varying genetic effects are developed under the Bayesian framework and fitted to longevity records of Danish Landrace sows. The results provide evidence that the additive gene action controlling the risk of culling varies over the reproductive cycle of sows. (ii) A joint quantitative genetic Bayesian model for a survival, a linear Gaussian and an ordered categorical trait that allow for both additive genetic and environment correlations are derived. The approach is illustrated in a bivariate analysis of longevity and calving difficulty of dairy cows. The two traits were found to be genetically favourable correlated (0.37).
%B Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, 13-18 August, 2006
%P 26.06
%G eng