Product versus additive threshold models for analysis of reproduction outcomes in animal genetics1
Open Access
- 1 August 2009
- journal article
- research article
- Published by Oxford University Press (OUP) in Journal of Animal Science
- Vol. 87 (8) , 2510-2518
Abstract
The phenotypic observation of some reproduction traits (e.g., insemination success, interval from lambing to insemination) is the result of environmental and genetic factors acting on 2 individuals: the male and female involved in a mating couple. In animal genetics, the main approach (called additive model) proposed for studying such traits assumes that the phenotype is linked to a purely additive combination, either on the observed scale for continuous traits or on some underlying scale for discrete traits, of environmental and genetic effects affecting the 2 individuals. Statistical models proposed for studying human fecundability generally consider reproduction outcomes as the product of hypothetical unobservable variables. Taking inspiration from these works, we propose a model (product threshold model) for studying a binary reproduction trait that supposes that the observed phenotype is the product of 2 unobserved phenotypes, 1 for each individual. We developed a Gibbs sampling algorithm for fitting a Bayesian product threshold model including additive genetic effects and showed by simulation that it is feasible and that it provides good estimates of the parameters. We showed that fitting an additive threshold model to data that are simulated under a product threshold model provides biased estimates, especially for individuals with high breeding values. A main advantage of the product threshold model is that, in contrast to the additive model, it provides distinct estimates of fixed effects affecting each of the 2 unobserved phenotypes. Copyright © 2009. .Keywords
This publication has 20 references indexed in Scilit:
- Multilevel Selection 1: Quantitative Genetics of Inheritance and Response to SelectionGenetics, 2007
- Associations between genetic merit for milk production and animal parameters and the fertility performance of dairy cowsAnimal, 2007
- A hierarchical Bayesian approach to modeling embryo implantation following in vitro fertilizationBiostatistics, 2002
- Models to estimate maternal effects for juvenile body weight in broiler chickensGenetics Selection Evolution, 1997
- On biased inferences about variance components in the binary threshold modelGenetics Selection Evolution, 1997
- Estimation of variance components of threshold characters by marginal posterior modes and means via Gibbs samplingGenetics Selection Evolution, 1995
- Bayesian inference in threshold models using Gibbs samplingGenetics Selection Evolution, 1995
- The analysis of binomial data by a generalized linear mixed modelBiometrika, 1985
- A Mixed-Model Procedure for Analyzing Ordered Categorical Data1984
- The Covariance between Relatives for Characters Composed of Components Contributed by Related IndividualsBiometrics, 1963