Comparing traditional and Bayesian analyses of selection experiments in animal breeding

The mixed linear model is commonly used in animal breeding to predict or es timate the breeding values of individual animals. Breeding values are used to select animals For use in breeding subsequent generations. A traditional analysis of data under this model involves estimating the variance compone nts with restricted maximum likelihood. These estimates are then used to fi nd best linear unbiased predictors for the animal breeding values. A Bayesi an analysis of data under this model involves treating all of the parameter s, including the variance components, as random and finding the joint poste rior distribution of all of the parameters given the data. Because the sele ction decision depends on the values of the variance components, a Bayesian analysis can yield different selection outcomes than the traditional analy sis. We demonstrate both types of data analysis on data from an animal bree ding experiment and compare the resulting selections.