Considerations on measures of precision and connectedness in mixed linear models of genetic evaluation
A criterion for measuring the degree of connectedness between factors arising in linear models of genetic evaluation is derived on theoretical grounds. Under normality and in the case of 2 fixed factors (0, 0), this criterion is defined as the Kullback-Leibler distance between the joint distribution of the maximum likelihood (ML) estimators of contrasts among 0 and 0 levels respectively and the product of their marginal distributions. This measure is extended to random effects and mixed linear models. The procedure is illustrated with an example of genetic evaluation based on an animal model with phantom groups.