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Journal of Dairy Science Vol. 69 No. 10 2696-2703
© 1986 by American Dairy Science Association ®
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Sequential Estimation of Genetic and Phenotypic Parameters in Multitrait Mixed Model Analysis1

C. Y. Lin and A. J. Lee

Animal Research Centre, Agriculture Canada, Ottawa, Ontario, Canada K1A 0C6

ABSTRACT

Single-trait and multitrait (2-, 3-, 4-, and 5-trait) restricted maximum likelihood methods were applied to the same set of data with complete information on all traits. Results suggest that parameter estimates from a data set vary depending upon the type of analysis (single- or multitrait model) and upon the other traits included in multitrait analysis. The choice of parameter estimation method for a breeding design should be based on the breeding goal. In parameter estimation or sire evaluation, traits included in a multitrait analysis should correspond to the traits of interest in the breeding goal. Multitrait analysis explores all intercorrelations simultaneously in parameter estimation and thus provides a complete picture of all interrelationships among traits. In contrast, single-trait analysis produces pairwise (simple) correlations and ignores the possible contribution of other related traits under study to the pairwise correlation. The 5-trait model analysis through canonical transformation was about 300% more efficient in terms of computer time than single-trait model analysis of the same 5 traits. In this study, parameter estimates converged faster under multitrait analysis through canonical transformation than under single-trait analysis.

FOOTNOTES

1 Animal Research Centre Contribution Number 1376.






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Copyright © 1986 by the American Dairy Science Association ®.