Comparison of Multitrait and Single-Trait Multiple Parity Evaluations by Monte Carlo Simulation

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Abstract
Three methods of analysis: 1) multi- parity analysis with the first three parities analyzed as correlated traits, 2)multi- parity analysis with all lactations analyzed as a single trait, and 3) first parity only analysis were compared on simulated data. A selection index was used to compute multiparity evaluations from the separate parity evaluations of the multi- trait analyses. Twenty simulated popula- tions, each of 8,500 cows, were generated by an algorithm that approximated the multitrait model. Populations were sim- ulated with both random and yield-based culling of cows after first and second parity. Populations simulated with yield- based culling were analyzed both with the first parity records of all cows included and with an arbitrary one-third of first parity records deleted. First parity records of all cows were included in the analyses of the randomly culled popula- tions. Accuracy of evaluation, estimated by correlations between true effects and evaluations and prediction error variances, was highest by the multitrait analysis and lowest by the first parity only analysis. Evaluations obtained by the two multi- lactation methods were nearly identical with random culling. Regression of effect on evaluation was close to unity for the multitrait evaluation; was only .94 and .90 for the all lactation single trait evaluation with random and yield culling, respectively; and was .80 for the index of sire effects on the first parity only analysis. Single-trait multilactation method may be preferred, as it is nearly

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