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Journal of Dairy Science Vol. 81 No. 10 2710-2722
© 1998 by American Dairy Science Association ®
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Bayesian Analysis via Gibbs Sampling of Susceptibility to Intramammary Infection in Holstein Cattle

S. L. Rodriguez-Zas 1, D. Gianola 1, and G. E. Shook 1

1 Department of Dairy Science, University of Wisconsin, Madison 53706

A Bayesian analysis was undertaken to assess the susceptibility of Holsteins to mastitis from 120 to 305 d in milk. Data included 595 lactations from 267 cows. The response variable was presence or absence of intramammary infection; explanatory variables were period and season of calving, somatic cell score, and cow. The logistic model adopted had period and season of calving and the regression on somatic cell score with vague prior distributions, and cow effects had a normal prior with unknown variance sigmau2, which, in turn, had a gamma prior. Implementation was by Gibbs sampling. Posterior densities of location parameters were unimodal and symmetric. The probability of intramammary infection of a sample cow was skewed. The posterior distribution of sigmau2 was skewed also. Gibbs samples of sigmau2 had high lag correlations, which gave an effective sample ranging between 47 and 117 from a chain of size 3000. There were differences between estimates of sigmau2 found using Gibbs sampling and those obtained using approximations. The low information content arising from the small size of the data and the binary nature of the response are reasons for such differences. A sensitivity analysis revealed influences of hyperparameters of the prior distribution of sigmau2 on inferences about this parameter.

Key Words: somatic cell score • Bayesian • Gibbs sampling • priors

Submitted on August 18, 1997
Accepted on June 9, 1998







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