Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: A Bayesian approach via Gibbs sampling

Journal of Dairy Science

Volumn 86, Issue 11, 2003, Pages 3694-3703

  Odegard J ^a   Jensen, J ^b   Madsen, P ^b   Gianola, D ^a,c   Klemetsdal, G ^a   Heringstad, B ^a  

^a NORWEGIAN UNIVERSITY OF LIFE SCIENCES   (Norway)

^b DANISH INSTITUTE OF AGRICULTURAL SCIENCES   (Denmark)

^c UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Bayesian method; Mixture model; Somatic cell score; Udder health

Indexed keywords

ANIMALIA; BOS TAURUS;

ANIMAL; ANIMAL DISEASE; ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; CATTLE; CATTLE DISEASE; CELL COUNT; COMPUTER SIMULATION; CYTOLOGY; FEMALE; MILK; PREDICTION AND FORECASTING; RANDOMIZATION; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ANIMALS; BAYES THEOREM; CATTLE; CELL COUNT; COMPUTER SIMULATION; FEMALE; LINEAR MODELS; MASTITIS, BOVINE; MILK; MODELS, BIOLOGICAL; PREDICTIVE VALUE OF TESTS; RANDOM ALLOCATION; SENSITIVITY AND SPECIFICITY;

EID: 1542649386     PISSN: 00220302     EISSN: None     Source Type: Journal    
DOI: 10.3168/jds.S0022-0302(03)73975-7     Document Type: Article

References (15)

1. Casella, G., and E. I. George. 1992. Explaining the Gibbs sampler. Am. Stat. 46:167-174.
2. Detilleux, J., and P. L. Leroy. 2000. Application of a mixed normal mixture model for the estimation of mastitis-related parameters. J. Dairy Sci. 83:2341-2349.
3. Heringstad, B., Y. M. Chang, D. Gianola, and G. Klemetsdal. 2003. Genetic analysis of longitudinal trajectory of clinical mastitis in first-lactation Norwegian Cattle. J. Dairy Sci. 86:2676-2683.
4. Jansen, R. C. 1992. A general mixture model for mapping quantitative trait loci by using molecular markers. Theor. Appl. Genet. 85:252-260.
5. Kao, C. H., and Z. B. Zeng. 1997. General formulas for obtaining the MLEs and the asymptotic variance-covariance matrix in mapping quantitative trait loci when using the EM algorithm. Biometrics 53:653-665.
6. Kuhn, M. T., A. E. Freeman, and R. L. Fernando. 1999. Approaches investigated to correct for preferential treatment. J. Dairy Sci. 82:181-190.
7. McLachlan, G., and D. Peel. 2000. Finite Mixture Models. John Wiley & Sons, Inc., New York, NY.
8. Militino, A. F., M. D. Ugarte, and C. B. Dean. 2001. The use of mixture models for identifying high risks in disease mapping. Stat. Med. 20:2035-2049.
9. Mrode, R. A., and G. J. T. Swanson. 1996. Genetic and statistical properties of somatic cell count and its suitability as an indirect means of reducing the incidence of mastitis in dairy cattle. Anim. Breed. Abstr. 64:847-857.
10. Raftery, A. L., and S. Lewis. 1992. How many iterations in the Gibbs sampler? Pages 763-774 in Bayesian Statistics 4. J. M. Bernando, J. O. Berger, A. P. Dawid, and A. F. M. Smith, ed. Oxford University Press, Oxford, UK.
11. Schukken, Y. H., B. A. Mallard, J. C. M. Dekkers, K. E. Leslie, and M. J. Stear. 1994. Genetic impact on the risk of intramammary infection following Staphylococcus aureus challenge. J. Dairy Sci. 77:639-647.
12. Schukken, Y. H., K. E. Leslie, D. A. Barnum, B. A. Mallard, J. H. Lumsden, P. C. Dick, G. H. Vessie, and M. E. Kehrli. 1999. Experimental Staphylococcus aureus intramammary challenge in late lactation dairy cows: Quarter and cow effects determining the probability of infection. J. Dairy Sci. 82:2393-2401.
13. Shuster, D. E., E. K. Lee, and M. E. Kehrli. 1996. Bacterial growth, inflammatory cytokine production, and neutrophil recruitment during coliform mastitis in cows within ten days after calving, compared with cows at midlactation. Am. J. Vet. Res. 57:1569-1575.
14. Sorensen, D., and D. Gianola. 2002. Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics. Springer-Verlag, New York, NY.
15. Suriyasathaporn, W., Y. H. Schukken, M. Nielen, and A. Brand. 2000. Low somatic cell count: A risk factor for subsequent clinical mastitis in a dairy herd. J. Dairy Sci. 83:1248-1255.