A comparison between Poisson and zero-inflated Poisson regression models with an application to number of black spots in Corriedale sheep

Genetics Selection Evolution

Volumn 40, Issue 4, 2008, Pages 379-394

  Naya, Hugo ^a,b,c   Urioste, Jorge I ^b   Chang, Yu Mei ^c   Rodrigues Motta, Mariana ^c   Kremer, Roberto ^b   Gianola, Daniel ^c  

^a INSTITUT PASTEUR DE MONTEVIDEO   (Uruguay)

^b UNIVERSIDAD DE LA REPÚBLICA   (Uruguay)

^c UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Bayesian hierarchical model; Posterior predictive ability; Sheep; Spot; Zero inflated Poisson

Indexed keywords

COMPARATIVE STUDY; POISSON RATIO; REGRESSION ANALYSIS; SHEEP;

SOUTH AMERICA; URUGUAY;

OVIS ARIES;

EID: 46749086676     PISSN: 0999193X     EISSN: 12979686     Source Type: Journal    
DOI: 10.1051/gse:2008010     Document Type: Article

References (31)

1. Cardellino R., Herencia de fibras coloreadas, Produc. Ovina 6 (1994) 19-37.
2. Cardellino R., Mendoza J., Fibras coloreadas en tops con lanas acondicionadas (zafra 94-95), Rev. Lananoticias SUL 115 (1996) 37-40.
3. Cardellino R., Guillamón B.E., Severi J.F., Origen de las fibras coloreadas en tops de lana uruguaya, Produc. Ovina 3 (1990) 81-83.
4. Celeux G., Forbes F., Robert C.P., Titterington D.M., Deviance information criteria for missing data models, Bayesian Anal. 1 (2006) 651-674.
5. Draper D., Tutorial 1: Hierarchical Bayesian Modeling, in: 6th World Meeting International Society for Bayesian Analysis, 28 May-1 June, 2000, Hersonissos, Heraklion, Crete.
6. Enns R.M., Nicoll G.B., Incidence and heritability of black wool spots in Romney sheep, N. Z. J. Agric. Res. 45 (2002) 67-70.
7. Fears T.R., Scotto J., Schneiderman M.A., Skin cancer, melanoma, and sunlight, Am. J. Public Health 66 (1976) 461-464.
8. Fears T.R., Scotto J., Schneiderman M.A., Mathematical models of age and ultraviolet effects on the incidence of skin cancer among whites in the United States, Am. J. Epidemiol. 105 (1977) 420-427.
9. Fleet M., Pigmentation types. Understanding the heritability and importance, Wool Tech. Sheep Breed. 44 (1996) 264-280.
10. Fleet M.R., Forrest J.W., The occurrence of pigmented skin and pigmented wool fibres in adult Merino sheep, Wool Tech. Sheep Breed. 33 (1984) 83-90.
11. Fleet M., Lush B., Sire effects on visible pigmentation in a Corriedale flock, Wool Tech. Sheep Breed. 45 (1997) 167-173.
12. Fleet M.R., Ponzoni R.W., Fibras pigmentadas en vellones blancos, in: Larrosa J.R., Bonifacino L.A. (Eds.), Seminario Científico Técnico Regional de Lanas, Montevideo, 1985, pp. 135-142.
13. Fleet M.R., Stafford J.E., The association between non-fleece pigmentation and fleece pigmentation in Corriedale sheep, Anim. Prod. 49 (1989) 241-247.
14. Forrest J.W., Fleet M.R., Pigmented spots in the wool-bearing skin induced by ultraviolet light, Aust. J. Biol. Sci. 39 (1986) 123-136.
15. Gianola D., Statistics in animal breeding: angels and demons, in: Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, 13-18 August, 2006, CD Paper 00-03, Belo Horizonte-MG, Brazil, 8 p.
16. Kremer R., Urioste J.I., Naya H., Rosés L., Rista L., López C., Incidence of skin spots and pigmentation in Corriedale sheep, in: IX World Conference on Animal Production, 26-31 October, 2003, Porto Alegre, Brazil.
17. Lambert D., Zero-inflated Poisson regression, with an application to defects in manufacturing, Technometrics 34 (1992) 1-14.
18. Larrosa J.R., Orlando D., Incidencia de fibras oscuras en lanas peinadas uruguayas, in: An. Fac. Vet. Uruguay, Montevideo, 21/25, 1984-1988, pp. 71-78.
19. Martínez-Ávila J.C., Spangler M., Rekaya R., Hierarchical model for zero-inflated count data: a simulation study, in: Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, 13-18 August, 2006, CD Paper 24-08, Belo Horizonte-MG, Brazil, 4 p.
20. Mendoza J., Cardellino R., Maggiolo J., Garín M., Fibras coloreadas en Corriedale, Lananoticias 129 (2001) 37-40.
21. McCullagh P., Nelder J.A., Generalized Linear Models, Chapman and Hall, London, 1989.
22. Newton M.A., Raftery A.E., Approximate Bayesian inference by the weighted likelihood bootstrap (with discussion), J. Roy. Stat. Soc. B 56 (1994) 1-48.
23. Oliveria S.A., Saraiya M., Geller A.C., Heneghan M.K., Jorgensen C., Sun exposure and risk of melanoma, Arch. Dis. Child. 91 (2006) 131-138.
24. Pereira G.I., Miquelerena J.M., Urioste J.I., Naya H., Kremer R., Lopez A., Surraco L., Presencia de fibras pigmentadas en una majada experimental, Corrie- dale, in: 12th CorriedaleWorld Congress, 1-10 September, 2003, Montevideo, Uruguay, p. 109.
25. Pinheiro J.C., Bates D.M., Mixed-effects Models in S and S-PLUS, Springer, New York, 2000.
26. R Development Core Team, R: A Language and Environment for Statistical Computing, 2007, R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07-0, http://www.R-project.org.
27. Rodrigues-Motta M., Gianola D., Heringstad B., Rosa G.J.M., Chang Y.M., A zero-inflated Poisson model for genetic analysis of number of mastitis cases in Norwegian Red cows, J. Dairy Sci. 90 (2007) 5306-5315.
28. Sorensen D., Gianola D., Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics, Springer-Verlag, New York, 2002.
29. Sorensen D., Waagepetersen R., Normal linear models with genetically structured residual variance heterogeneity: a case study, Genet. Res. Camb. 82 (2003) 207-222.
30. Spiegelhalter D.J., Best N.G., Carlin B.P., van der Linde A., Bayesian measures of model complexity and fit (with discussion), J. Roy. Stat. Soc. B 64 (2002) 583-639.
31. Thomas A., Hara B.O., Ligges U., Sturtz S., Making BUGS Open, R News 6 (2006) 12-17.