Free Access
Genet. Sel. Evol.
Volume 38, Number 6, November-December 2006
Page(s) 565 - 581
Published online 28 November 2006
References of  Genet. Sel. Evol. 38 (2006) 565-581
  1. Albert J.H., Chib S., Bayesian analysis of binary and polychotomous response data, J. Am. Stat. Assoc. 88 (1993) 669-679.
  2. Andersen A.H., Korsgaard I.R., Jensen J., Idenfiability of parameters in - and equivalence of animal and sire models for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits, Department of Theoretical Statistics, University of Aarhus, Research reports 417 (2000) 1-36.
  3. Andersen P.K., Borgan Ø., Gill R.D., Keiding N., Statistical models based on counting processes, Springer, New York, 1992.
  4. Bulmer M.G., The mathematical theory of quantitative genetics, Clarendon Press, Oxford, 1980.
  5. Bundgaard E., Hoej S., Direct access to the cattle database with livestock registration, Annu. Rep. National Committee on Danish Cattle Husbandry, Aarhus Denmark, 2000.
  6. Carlin B.P., Louis T.A., Bayes empirical bayes methods for data analysis, Chapman and Hall, Boca Raton, 2000.
  7. Damgaard L.H., The use of survival models to infer phenotypic and genetic aspects of longevity of sows, Plant & Animal Genomes XIV Conference, 14-18 January 2006, San Diego, CA, USA.
  8. Damgaard L.H., Korsgaard I.R., A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait, Genet. Sel. Evol. 38 (2006) 45-64 [EDP Sciences] [PubMed].
  9. Damgaard L.H., Korsgaard I.R., Simonsen J., Dalsgaard O., Andersen A.H., The effect of ignoring individual heterogeneity in Weibull log-normal sire frailty models, J. Anim. Sci. 84 (2006) 1338-1350 [PubMed].
  10. Danish Cattle Federation, Principles of Danish cattle breeding (2006), [consulted: 20 June 2006].
  11. Ducrocq V., Casella G., A Bayesian analysis of mixed survival models, Genet. Sel. Evol. 28 (1996) 505-529.
  12. Ducrocq V., Sölkner J., "The Survival Kit V3.0", a package for large analyses of survival data, in: Proceedings of the 6th World Congress on Genetics Applied to Livestock Production, 11-16 January 1998, Vol 27, University of New England, Armidale, pp. 447-450.
  13. Ducrocq V., Quaas R.L., Pollak E.J., Casella G., Length of productive life of dairy cows. 2. Variance component estimation and sire evaluation, J. Dairy Sci. 71 (1988) 3071-3079.
  14. Fisher B.A., The correlation between relatives on the supposition of Mendelian inheritance, T. Roy. Soc. Edin. 52 (1918) 399-433.
  15. Gelman A., Carlin J.B., Stern H.S., Rubin D.B., Bayesian data analysis, Chapman and Hall, Boca Raton, 1995.
  16. Gilks W.R., Wild P., Adaptive rejective sampling for Gibbs sampling, Appl. Statist. 41 (1992) 337-348.
  17. Hansen M., Lund M.S., Pedersen J., Christensen L.G., Gestation length in Danish Holsteins has weak genetic associations with stillbirth, calving difficulty, and calf size, Livest. Prod. Sci. 91 (2004) 23-33 [CrossRef].
  18. Hastings W.K., Monte Carlo sampling methods using Markov chains and their application, Biometrika 57 (1970) 97-109.
  19. Henryon M., Berg P., Jensen J., Andersen S., Genetic variation for resistance to clinical and subclinical diseases exists in growing pigs, Anim. Sci. 73 (2001) 375-387.
  20. Henryon M., Jokumsen A., Berg P., Lund I., Pedersen P.B., Olesen N.J., Slierendrecht W.J., Genetic variation for growth rate, feed conversion efficiency, and disease resistance exists within a farmed population of rainbow trout, Aquaculture 209 (2002) 59-76 [CrossRef].
  21. Hobert J.P., Casella G., The effect of improper priors on Gibbs sampling in hierarchical linear mixed models, J. Amer. Statist. Assoc. 91 (1996) 1461-1473 [MathSciNet].
  22. Jørgensen B., Andersen S., Genetic parameters for osteochondrosis in Danish Landrace and Yorkshire boars and correlations with leg weakness and production traits, Anim. Sci. 71 (2000) 427-434.
  23. Korsgaard I.R., Madsen P., Jensen J., Bayesian inference in the semi-parametric log normal frailty model using Gibbs sampling, Genet. Sel. Evol. 30 (1998) 241-256.
  24. Korsgaard I.R., Andersen A.H., Jensen J., Prediction error variance and expected response to selection is based on the best predictor - for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits, Genet. Sel. Evol. 34 (2002) 307-333 [EDP Sciences] [CrossRef] [PubMed].
  25. Korsgaard I.R., Lund M.S., Sorensen D., Gianola D., Madsen P., Jensen J., Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical, and binary traits using Gibbs sampling, Genet. Sel. Evol. 35 (2003) 159-183 [EDP Sciences] [CrossRef] [PubMed].
  26. Larroque H., Ducrocq V., An indirect approach for the estimation of genetic correlations between longevity and other traits, in: Proceedings of the 21th Interbull Meeting, May, 1999, vol. 21, Jouy-en-Josas, pp. 128-135.
  27. Little R.J.A., Rubin D.B., Statistical analysis with missing data, Wiley, New York, 1987.
  28. Liu J.S., The collapsed Gibbs sampler in Bayesian computations with applications to a gene regulation problem, J. Amer. Statist. Assoc. 89 (1994) 958-966 [MathSciNet].
  29. Liu J.S., Wong H.W., Kong A., Covariance structure of the Gibbs sampler with applications to the comparisons of estimators and augmentation schemes, Biometrica 81 (1994) 27-40.
  30. Lundeheim N., Genetic analysis of osteochondrosis and leg weakness in the Swedish pig progeny testing scheme, Acta. Agr. Scand. 37 (1987) 159-173.
  31. Luo M.F., Boettcher P.J., Schaeffer L.R., Dekkers J.C.M., Estimation of genetic parameters of calving ease in first and second parities of Canadian Holsteins using Bayesian methods, Livest. Prod. Sci. 74 (2002) 175-184 [CrossRef].
  32. Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., Teller E., Equations of state calculations by fast computing machines, J. Chem. Phys. 21 (1953) 1087-1092 [CrossRef].
  33. Roberts G.O., Sahu S.K., Updating schemes, correlation structure, blocking and parameterization for the Gibbs sampler, J. Royal Stat. Soc. B 59 (1997) 291-317.
  34. Robertson A., Lerner I.M., The heritability of all-or-none traits: Viability of poultry, Genetics 34 (1949) 395-411.
  35. Smith S.P., Quaas R.L., Productive lifespan of bull progeny groups: failure time analysis, J. Dairy Sci. 67 (1984) 2999-3007.
  36. Sorensen D., Gianola D., Likelihood, Bayesian, MCMC methods in quantitative genetics, Springer, New York, 2002.
  37. Sorensen D., Andersen S., Gianola D., Korsgaard I., Bayesian inference in threshold models using Gibbs sampling, Genet. Sel. Evol. 27 (1995) 229-249.
  38. Steinbock L., Näsholm A., Berglund B., Johansson K., Philipsson J., Genetic effects on stillbirth and calving difficulty in Swedish Holsteins at first and second calving, J. Dairy Sci. 86 (2003) 2228-2235 [PubMed].
  39. Veerkamp R.F., Brotherstone S., Engel B., Meuwissen T.H.E., Analysis of censored survival data using random regression models, Anim. Sci. 72 (2001) 1-10.
  40. Vukasinovic N., Application of survival analysis in breeding for longevity, in: Proceedings of the 21th Interbull Meeting, May, 1999, vol. 21, Jouy-en-Josas, pp. 181-189.
  41. Wright S., An analysis of variability in number of digits in an inbred strain of guinea pigs, Genetics 19 (1934) 506-536.
  42. Yazdi M.H., Visscher P.M., Ducrocq V., Thompson R., Heritability, reliability of genetic evaluations and response to selection in proportional hazard models, J. Dairy Sci. 67 (2002) 1563-1577.