Statistical analysis of test-day milk yields using random regression models for the comparison of feeding groups during the lactation period

Archives of Animal Nutrition

Volumn 60, Issue 5, 2006, Pages 341-357

  Mielenz, Norbert ^a   Spilke, Joachim ^a   Krejcova, Hana ^a   Schüler, Lutz ^a  

^a MARTIN LUTHER UNIVERSITY HALLE WITTENBERG   (Germany)

Author keywords

Feeding experiment; Random regression models; Statistical analysis; Test day milk yields

Indexed keywords

ANIMAL; ANIMAL FOOD; ARTICLE; BIOLOGICAL MODEL; CATTLE; COMPARATIVE STUDY; DAIRYING; FEMALE; GENETICS; LACTATION; METABOLISM; METHODOLOGY; MILK; PHYSIOLOGY; PREDICTION AND FORECASTING; REGRESSION ANALYSIS; SECRETION; STATISTICAL MODEL;

ANIMAL FEED; ANIMAL NUTRITION PHYSIOLOGY; ANIMALS; CATTLE; DAIRYING; FEMALE; LACTATION; MILK; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PREDICTIVE VALUE OF TESTS; REGRESSION ANALYSIS;

ANIMALIA; BOS TAURUS;

EID: 33750065439     PISSN: 1745039X     EISSN: 14772817     Source Type: Journal    
DOI: 10.1080/17450390600884435     Document Type: Article

References (19)

1. Akaike H. 1973. Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Csaki F, editors. 2nd Int. Symp. Information theory. Akademiai Kiado, Budapest, Hungary. pp 267-281.
2. Ali TE, Schaeffer LR. 1987. Accounting for covariances among test day milk yield in dairy cows. Can J Anim Sci 67:637-644.
3. Burnham KP, Anderson DR. 2002. Model selection and multimodel inference: A practical information-theoretic approach. 2nd ed. New York: Springer-Verlag.
4. Bormann J, Wiggans GR, Druet T, Gengler N. 2003. Within-herd effects of age at test day and lactation stage on test-day yields. J Dairy Sci 86:3765-3774.
5. Diggle PJ, Heagerty P, Liang KY, Zeger SL. 2002. Analysis of longitudinal data. 2nd ed. Oxford: Oxford University Press.
6. Dunkel S, Kluge H, Spilke J, Eder K. 2004. Einsatz organischer Spurenelemente: Wirkungen von Aminosäure-Zink-und Manganchelaten auf Milchleistung und Tiergesundheit. Die Milchpraxis: Die Fachzeitschrift für Milcherzeuger und Rindermäster 42:180-181.
7. Fahrmeir L, Hamerle A. 1984. Multivariate statistische Verfahren. Berlin/New York: de Gruyter.
8. Greene WH. 2000. Econometric anaylsis. 4th ed. New York: Prentice Hall.
9. Jamrozik J, Schaeffer LR. 1997. Estimates of genetic parameters for a test day model with random regressions for yield traits of first lactation Holsteins. J Dairy Sci 80:762-770.
10. Kenward MG, Roger JH. 1997. Small sample inference for fixed effects from restricted maximum likelihood. Biometrics 53:983-997.
11. Lesaffre E, Todem D, Verbeke G, Kenward M. 2000. Flexible modelling of the covariance matrix in a linear random effects model. Biometr J 42:807-822.
12. Ptak E, Schaeffer LR. 1993. Use of test day yields for genetic evaluation of dairy sires and cows. Livest Prod Sci 34:23-34.
13. Pitt MA, Myung IJ, Zhang S. 2002. Toward a method of selecting among computational models of cognition. Psychological Rev 109:472-491.
14. Reents R, Jamrozik J, Schaeffer LR, Dekkers JCM. 1995. Genetic evaluation for somatic cell score with a multiple lactation test day model. J Dairy Sci 78:2858-2870.
15. Schaeffer LR, Dekkers JCM. 1994. Random regressions in animal models for test-day production in dairy cattle. Proc. 5th WCGALP, Guelph, Canada.
16. Schaeffer LR. 2004. Application of random regression models in animal breeding. Livest Prod Sci 86: 35-45.
17. Schwarz G. 1978. Estimating the dimension of a model. Ann Statistics 6:461-464.
18. Swalve HH. 1995. Test day models in the analysis of dairy production data -a review. Arch Tierz 38: 591-612.
19. Verbeke G, Lesaffre E, Brandt LJ. 1998. The detection of residual serial correlation in linear mixed models. Stat Med 17:1391-1402.