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Genetics Selection Evolution

, 35:489 | Cite as

Cumulative t-link threshold models for the genetic analysis of calving ease scores

  • Kadir Kizilkaya
  • Paolo Carnier
  • Andrea Albera
  • Giovanni Bittante
  • Robert J. TempelmanEmail author
Open Access
Research

Abstract

In this study, a hierarchical threshold mixed model based on a cumulative t-link specification for the analysis of ordinal data or more, specifically, calving ease scores, was developed. The validation of this model and the Markov chain Monte Carlo (MCMC) algorithm was carried out on simulated data from normally and t4 (i.e. a t-distribution with four degrees of freedom) distributed populations using the deviance information criterion (DIC) and a pseudo Bayes factor (PBF) measure to validate recently proposed model choice criteria. The simulation study indicated that although inference on the degrees of freedom parameter is possible, MCMC mixing was problematic. Nevertheless, the DIC and PBF were validated to be satisfactory measures of model fit to data. A sire and maternal grandsire cumulative t-link model was applied to a calving ease dataset from 8847 Italian Piemontese first parity dams. The cumulative t-link model was shown to lead to posterior means of direct and maternal heritabilities (0.40 ± 0.06, 0.11 ± 0.04) and a direct maternal genetic correlation (-0.58 ± 0.15) that were not different from the corresponding posterior means of the heritabilities (0.42 ± 0.07, 0.14 ± 0.04) and the genetic correlation (-0.55 ± 0.14) inferred under the conventional cumulative probit link threshold model. Furthermore, the correlation (> 0.99) between posterior means of sire progeny merit from the two models suggested no meaningful rerankings. Nevertheless, the cumulative t-link model was decisively chosen as the better fitting model for this calving ease data using DIC and PBF.

Keywords

threshold model t-distribution Bayesian inference calving ease 

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Copyright information

© INRA, EDP Sciences 2003

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Kadir Kizilkaya
    • 1
  • Paolo Carnier
    • 2
  • Andrea Albera
    • 3
  • Giovanni Bittante
    • 2
  • Robert J. Tempelman
    • 1
    Email author
  1. 1.Department of Animal ScienceMichigan State UniversityEast LansingUSA
  2. 2.Department of Animal ScienceUniversity of Padova, AgripolisLegnaroItaly
  3. 3.Associazione Nazionale Allevatori Bovini di Razza PiemonteseCarrùItaly

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