Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, University of Aarhus, DK-8830 Tjele, Denmark.
Genetics. 2010 Jan;184(1):277-84. doi: 10.1534/genetics.109.110759. Epub 2009 Nov 9.
An analysis of mortality is undertaken in two breeds of pigs: Danish Landrace and Yorkshire. Zero-inflated and standard versions of hierarchical Poisson, binomial, and negative binomial Bayesian models were fitted using Markov chain Monte Carlo (MCMC). The objectives of the study were to investigate whether there is support for genetic variation for mortality and to study the quality of fit and predictive properties of the various models. In both breeds, the model that provided the best fit to the data was the standard binomial hierarchical model. The model that performed best in terms of the ability to predict the distribution of stillbirths was the hierarchical zero-inflated negative binomial model. The best fit of the binomial hierarchical model and of the zero-inflated hierarchical negative binomial model was obtained when genetic variation was included as a parameter. For the hierarchical binomial model, the estimate of the posterior mean of the additive genetic variance (posterior standard deviation in brackets) at the level of the logit of the probability of a stillbirth was 0.173(0.039) in Landrace and 0.202(0.048) in Yorkshire. The implications of these results from a breeding perspective are briefly discussed.
对丹麦长白猪和约克夏猪这两个品种进行了死亡率分析。使用马尔可夫链蒙特卡罗（MCMC）方法拟合了零膨胀和标准版本的分层泊松、二项式和负二项式贝叶斯模型。研究的目的是探讨是否存在死亡率的遗传变异支持，并研究各种模型的拟合质量和预测性能。在这两个品种中，最适合数据的模型是标准二项式分层模型。在预测死产分布方面表现最好的模型是分层零膨胀负二项式模型。当将遗传变异作为参数纳入时，二项式分层模型和零膨胀分层负二项式模型的拟合效果最佳。对于二项式分层模型，在对数几率死亡产概率水平上，加性遗传方差的后验均值（后验标准差在括号内）的估计值为 0.173（0.039）在长白猪和 0.202（0.048）在约克夏猪。从育种的角度简要讨论了这些结果的意义。
