论文标题
具有定性和定量响应的出生记录数据的贝叶斯辅助变量模型
Bayesian Auxiliary Variable Model for Birth Records Data with Qualitative and Quantitative Responses
论文作者
论文摘要
许多应用程序涉及具有定性和定量响应的数据。当两个响应之间存在关联时，联合模型将提供改进的结果，而不是单独建模它们。在本文中，我们提出了一种贝叶斯方法，以共同建模此类数据。联合模型将定性和定量响应联系起来，并可以通过潜在变量评估其依赖性强度。参数的后验分布是通过有效的MCMC采样算法获得的。模拟表明，所提出的方法可以提高两个响应的预测能力。我们将拟议的联合模型应用于弗吉尼亚州卫生部获得的出生记录数据，并研究婴儿早产与其出生体重之间的相互依赖。
Many applications involve data with qualitative and quantitative responses. When there is an association between the two responses, a joint model will provide improved results than modeling them separately. In this paper, we propose a Bayesian method to jointly model such data. The joint model links the qualitative and quantitative responses and can assess their dependency strength via a latent variable. The posterior distributions of parameters are obtained through an efficient MCMC sampling algorithm. The simulation shows that the proposed method can improve the prediction capacity for both responses. We apply the proposed joint model to the birth records data acquired by the Virginia Department of Health and study the mutual dependence between preterm birth of infants and their birth weights.
