A comparison of the hierarchical likelihood and Bayesian approaches to spatial epidemiological modelling
A comparison of the hierarchical likelihood and Bayesian approaches to spatial epidemiological modelling
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DOI：
10.1002/env.877
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发表时间：
2007-11-01
期刊：
影响因子：
1.7
通讯作者：
Browne, William J.
中科院分区：
文献类型：
--
作者：
Jang, Myoung Jin;Lee, Youngjo;Browne, William J.
近年来，贝叶斯方法在疾病制图中得到了广泛应用。分层（h-）似然方法允许在随机效应模型中进行可靠的似然推断，因此比较h-似然方法和贝叶斯方法是有趣的。为了进行比较，我们考虑了三个例子：南卡罗来纳州的低出生体重和癌症死亡率数据以及苏格兰的唇癌数据。h-似然方法和贝叶斯方法的均值估计几乎相同，而方差成分估计可能有些不同，这取决于先验的选择。版权所有(c) 2007约翰威利父子有限公司
Recently Bayesian methods have been widely used in disease mapping. Hierarchical (h-) likelihood methods allow reliable likelihood inference in random-effect models and it is therefore interesting to compare h-likelihood and Bayesian methods. For comparison we consider three examples: low birth weight and cancer mortality data in South Carolina and lip cancer data in Scotland. Mean estimates from both h-likelihood and Bayesian approaches are almost identical, while variance-component estimates can be somewhat different, depending upon choice of priors. Copyright (c) 2007 John Wiley & Sons, Ltd.