Bayesian extrapolation of space-time trends in cancer registry data
Bayesian extrapolation of space-time trends in cancer registry data
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DOI：
10.1111/j.0006-341x.2004.00259.x
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发表时间：
2004-12-01
期刊：
影响因子：
1.9
通讯作者：
Held, L
中科院分区：
文献类型：
--
作者：
Schmid, V;Held, L
我们应用一个完整的贝叶斯模型框架，在西德国胃癌死亡率的数据集。数据按年龄组、年份和地区分层。我们的目标是使用一个额外的空间组件的年龄-时期-队列模型，调查是否有证据表明这些数据中的时空相互作用。此外，我们将确定是否周期空间或队列空间相互作用模型更适合预测未来的死亡率。该设置将是完全贝叶斯基于一系列高斯马尔可夫随机场先验的每个组件。统计推断是基于有效的算法块更新高斯马尔可夫随机场，这是最近提出的文献。
We apply a full Bayesian model framework to a dataset on stomach cancer mortality in West Germany. The data are stratified by age group, year, and district. Using an age-period-cohort model with an additional spatial component, our goal is to investigate whether there is evidence for space-time interactions in these data. Furthermore, we will determine whether a period-space or a cohort-space interaction model is more appropriate to predict future mortality rates. The setup will be fully Bayesian based on a series of Gaussian Markov random field priors for each of the components. Statistical inference is based on efficient algorithms to block update Gaussian Markov random fields, which have recently been proposed in the literature.