An analysis of Japanese liver cancer mortality data with Bayesian age – period – cohort models
An analysis of Japanese liver cancer mortality data with Bayesian age – period – cohort models
复制标题
用贝叶斯年龄-时期-队列模型分析日本肝癌死亡率数据
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Wataru Sakamoto
中科院分区：
文献类型：
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作者：
Wataru Sakamoto
年龄-时期-队列(APC)模型已被广泛应用于发病率和死亡率数据的分析。贝叶斯APC模型结合了年龄、周期和队列效应的多变量高斯先验信息，可以避免可辨识性问题。集成嵌套拉普拉斯近似(INLA)推理最近已成为一种有用的工具。以日本肝癌死亡率数据为例，说明了带INLA的贝叶斯APC模型的应用，揭示了队列效应的突变。关键词：信息准则；积分嵌套拉普拉斯逼近；高斯马尔可夫随机场
Age–period–cohort (APC) models have been widely used in the analysis of incidence and mortality data. Bayesian APC models, in which multivariate Gaussian priors are incorporated on age, period and cohort effects, can evade the identifiability problem. Inference with integrated nested Laplace approximations (INLA) has recently been a useful tool. An application of the Bayesian APC models with INLA to Japanese liver cancer mortality data is illustrated, in which a sudden change of the cohort effect was revealed. Keyword: information criteria; integrated nested Laplace approximation; Gaussian Markov random field