Integrating informative priors from experimental research with Bayesian methods: an example from radiation epidemiology.
Integrating informative priors from experimental research with Bayesian methods: an example from radiation epidemiology.
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DOI：
10.1097/ede.0b013e31827623ea
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发表时间：
2013-01
期刊：
影响因子：
--
通讯作者：
Wing S
中科院分区：
文献类型：
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作者：
Hamra G;Richardson D;Maclehose R;Wing S
在回归建模中，信息先验是流行病学家处理稀疏数据问题的有用工具。有时，调查人员正在研究暴露于两种媒介X和Y的人群，其中Y是主要感兴趣的媒介。先前的研究可能表明，这些暴露对健康结果有不同的影响，其中一种比另一种更有害。此类信息可来自流行病学分析；然而，在没有这种证据的情况下，可以从毒理学研究或其他实验研究中获得知识。不幸的是，在流行病学分析中使用毒理学发现来建立信息先验需要强有力的假设，而没有既定的使用方法。我们提出了一种方法，以帮助弥合动物和细胞研究之间的差距和流行病学研究规范的顺序约束的先验。我们用辐射流行病学的一个例子来说明这种方法。
Informative priors can be a useful tool for epidemiologists to handle problems of sparse data in regression modeling. It is sometimes the case that an investigator is studying a population exposed to two agents, X and Y, where Y is the agent of primary interest. Previous research may suggest that the exposures have different effects on the health outcome of interest, one being more harmful than the other. Such information may be derived from epidemiologic analyses; however, in the case where such evidence is unavailable, knowledge can be drawn from toxicologic studies or other experimental research. Unfortunately, using toxicologic findings to develop informative priors in epidemiologic analyses requires strong assumptions, with no established method for its utilization. We present a method to help bridge the gap between animal and cellular studies and epidemiologic research by specification of an order-constrained prior. We illustrate this approach using an example from radiation epidemiology.