EMPIRICAL-BAYES AND SEMI-BAYES APPROACHES TO OCCUPATIONAL AND ENVIRONMENTAL-HAZARD SURVEILLANCE
EMPIRICAL-BAYES AND SEMI-BAYES APPROACHES TO OCCUPATIONAL AND ENVIRONMENTAL-HAZARD SURVEILLANCE
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DOI：
10.1080/00039896.1994.9934409
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发表时间：
1994-01-01
期刊：
影响因子：
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通讯作者：
POOLE, C
中科院分区：
文献类型：
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作者：
GREENLAND, S;POOLE, C
与传统的统计方法相比，经验-贝叶斯方法在统计精度方面提供了潜在的显著改进。我们提供了职业和环境危害监测数据的经验贝叶斯分析的初步介绍。这种分析特别适用于必须检查许多关联，但很少或根本不能准确估计的情况。回顾了危险监测中的统计问题，然后讨论了经验贝叶斯分析的原理和方法，并使用职业暴露和癌症死亡率的研究来说明关键概念。最后，对经验贝叶斯分析背后的假设进行了批判性的讨论，特别关注了将经验贝叶斯与传统方法区分开来的“可互换性”假设。
Empirical-Bayes methods offer potentially dramatic improvements in statistical accuracy over conventional statistical methods. We provide an elementary introduction to empirical-Bayes analysis of occupational and environmental hazard surveillance data. Such analyses are especially well suited to situations in which many associations must be examined, but few or none can be estimated precisely. Statistical issues in hazard surveillance are reviewed, followed by a discussion of the rationale and methods for empirical-Bayes analyses, using a study of occupational exposures and cancer mortality to illustrate key concepts. Finally, the assumptions underlying empirical-Bayes analyses are discussed critically, with special attention to the ''exchangeability'' assumptions that distinguish empirical-Bayes from conventional methods.