IDENTIFIABILITY, EXCHANGEABILITY, AND EPIDEMIOLOGIC CONFOUNDING
IDENTIFIABILITY, EXCHANGEABILITY, AND EPIDEMIOLOGIC CONFOUNDING
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DOI：
10.1093/ije/15.3.413
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发表时间：
1986-09-01
影响因子：
7.7
通讯作者：
ROBINS, JM
中科院分区：
文献类型：
--
作者：
GREENLAND, S;ROBINS, JM
参数的不可辨识性是经典统计学中一个公认的问题，贝叶斯统计学家很早就认识到可交换性假设在统计推断中的重要性。流行病学中一个看似不相关的问题是混杂问题：由于暴露者和未暴露者之间风险的固有差异，在估计暴露对疾病风险的影响时存在偏差。使用简单的暴露效应确定性模型，在可识别性、可交换性和混杂性的概念之间建立了逻辑联系。这种联系允许人们将混杂问题视为由可识别性问题引起的，并揭示混杂控制方法中隐含的可交换性假设。它还为基于暴露组的可比性的混杂定义（而不是基于可折叠性的定义）提供了进一步的理由。
Non-identifiability of parameters is a well-recognized problem in classical statistics, and Bayesian statisticians have long recognized the importance of exchangeability assumptions in making statistical inferences. A seemingly unrelated problem in epidemiology is that of confounding: bias in estimation of the effects of an exposure on disease risk, due to inherent differences in risk between exposed and unexposed individuals. Using a simple deterministic model for exposure effects, a logical connection is drawn between the concepts of identifiability, exchangeability, and confounding. This connection allows one to view the problem of confounding as arising from problems of identifiability, and reveals the exchangeability assumptions that are implicit in confounder control methods. It also provides further justification for confounder definitions based on comparability of exposure groups, as opposed to collapsibility-based definitions.