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关于病例对照研究和病例队列研究中倾向得分的估计与应用。

On the estimation and use of propensity scores in case-control and case-cohort studies.

作者信息

Månsson Roger, Joffe Marshall M, Sun Wenguang, Hennessy Sean

机构信息

Department of Biostatistics and Epidemiology and Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104-6021, USA.

出版信息

Am J Epidemiol. 2007 Aug 1;166(3):332-9. doi: 10.1093/aje/kwm069. Epub 2007 May 15.

Abstract

The use of propensity scores to adjust for measured confounding factors has become increasingly popular in cohort studies. However, their use in case-control and case-cohort studies has received little attention. The authors present some theory on the estimation and use of propensity scores in case-control and case-cohort studies and present the results of simulation studies that examine whether large-sample expectations are realized in studies of typical size. The application of propensity scores is less straightforward in case-control and case-cohort studies than in cohort studies. The authors' simulations revealed two potentially important issues. First, when using several potential approaches, there is artifactual effect modification of the odds ratio by level of propensity score. The magnitude of this phenomenon decreases as the sample size increases. Second, several potential approaches produce estimated propensity scores that do not converge to the true value as sample size increases and, thus, can fail to adjust fully for measured confounding factors. However, the magnitude of residual confounding appeared modest in our simulations. Researchers considering using propensity scores in case-control or case-cohort studies should consider the potential for artifactual effect modification and their reduced ability to control for potential confounding factors.

摘要

在队列研究中,使用倾向得分来调整已测量的混杂因素已变得越来越普遍。然而,它们在病例对照研究和病例队列研究中的应用却很少受到关注。作者提出了一些关于病例对照研究和病例队列研究中倾向得分估计和使用的理论,并展示了模拟研究的结果,这些研究考察了在典型规模的研究中是否实现了大样本预期。倾向得分在病例对照研究和病例队列研究中的应用不如在队列研究中那么直接。作者的模拟揭示了两个潜在的重要问题。首先,当使用几种潜在方法时,比值比会因倾向得分水平而出现人为的效应修正。随着样本量的增加,这种现象的程度会降低。其次,几种潜在方法产生的估计倾向得分不会随着样本量的增加而收敛到真实值,因此可能无法完全调整已测量的混杂因素。然而,在我们的模拟中,残余混杂的程度似乎不大。考虑在病例对照研究或病例队列研究中使用倾向得分的研究人员应考虑人为效应修正的可能性以及他们控制潜在混杂因素能力的降低。

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