Borgan O, Langholz B, Samuelsen S O, Goldstein L, Pogoda J
Department of Mathematics, University of Oslo, Norway.
Lifetime Data Anal. 2000 Mar;6(1):39-58. doi: 10.1023/a:1009661900674.
A variant of the case-cohort design is proposed for the situation in which a correlate of the exposure (or prognostic factor) of interest is available for all cohort members, and exposure information is to be collected for a case-cohort sample. The cohort is stratified according to the correlate, and the subcohort is selected by stratified random sampling. A number of possible methods for the analysis of such exposure stratified case-cohort samples are presented, some of their statistical properties developed, and approximate relative efficiency and optimal allocation to the strata discussed. The methods are compared to each other, and to randomly sampled case-cohort studies, in a limited computer simulation study. We found that all of the proposed analysis methods performed well and were more efficient than a randomly sampled case-cohort study.
针对一种情况,我们提出了病例队列设计的一种变体,即对于所有队列成员,感兴趣的暴露因素(或预后因素)的一个相关因素是可用的,并且要为一个病例队列样本收集暴露信息。根据该相关因素对队列进行分层,并通过分层随机抽样选择亚队列。本文提出了一些分析此类暴露分层病例队列样本的可能方法,推导了它们的一些统计特性,并讨论了各层的近似相对效率和最优分配。在一项有限的计算机模拟研究中,将这些方法相互比较,并与随机抽样的病例队列研究进行比较。我们发现,所有提出的分析方法都表现良好,并且比随机抽样的病例队列研究更有效。