Analysis of case-cohort data: A comparison of different methods
Analysis of case-cohort data: A comparison of different methods
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DOI：
10.1016/j.jclinepi.2006.06.022
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发表时间：
2007-04-01
影响因子：
7.2
通讯作者：
Peeters, Petra H. M.
中科院分区：
文献类型：
--
作者：
Onland-Moret, N. Charlotte;van der A, Daphne L.;Peeters, Petra H. M.
目的：病例-队列设计结合了前瞻性队列研究的优点和病例-对照设计的效率。通常使用考克斯比例风险模型进行分析。然而，由于采样，模型的适应是必要的。我们比较了文献中提出的三种方法，它们在研究对象的权重上不同：普伦蒂斯的方法、巴洛的方法和自我和普伦蒂斯的方法。在17，357名女性中，我们研究了体重指数与心血管疾病之间的关系（n = 821），结果：即使在抽样分数为0.01的情况下，三种方法的估计值和标准误（SE）均相同。当采样分数>= 0.10时，病例队列分析的结果与全队列分析相似。通过模拟，如果整个队列很小，三种方法提供了不同的结果（
Objective: The case-cohort design combines the advantages of a prospective cohort study and the efficiency of a case-control design. Usually a Cox proportional-hazards model is used for the analyses. However, adaptation of the model is necessary because of the sampling. We compared three methods that were proposed in the literature, which differ in weighting of study subjects: Prentice's, Barlow's, and Self and Prentice's method.Study Design and Setting: In a cohort of 17,357 women we studied the relationship between body mass index and cardiovascular disease (n = 821) with varying subcohort sizes (sampling fraction = 0.005, 0.01, 0.05, 0.10, 0.15).Results: Even with a sampling fraction of 0.01, all three methods showed identical estimates and standard errors (SE). With sampling fractions >= 0.10, results of the case-cohort analyses were similar to the full-cohort analyses. With simulations, the three methods provided different results if the full cohort is small (