Zhang H, Holford T, Bracken M B
Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034, USA.
Stat Med. 1996 Jan 15;15(1):37-49. doi: 10.1002/(SICI)1097-0258(19960115)15:1<37::AID-SIM144>3.0.CO;2-0.
Prospective studies often involve rare events as study outcomes, and a primary concern is to identify risk factors and risk groups associated with the outcomes. We discuss practical solutions to risk factor analyses in prospective studies and address strategies to determine tree structures, to estimate relative risks, and to manage missing data in connection with some important epidemiologic problems. Some of the basic ideas for our strategies follow from work of Breiman, Friedman, Olshen, and Stone, although we propose extensions to their methods to resolve some practical problems that arise in implementation of these methods in epidemiologic studies. To illustrate these ideas, we analyse low birthweight associated risk factors with use of a data set from the Yale Pregnancy Outcome Study.
前瞻性研究常常将罕见事件作为研究结果，而一个主要关注点是识别与这些结果相关的风险因素和风险群体。我们讨论了前瞻性研究中风险因素分析的实际解决方案，并阐述了确定树状结构、估计相对风险以及处理与一些重要流行病学问题相关的缺失数据的策略。我们策略的一些基本思想源自布莱曼、弗里德曼、奥尔申和斯通的研究成果，不过我们对他们的方法进行了扩展，以解决在流行病学研究中实施这些方法时出现的一些实际问题。为了阐明这些观点，我们使用耶鲁妊娠结局研究的数据集分析了与低出生体重相关的风险因素。
