Howe G R, Chiarelli A M
NCIC Epidemiology Unit, University of Toronto, Ontario.
Int J Epidemiol. 1988 Jun;17(2):464-8. doi: 10.1093/ije/17.2.464.
A simple model is described for estimating power in cohort studies, in which the exposure is treated as a polytomous variable, with a known distribution in the population from which the sample is drawn. The model then requires the specification of the expected number of deaths which will occur in the cohort, calculated from the population rates, the dose-response relationship, and the size of the cohort. The model also allows for misclassification of exposure, the rule rather than the exception in epidemiological studies. The model is applied to a proposed study of saturated fat intake and risk of death from colorectal cancer in a male cohort drawn from the general population. It is demonstrated that this approach leads to an optimization of the power estimates, and in particular that maximization of power can be achieved by using a relatively small number of categories, eg four. It is also demonstrated that the effect of misclassification is less extreme if a polytomous dose-response model is used for analysis as compared to the usual simple dichotomous exposure model.
本文描述了一种用于队列研究中估计检验效能的简单模型。在该模型中，暴露被视为一个多分类变量，其在抽样总体中的分布是已知的。该模型接着需要根据总体发生率、剂量反应关系和队列规模来确定队列中预期的死亡数。该模型还考虑了暴露的错误分类，而这在流行病学研究中是常见而非个例。该模型应用于一项拟开展的研究，该研究旨在探讨从普通人群中抽取的男性队列中饱和脂肪摄入量与结直肠癌死亡风险之间的关系。结果表明，这种方法能够优化检验效能估计值，特别是通过使用相对较少的类别（如四个）就可以实现检验效能的最大化。研究还表明，与通常的简单二分暴露模型相比，使用多分类剂量反应模型进行分析时，错误分类的影响没那么严重。
