Pepe M S, Whitaker R C, Seidel K
Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA.
Stat Med. 1999 Jan 30;18(2):163-73. doi: 10.1002/(sici)1097-0258(19990130)18:2<163::aid-sim11>3.0.co;2-f.
Studies examining the association between an outcome variable and multiple predictors are common in medical research. Examples include epidemiologic studies of risk factors for disease and clinical studies of prognostic indicators for diseased subjects. This paper is concerned with the assessment of the associations between the outcome and each predictor separately, the so-called univariate associations. Comparisons between predictors in regards to the strengths of their association with the outcome are considered. We show that though such comparisons cannot be made with standard techniques, they can be made using an algorithm which performs all of the univariate analyses simultaneously. This is accomplished with a non-standard application of generalized estimating equation methods. Comparisons of univariate associations are shown to be the key analyses of interest in a retrospective longitudinal study of childhood predictors of adult obesity. We illustrate the methodology on data from this study.
在医学研究中，考察一个结果变量与多个预测因素之间关联的研究很常见。例如，疾病危险因素的流行病学研究以及患病受试者预后指标的临床研究。本文关注的是分别评估结果与每个预测因素之间的关联，即所谓的单变量关联。还会考虑预测因素在与结果关联强度方面的比较。我们表明，虽然无法用标准技术进行此类比较，但可以使用一种能同时执行所有单变量分析的算法来进行。这是通过广义估计方程方法的非标准应用来实现的。在一项关于成人肥胖症儿童预测因素的回顾性纵向研究中，单变量关联的比较被证明是关键的感兴趣分析。我们用该研究的数据来说明这种方法。
