DOSE-RESPONSE AND TREND ANALYSIS IN EPIDEMIOLOGY - ALTERNATIVES TO CATEGORICAL ANALYSIS
DOSE-RESPONSE AND TREND ANALYSIS IN EPIDEMIOLOGY - ALTERNATIVES TO CATEGORICAL ANALYSIS
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DOI：
10.1097/00001648-199507000-00005
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发表时间：
1995-07-01
期刊：
影响因子：
5.4
通讯作者：
GREENLAND, S
中科院分区：
文献类型：
--
作者：
GREENLAND, S
标准的分类分析是基于一个不切实际的剂量反应和趋势模型，没有有效利用类别内的信息。本文介绍了两类简单的替代方案，可以实现任何回归软件：分数多项式回归和样条回归。这些方法都说明了在人类免疫缺陷病毒发病率的历史趋势估计的问题。分数多项式和样条回归是特别有价值的，当重要的非线性预期和更一般的非参数回归方法的软件是不可用的。
Standard categorical analysis is based on an unrealistic model for dose-response and trends and does not make efficient use of within-category information. This paper describes two classes of simple alternatives that can be implemented with any regression software: fractional polynomial regression and spline regression. These methods are illustrated in a problem of estimating historical trends in human immunodeficiency virus incidence. Fractional polynomial and spline regression are especially valuable when important nonlinearities are anticipated and software for more general nonparametric regression approaches is not available.