A Simple Approach for Fitting Linear Relative Rate Models in SAS
A Simple Approach for Fitting Linear Relative Rate Models in SAS
复制标题
DOI：
10.1093/aje/kwn278
复制
发表时间：
2008-12-01
影响因子：
5
通讯作者：
Richardson, David B.
中科院分区：
文献类型：
--
作者：
Richardson, David B.
线性相对率模型已用于各种环境和职业暴露的流行病学分析。与指数率模型相反，线性相对率模型意味着疾病的过度相对率随暴露以加性方式变化。线性相对速率模型可以使用EPICURE（HiroSoft International Corporation，西雅图，华盛顿）来拟合，EPICURE是一种广泛用于此类分析的专用统计软件包。在本文中，作者提出了一种使用 SAS 统计软件包（北卡罗来纳州卡里市 SAS Institute Inc.）中的 PROC NLMIXED 将线性相对率模型拟合到流行病学数据的简单方法。通过对南卡罗来纳州石棉纺织工人（1940-2001 年）死亡率研究数据的分析来说明这种方法。
The linear relative rate model has been employed in epidemiologic analyses of a variety of environmental and occupational exposures. In contrast to an exponential rate model, the linear relative rate model implies that the excess relative rate of disease changes in an additive fashion with exposure. The linear relative rate model may be fitted using EPICURE (HiroSoft International Corporation, Seattle, Washington), a specialized statistical software package widely used for such analyses. In this paper, the author presents a simple approach to fitting the linear relative rate model to epidemiologic data using PROC NLMIXED in the SAS statistical software package (SAS Institute Inc., Cary, North Carolina). This approach is illustrated via analyses of data from a study of mortality in a cohort of South Carolina asbestos textile workers (1940-2001).