Logistic回归模型中连续变量交互作用的分析  

Interaction between continuous variables in logistic regression model

作　　者：邱宏[1] 余德新[1] 谢立亚[1] 王晓蓉[1] 付振明[1] 

机构地区：[1]香港中文大学公共卫生及基层医疗学院

出　　处：《中华流行病学杂志》2010年第7期812-814,共3页Chinese Journal of Epidemiology

摘　　要：Rothman提出生物学交互作用的评价应该基于相加尺度即是否有相加交互作用,而logistic回归模型的乘积项反映的是相乘交互作用.目前国内外文献讨论logistic回归模型中两因素的相加交互作用以两分类变量为主,本文介绍两连续变量或连续变量与分类变量相加交互作用可信区间估计的Bootstrap方法,文中以香港男性肺癌病例对照研究资料为例,辅以免费软件R的实现程序,为研究人员分析交互作用提供参考.Rothman argued that interaction estimated as departure from additivity better reflected the biological interaction. In a logistic regression model, the product term reflects the interaction as departure from multiplicativity. So far, literature on estimating interaction regarding an additive scale using logistic regression was only focusing on two dichotomous factors. The objective of the present report was to provide a method to examine the interaction as departure from additivity between two continuous variables or between one continuous variable and one categorical variable.We used data from a lung cancer case-control study among males in Hong Kong as an example to illustrate the bootstrap re-sampling method for calculating the corresponding confidence intervals.Free software R （Version 2.8.1） was used to estimate interaction on the additive scale.

关 键 词：LOGISTIC回归模型 连续变量 相加交互作用S指数 方法 Bootstrap 

分 类 号：R181.3[医药卫生—流行病学]