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[逻辑回归模型中连续变量之间的相互作用]

[Interaction between continuous variables in logistic regression model].

作者信息

Qiu Hong, Yu Ignatius Tak-Sun, Tse Lap Ah, Wang Xiao-rong, Fu Zhen-ming

机构信息

School of Public Health and Primary Care, Chinese University of Hong Kong, H.K.S.A.R.

出版信息

Zhonghua Liu Xing Bing Xue Za Zhi. 2010 Jul;31(7):812-4.

Abstract

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.

摘要

罗斯曼认为,以偏离可加性来估计的交互作用能更好地反映生物交互作用。在逻辑回归模型中,乘积项反映的是偏离可乘性的交互作用。到目前为止,关于使用逻辑回归在相加尺度上估计交互作用的文献仅关注两个二分因素。本报告的目的是提供一种方法,以检验两个连续变量之间或一个连续变量与一个分类变量之间偏离可加性的交互作用。我们以香港男性肺癌病例对照研究的数据为例,来说明用于计算相应置信区间的自助重抽样方法。使用免费软件R(版本2.8.1)在相加尺度上估计交互作用。

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