Interaction between continuous variables in logistic regression model

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 u...

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Bibliographic Details
Published inZhōnghuá liúxíngbìng zázhì Vol. 31; no. 7; p. 812
Main Authors Qiu, Hong, Yu, Ignatius Tak-Sun, Tse, Lap Ah, Wang, Xiao-rong, Fu, Zhen-ming
Format Journal Article
LanguageChinese
Published China 01.07.2010
Subjects
Aged
Case-Control Studies
Confidence Intervals
Hong Kong
Humans
Logistic Models
Lung Neoplasms
Male
Middle Aged
Software
Hong Kong
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Summary: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.
ISSN:0254-6450