title: [Interaction between continuous variables in logistic regression model].
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.
authors.affiliation: School of Public Health and Primary Care, Chinese University of Hong Kong, H.K.S.A.R.
authors.forename: Hong
authors.initials: H
authors.lastname: Qiu
authors.forename: Ignatius Tak-Sun
authors.initials: IT
authors.lastname: Yu
authors.forename: Lap Ah
authors.initials: LA
authors.lastname: Tse
authors.forename: Xiao-rong
authors.initials: XR
authors.lastname: Wang
authors.forename: Zhen-ming
authors.initials: ZM
authors.lastname: Fu
mesh_terms: D000368:Aged; D016022:Case-Control Studies; D016001:Confidence Intervals; D006723:Hong Kong; D006801:Humans; D016015:Logistic Models; D008175:Lung Neoplasms; D008297:Male; D008875:Middle Aged; D012984:Software