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2011 Jun 13
0
How to formulate an (effect-modifying) interaction with matching variable in a conditional logistic regression?
...$smoke=="yes")*dataset$age multi2a.cl<-update(mult2.cl,.~.+ageNsmoke) summary(multi2a.cl) anova(mult2.cl,multi2a.cl) # but suppose I had a model with race, then I'd have to # define two variables dataset$ageNblack<-as.numeric(dataset$race=="black")*dataset$age dataset$ageNother<-as.numeric(dataset$race=="other")*dataset$age multi3.cl<-update(mult.cl,.~.+race:age) summary(multi3.cl) anova(multi3.cl, mult.cl) multi3.cl<-update(mult.cl,.~.+ageNblack+ageNother) summary(multi3.cl) anova(multi3.cl, mult.cl) # even more unwieldy with factors as matching vari...