[R] Two ways to deal with age in Cox model

From: John Sorkin <jsorkin_at_grecc.umaryland.edu>
Date: Mon 05 Feb 2007 - 13:52:14 GMT

I hope one and all will allow a stats question:

When running a cox proportional hazards model ,there are two ways to deal with age,
including age as a covariate, or to include age as part of the follow-up time, viz,

Age as a covariate:

tetest1 <- list(time=  c(4, 3,1,1,2,2,3),
                     age= c(0, 2,1,1,1,0,0),
                     riskfactor=   c(0, 0,0,0,1,1,1))
 fitagecovariate<-coxph( Surv(time, status) ~ age +riskfactor, test1)  fitagecovariate

Age included as part of follow-up time:

 test2$timeplusage<-test2$time+test2$age  fitagefollowup<-coxph( Surv(timeplusage, status) ~ riskfactor, test2)  fitagefollowup

I would appreciate any thoughts about the differences in the interpretation of the two models.
One obvious difference is that in the first model (fitagecovariate) one can make inferences about age and in the second one cannot. I think a second
difference may be that in the first model the riskfactor is assumed to have values measured at the values of age where as in the second model riskfactor is assumed to have given values throughout the subject's life.

Your thoughts please.


R 2.1.1
windows XP

John Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
Baltimore VA Medical Center GRECC,
University of Maryland School of Medicine Claude D. Pepper OAIC, University of Maryland Clinical Nutrition Research Unit, and Baltimore VA Center Stroke of Excellence

University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
Baltimore, MD 21201-1524

(Phone) 410-605-7119
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