Eleni Rapsomaniki
2009-Feb-18 19:43 UTC
[R] Age as time-scale in a cox model-How to calculate x-time risk?
Dear R users, My question is more methodology related rather than specific to R usage. Using time on study as time in a cox model, eg: library(Design) stanf.cph1=cph(Surv(time, status) ~ t5+id+age, data=stanford2, surv=T) #In this case the 1000-day survival probability would be: stanf.surv1=survest(stanf.cph1, times=1000) #Age in this case is a covariate. #I now want to compare the above estimate to the 1000-day survival probability I get using age at entry and exit as my time-scale: stanf.cph2=cph(Surv(age,age+time, status) ~ t5+id, data=stanford2, surv=T) stanf.surv2=survest(stanf.cph2, times=1000) summary(stanf.surv1$surv) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.1131 0.3370 0.4669 0.4538 0.5633 0.7480 27.0000> summary(stanf.surv2$surv)Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.07387 0.23240 0.35770 0.35370 0.46820 0.60650 27.00000 These are obviously out-of sync, so there must be some way I can adjust them to mean the same thing. The first means the probability of surviving a 1000 days since they started being followed up while the second means the probability of surviving up to starting age+1000 days. How do I get the equivalent risks from the two models? Any tips greatly appreciated!! (FYI A related entry to my question can be found at: http://tolstoy.newcastle.edu.au/R/e2/help/07/02/9831.html) Eleni Rapsomaniki Research Associate Department of Public Health and Primary Care University of Cambridge [[alternative HTML version deleted]]
Dear R users, My question is more methodology related rather than specific to R usage. Using time on study as time in a cox model, eg: library(Design) stanf.cph1=cph(Surv(time, status) ~ t5+id+age, data=stanford2, surv=T) #In this case the 1000-day survival probability would be: stanf.surv1=survest(stanf.cph1, times=1000) #Age in this case is a covariate. #I now want to compare the above estimate to the 1000-day survival probability I get using age at entry and exit as my time-scale: stanf.cph2=cph(Surv(age,age+time, status) ~ t5+id, data=stanford2, surv=T) stanf.surv2=survest(stanf.cph2, times=1000) summary(stanf.surv1$surv) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.1131 0.3370 0.4669 0.4538 0.5633 0.7480 27.0000> summary(stanf.surv2$surv)Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.07387 0.23240 0.35770 0.35370 0.46820 0.60650 27.00000 These are obviously out-of sync, so there must be some way I can adjust them to mean the same thing. The first means the probability of surviving a 1000 days since they started being followed up while the second means the probability of surviving up to starting age+1000 days. How do I get the equivalent risks from the two models? Any tips greatly appreciated!! (FYI A related entry to my question can be found at: http://tolstoy.newcastle.edu.au/R/e2/help/07/02/9831.html) Eleni Rapsomaniki Research Associate Department of Public Health and Primary Care University of Cambridge