I am using the package Design for survival analysis. I want to plot a simple Kaplan-Meier fit of survival vs. age, with age grouped as quantiles. I can do this: survplot(survfit(Surv(time,status) ~ cut(age,3), data=veteran) but I would like to do something like this: survplot(survfit(Surv(time,status) ~ quantile(age,3), data=veteran) #will not work ideally I would like to superimpose estimates from cph models, which automatically fit the 2nd to 4rth quantiles for age, so I need the age groups to be grouped the same. Any help greatly appreciated! Eleni Rapsomaniki
survfit using quantiles to group age
2 messages · Eleni Rapsomaniki, Frank E Harrell Jr
Eleni Rapsomaniki wrote:
I am using the package Design for survival analysis. I want to plot a simple Kaplan-Meier fit of survival vs. age, with age grouped as quantiles. I can do this: survplot(survfit(Surv(time,status) ~ cut(age,3), data=veteran) but I would like to do something like this: survplot(survfit(Surv(time,status) ~ quantile(age,3), data=veteran) #will not work ideally I would like to superimpose estimates from cph models, which automatically fit the 2nd to 4rth quantiles for age, so I need the age groups to be grouped the same. Any help greatly appreciated! Eleni Rapsomaniki
This will result in a poor fitting model and residual confounding (by only partially adjusting for a variable; you are assuming a piecewise flat model). Use Surv( ) ~ strat(cut2(age,g=3)) ... For Design it is often better to do ageg <- cut2(age,g=3) # Donald Rumsfeld approach to using information f <- cph(Surv( ) ~ strat(ageg), ...) Frank
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University