Hey Josh, use |summary| to get estimates for specific times. E.g.:
|data(slopop) data(rdata) #calculate the relative survival curve #note that the variable year is given in days since 01.01.1960 and that #age must be multiplied by 365 in order to be expressed in days. rs <- rs.surv(Surv(time,cens)~sex+ratetable(age=age*365,sex=sex, year=year),ratetable=slopop,data=rdata) summary(rs, times = c(3, 5)*365.25) | Not sure what you mean about the validation part, but you might try estimating both EdererII and Pohar-Perme curves and see if they're similar. BR: Joonas 2015-11-06, 15:15, Josh Rosen kirjoitti: > Hello, > > I am trying to compute the relative survival curves for a cohort of cancer > patients that I have data on. I have been trying to use some of the > elements of the relsurv package and have gotten to the point where I have > built my US Life Table, and have my data set in the proper form and am able > to run rs.surv rs.add and rs.surv.add. I also think I have been able to > plot the appropriate survival curve using some code found online. However, > what I am wondering is how to best extract the 5-year (and 3-year) and > median relative survivals for my cohort. > > I am also trying to figure out the best way to then go about validating my > choices of method for relative survival computation as well. > > I am fairly new to R (usually use SAS) so any help that you can provide > would be greatly appreciated. > > Thank you! > -JR > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Epi@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-epi [[alternative HTML version deleted]] _______________________________________________ R-sig-Epi@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-epi
