Dear R-users, One can use the rcorr.cens function in Design to compute the C index when only the stop time is indicated (I think implicitely start=0 in that case). When the start and stop times are used in a Surv object, e.g.
library(Design) S=with(heart, Surv(start,stop,event)) the object returned is no longer a single number vector, so none of the following ways to compare a model fit to S makes sense: rcorr.cens(-cph(S~ age+transplant+surgery, heart)$linear.predictors, with(heart, Surv(start,stop,event))) # C Index Dxy S.D. n missing # 4.95e-01 -9.66e-03 7.15e-02 1.72e+02 0.00e+00 #this seems bad because it compares the fit to a different Surv than the one used to fit it (S, above) rcorr.cens(-cph(S~ age+transplant+surgery, heart)$linear.predictors, with(heart, Surv(stop-start,event))) # C Index Dxy S.D. n missing # 6.02e-01 2.03e-01 7.54e-02 1.72e+02 0.00e+00 Is there some way I can compute the correlation for this type of survival time specification in R? If not, does anybody have some tips on how to go about computing it myself? Many Thanks Eleni Rapsomaniki Research Associate Strangeways Research Laboratory Department of Public Health and Primary Care University of Cambridge ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
