Hi, I've been banging my head against the following problem for a while and thought the fine people on r-help might be able to help. I'm using the survival package.
I'm studying the survival rate of a population with a preexisting linear-like event rate (there are theoretical reasons to believe it's linear, but of course it's subject to the usual sampling noise) Some of the population exhibit predictor X and some don't [I'm not trying to be cagey about the setting here, it's just complicated to explain and I'm trying to keep my message short.] When I plot the survival curves, there's a qualitatively significant difference and this is confirmed by survdiff. When I run cox.zph, however, it's pretty clear that the proportional hazards assumption isn't satisfied: > zph <- cox.zph(cox) > zph rho chisq p Initially.Vulnerable -0.0476 32.5 1.19e-08 > Similarly, when I do plot(zph), B(t) is fairly non-constant. This isn't inherently a problem for me. I don't need a hard single number to characterize the shape of the excess risk. However, I'd like to be able to say something qualitative about the shape of the excess risk for the predictor. E.g., is it linear, monotonically increasing, monotonially decreasing, etc. Is it safe to use the coxph diagnostic plot for this purpose? I did try heuristically subtracting out the background and then fitting a spline using locfit as described in the MASS supplement, but this seemed a little more ad hoc than I was hoping for something more principled. Thanks in advance. -Ekr ______________________________________________ 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.