On 22 Feb 2012, at 14:01, Terry Therneau wrote: > --- begin included message --- > I have a left truncated, right censored cox model: > > coxph(Surv(start, stop, censor) ~ x + y, mydata) > > I would like to know how much of the observed variance (as a number > between 0 and 1) is explained by each variable. How could I do that? > > Adding terms sequentially and then using anova(mod1, mod2) tells me > whether I get a significant improvement of the fit, but does not tell me > how much variance I actually explain? > > --------- end inclusion -------- > > There is not a "variance explained" in a Cox model, since it does not > try to predict the actual survival time. There are several proposals in > the literature for an "approximate" R^2. If you use summary(fit) it > will print one of the older ideas, which unfortuantely was shown by > later literature to not be a very good approach (replacing this is > another item on my long list of "someday fix"). At present your best > choice is to use the c-statistic, which is also printed out by summary.
I am now actually looking at the Schoenfeld residuals (which are calculated as a matter of fact by residuals()/resid()), and I am looking at Muller et al. Quantifying the contribution of genetic variants for survival phenotypes Genetic Epidemiology 2008 BW F -- Federico C. F. Calboli Neuroepidemiology and Ageing Research Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com ______________________________________________ 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.
