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Plotting an adjusted survival curve

First a statistical issue: The survfit routine will produce predicted survival curves for 
any requested combination of the covariates in the original model.  This is not the same 
thing as an "adjusted" survival curve.  Confusion on this is prevalent, however.  True 
adjustment requires a population average over the confounding factors and is closely 
related to the standardized incidence ratio concept found in epidemiology.

To answer your technical question:
    fit <- coxph(Surv(.........
    mysurv <- survfit(fit, newdata= mydata)
This will give a set of predicted curves, one for each observation in mydata.  If we 
assume 2 treatments and 4 ethnicities, this means that there are 8 possible predicted 
curves.  You can certainly take the curves for "trt=1, white" and "trt=2, white", plot 
them together on one graph, and call this your "adjusted" survival curves; the mydata data 
set would have two observations.  This is not a correct label but is certainly common.

Terry Therneau
On 11/26/2012 05:00 AM, r-help-request at r-project.org wrote: