The Cox model predicts two things: the relative hazard (death rate) associated with each variable, and a predicted survival curve for any particular variable combination.
The predicted survival curve will look like a Kaplan-Meier curve: multiple small steps, and will only rarely go all the way to zero. There is not a natural way to give "a predicted survival time" for each subject. There isn't any program to do what you ask because there isn't a good answer to "what" it should compute. This troublesome fact has led to a lot of work to define some residuals for a Cox model in other ways: see chapters 4-7 of the book by Therneau and Grambsh for a partial summary of ideas. (A little too much to summarize in an email). Terry Therneau ---- begin included message ---- I would like to produce a plot like the attached - although simplified to actual vs. Predicted survival time with distinguishing marks for censored and observed points. I have a dataset and have fitted a Cox model to it. In an attempt to visualise how accurate the model is it would be ideal if I could plot the actual survival times against the predicted survival times. I have been looking on the internet to see if there are ways to do this in R. The only post I found (https://stat.ethz.ch/pipermail/r-help/2009-February/189888.html) that seemed directly relevant suggested that I shouldn't be generating survival times at all. Given that, I was concerned about proceeding but I would like to have access to a plot to make a decision on its usefulness. .... ______________________________________________ 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.
