Marc, Thank you so much! Your solution is perfect! I hadn't known about the "cut" function. The graph is precisely what I needed. I have the ISwR book but not anything more advanced. Need to get some more advanced books, maybe?
I have been stubbornly working on this for a few hours now, and getting nowhere. I wish I were able to repay in some way. Thank you! Greg -----Original Message----- From: Marc Schwartz [mailto:[EMAIL PROTECTED] Sent: Thursday, May 03, 2007 12:18 AM To: Gregory Pierce Cc: [EMAIL PROTECTED] Subject: Re: [R] Survival statistics--displaying multiple plots Greg, I suspect that you want something like this: Use the 'aml' dataset and create a 'meld' column with random values from 1:25: library(survival) set.seed(1) aml$meld <- sample(25, 23, replace = TRUE) > aml$meld [1] 7 10 15 23 6 23 24 17 16 2 6 5 18 10 20 13 18 25 10 20 24 6 [23] 17 Now use cut() to create a 3 level factor from the values in 'meld': aml$meld.grp <- cut(aml$meld, breaks = c(-Inf, 10, 20, Inf)) > aml$meld.grp [1] (-Inf,10] (-Inf,10] (10,20] (20, Inf] (-Inf,10] (20, Inf] [7] (20, Inf] (10,20] (10,20] (-Inf,10] (-Inf,10] (-Inf,10] [13] (10,20] (-Inf,10] (10,20] (10,20] (10,20] (20, Inf] [19] (-Inf,10] (10,20] (20, Inf] (-Inf,10] (10,20] Levels: (-Inf,10] (10,20] (20, Inf] Now, let's do the plot, grouping by 'meld.grp': plot(survfit(Surv(time, status) ~ meld.grp, data = aml), col = 1:3, legend.text = levels(aml$meld.grp), legend.pos = 1) If this is close, see ?cut for creating a factor from a continuous vector. You can of course further tweak the plot aesthetics as you desire. HTH, Marc Schwartz On Wed, 2007-05-02 at 23:14 -0400, Gregory Pierce wrote: > I should clarify. I can generate plots for each category individually but > not for all three on the same chart. > > Greg > > -----Original Message----- > From: Gregory Pierce [mailto:[EMAIL PROTECTED] > Sent: Wednesday, May 02, 2007 10:21 PM > To: '[EMAIL PROTECTED]' > Subject: Survival statistics--displaying multiple plots > > Hello all! > > I am once again analyzing patient survival data with chronic liver disease. > > The severity of the liver disease is given by a number which is continuously > variable. I have referred to this number as "meld"--model for end stage > liver disease--which is the result of a mathematical calculation on > underlying laboratory values. So, for example, I can generate a Kaplan-Meier > plot of patients undergoing a TIPS procedure with the following: > > >plot(survfit(Surv(days,status==1),subset(tips,meld<10)) > > where "tips" is my data set, "days" is the number of days alive, and meld is > the meld score. > > What I would like to do is display the survival graphs of patients with > meld<10, 10<meld<20, and meld>20. I am unsure about how to go about this. > > Any suggestions would be appreciated. > > Greg > > ______________________________________________ > [EMAIL PROTECTED] 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. ______________________________________________ [EMAIL PROTECTED] 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. ______________________________________________ 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.