One approach is to use the rms package's cph and Mean.cph functions. Mean.cph (cph calls coxph and can compute Kaplan-Meier and other survival estimates) can compute mean restricted life. Frank
Dinesh W wrote > I am using survfit to generate a survival curve. My population is such > that my x axis is in days and i have a starting population of say 10,000 > of which say only 2000 are left as of day 365. When I try to print rmean > it does not print and in any case I am not interested in that. I actually > want to sum up all the daily survival values starting at 1.0 (S_0) for day > 1 through 0.2 (S_365) through day 365. I then want to assume "r% retained > each day" and compute the remaining integral as sum of a geometric series > through infinity ( (S_365 * r) * 1/(1-r) ) or through a specific future > time period (730 for example in which case the summation portion 1/ (1-r) > would change). Is there an easy way to do this? ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/rmean-in-survfit-tp4667668p4667708.html Sent from the R help mailing list archive at Nabble.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.
