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On Mar 14, 2013, at 2:49 PM, array chip <arrayprof...@yahoo.com> wrote: > Hi, I am wondering how the confidence interval for Kaplan-Meier estimator is > calculated by survfit(). For example, > >> summary(survfit(Surv(time,status)~1,data),times=10) > Call: survfit(formula = Surv(rtime10, rstat10) ~ 1, data = mgi) > > time n.risk n.event survival std.err lower 95% CI upper 95% CI > 10 168 55 0.761 0.0282 0.707 0.818 > > > I am trying to reproduce the upper and lower CI by using standard error. As > far I understand, the default method for survfit() to calculate confidence > interval is on the log survival scale, so: That's not my understanding. I would have expected the estimates to be on a log-hazard scale ( continuous expression: log(deltaS/deltaT/S) ) > > upper CI = exp(log(0.761)+qnorm(0.975)*0.0282) = 0.804 > lower CI = exp(log(0.761)-qnorm(0.975)*0.0282) = 0.720 > > > they are not the same as the output from survfit(). > > Am I missing something? > > Thanks > > John > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. ______________________________________________ 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.
