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cnfidence intervals for survfit()
2 messages · array chip, David Winsemius
Sent from my iPhone
On Mar 14, 2013, at 2:49 PM, array chip <arrayprofile at 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]]
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