[R] cnfidence intervals for survfit()

[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
> 
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> 
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