Hi, I have the same question as Jason on how to estimate the standard error and construct CI around S_1(t) - S_2(t). From summary.survfit(obj), how can I combine the 2 survival estimates and the associated standard errors, to get an estimate of standard error for the difference / then calculate CI?

For example, my summary(obj) gave me:

                treatment=0 
        time       n.risk      n.event     survival      std.err lower 95% CI upper 95% CI 
     10.0000      69.0000      28.0000       0.7313       0.0438       0.6504       0.8223 

                treatment=1 
        time       n.risk      n.event     survival      std.err lower 95% CI upper 95% CI 
     10.0000      86.0000      10.0000       0.9055       0.0285       0.8514       0.9631 


The S_1(t=10) - S_2(t=1) = 0.9055-0.7313 = 0.1742. how to calculate the standard error this difference based on SD_1 = 0.0438 and SD_2 = 0.0285, and then the 95% CI for the difference?

Thanks

John



________________________________
 From: Thomas Lumley <tlumley@uw.edu>
To: Jason Connor <jconnor@alumni.cmu.edu> 
Cc: r-help@r-project.org 
Sent: Wednesday, March 7, 2012 10:58 AM
Subject: Re: [R] Difference in Kaplan-Meier estimates plus CI

On Thu, Mar 8, 2012 at 4:50 AM, Jason Connor <jconnor@alumni.cmu.edu> wrote:
> I thought this would be trivial, but I can't find a package or function
> that does this.
>
> I'm hoping someone can guide me to one.
>
> Imagine a simple case with two survival curves (e.g. treatment & control).
>
> I just want to calculate the difference in KM estimates at a specific time
> point (e.g. 1 year) plus the estimate's 95% CI.  The former is
> straightforward, but the estimates not so much.
>
> I know methods exist such as Parzen, Wei, and Ying, but was surprised not
> to find a package that included this.
>
> Before I code it up, I thought I'd ask if I was just missing it somewhere.

summary.survfit() in the survival package will give you the point
estimate and standard error, and then combining these into a
difference and confidence interval for the difference is easy.

   -thomas

-- 
Thomas Lumley
Professor of Biostatistics
University of Auckland

______________________________________________
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.
	[[alternative HTML version deleted]]

