on 12/05/2008 09:10 PM Ritwik Sinha wrote:> Hi All,
>
> Please pardon me if I am missing something obvious here. How do I get
> the Kaplan-Meier estimate function that is created by survfit and
> plotted by the code.
>
> fit <- survfit(Surv(time, status) , data=aml)
> plot(fit)
>
> That is, I need a function that will give me the survival estimate at
> a given time: \hat{S}(t).
>
> Thanks in advance.
>
> Ritwik Sinha
See:
library(survival)
?summary.survfit
and note the 'times' argument.
fit <- survfit(Surv(time, status) , data = aml)
> summary(fit)
Call: survfit(formula = Surv(time, status), data = aml)
time n.risk n.event survival std.err lower 95% CI upper 95% CI
5 23 2 0.9130 0.0588 0.8049 1.000
8 21 2 0.8261 0.0790 0.6848 0.996
9 19 1 0.7826 0.0860 0.6310 0.971
12 18 1 0.7391 0.0916 0.5798 0.942
13 17 1 0.6957 0.0959 0.5309 0.912
18 14 1 0.6460 0.1011 0.4753 0.878
23 13 2 0.5466 0.1073 0.3721 0.803
27 11 1 0.4969 0.1084 0.3240 0.762
30 9 1 0.4417 0.1095 0.2717 0.718
31 8 1 0.3865 0.1089 0.2225 0.671
33 7 1 0.3313 0.1064 0.1765 0.622
34 6 1 0.2761 0.1020 0.1338 0.569
43 5 1 0.2208 0.0954 0.0947 0.515
45 4 1 0.1656 0.0860 0.0598 0.458
48 2 1 0.0828 0.0727 0.0148 0.462
> summary(fit, times = seq(0, 48, 6))
Call: survfit(formula = Surv(time, status), data = aml)
time n.risk n.event survival std.err lower 95% CI upper 95% CI
0 23 0 1.0000 0.0000 1.0000 1.000
6 21 2 0.9130 0.0588 0.8049 1.000
12 18 4 0.7391 0.0916 0.5798 0.942
18 14 2 0.6460 0.1011 0.4753 0.878
24 11 2 0.5466 0.1073 0.3721 0.803
30 9 2 0.4417 0.1095 0.2717 0.718
36 5 3 0.2761 0.1020 0.1338 0.569
42 5 0 0.2761 0.1020 0.1338 0.569
48 2 3 0.0828 0.0727 0.0148 0.462
HTH,
Marc Schwartz