Looks like we can use Surv
and survfit
function in R to get 95% lower bound confidence interval by using
surv.fit <- survfit(...)
and get the 95% CI using
summary(surv.fit)
On Python, I tried something like kmf = KaplanMeierFitter()
and kmf.fit(T, event_observed=C)
Is there a way to get 95% lower bound CI on Python like R did?
Thanks!
Try using kmf.confidence_interval_
.