# R/a.up.low.fun.R In km.ci: Confidence intervals for the Kaplan-Meier estimator

```"a.up.low.fun" <-
function(survi, tl, tu)
{
# Calculates the indices used to derive the critical value
# determining a Hall-Wellner band. It takes the a survfit object
# and returns the values belonging to the two timepoints
# and a matrix with time, the Kaplan-Meier estimator, the sigmas
# (the sum in Greenwoods formula) and the std. error.
# t1 should be at least the smallest time, tu the smaller or equal
# than the highest time.

survi <- survi
n <- survi\$n
time <- survi\$time
kap.mei <- survi\$surv
indices <- (1:length(time))[survi\$n.event>0]
n.risk <- survi\$n.risk
n.event <- survi\$n.event
a <- n.event/(n.risk*(n.risk-n.event))
a <- cumsum(a)
var.st <- kap.mei^2*a
std.err <- sqrt(var.st)
sigma <- var.st/kap.mei^2
index.low <- max((1:length(time))[(time-tl)<=0])
index.up <-  max((1:length(time))[(time-tu)<=0])
sigma.low <- sigma[index.low]
sigma.up <- sigma[index.up]
al <- n*sigma.low/(1+n*sigma.low)
au <- n*sigma.up/(1+n*sigma.up)
return(list(a.low=al,a.up=au,sigma.mat=cbind(time,kap.mei,sigma,std.err)
,start=index.low,end=index.up))
}
```

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km.ci documentation built on May 2, 2019, 2:46 a.m.