# R-commands for Kaplan-Meier estimates
# =====================================

# For illustration we will use the melanoma data for patients 
# with ulceration (treating deaths from other causes as censorings).

# We first read the data:
melanoma=read.table("http://www.uio.no/studier/emner/matnat/math/STK4080/h12/melanoma.txt",header=T)

# We use the survival library, so this has to be loaded.

# We compute and plot the Kaplan-Meier estimate with the 
# standard confidence intervals (3.29):
fit.u=survfit(Surv(lifetime,status==1)~1,data=melanoma,
              subset=(ulcer==1), conf.type="plain")
plot(fit.u,mark.time=F,xlim=c(0,10),ylim=c(0,1),
     xlab="Years since operation")

# The summary command lists the Kaplan-Meier estimates with 
# standard errors (Greenwood) and confidence intervals:
summary(fit.u)

# The options type="fl" and type="fh2" to the survfit command 
# give the survival estimate as exp(-Nelson-Aalen). 
# The options differ in the way they handle tied failure times 
# [type "fl" uses (3.13) in the ABG-book, while type "fh2" uses (3.12)].

# To get the log-log transformed confidence intervals (3.30) 
# we use the survfit command with option conf.type="log-log"


# The print command gives a crude summary including an estimate 
# of the median survival time with confidence intervals
print(fit.u)

The option rmean=10 to the print command gives an estimate of 
# the restricted mean for the interval [0,10] with standard error.