Sta678 Handout #1: Estimating survival curves 

library(survival)

pbc<-matrix(scan('http://www-rohan.sdsu.edu/~jjfan/sta678/pbcS.txt'),
  byrow=T,ncol=20)
> dim(pbc)  # 418  20
case<-pbc[,1]
time<-pbc[,2]
status<-pbc[,3]
delta<-(status==2)
trt<-pbc[,4]

case
time
table(status)
#0=alive, 1=liver transplant, 2=dead
table(delta)
table(trt)

help(survfit)

# Nelson-Aalen estimator of survival function
#fitNA<-survfit(Surv(time,delta)~1,subset=(case<=312), type='fleming')
#summary(fitNA)
#plot(fitNA)

# Kaplan-Meier
fitKM<-survfit(Surv(time,delta)~1,subset=(case<=312), type='kaplan',
 conf.type='log-log')
fitKM
summary(fitKM)
plot(fitKM)
plot(fitKM, xlab='time (days)', ylab='survival probability')