postscript("l02.ps")
larynx<-as.data.frame( scan("larynx.dat", 
   what=list(stage=0,time=0,y1=0,y2=0,status=0)))
wean<-as.data.frame(scan("bfeed.dat",
   what=list(time=0,state=0,race=0, poverty=0,smoked=0,
      alcohol=0,age=0,year=0,edu=0,prenatal=0)))
#****************************************************/
#* Kaplan--Meier curve for the combined larynx data */
#****************************************************/
library(survival)
sf.larynx<-survfit(Surv(larynx$time,larynx$status),
   conf.type="none")
summary(sf.larynx)
print(sf.larynx)
plot(sf.larynx,main="Larynx Tumor Survival")
plot(survfit(Surv(larynx$time,larynx$status),
      conf.type="plain"), main="Larynx Tumor Survival",
   sub="Confidence Interval on Raw Scale")
#*******************************************************/
#* Draw confidence intervals for the survival function */
#* of weaning two ways. Do this on a subset whose      */
#* mothers smoked and drank.                           */
#*******************************************************/
alch<-wean[(wean$alcohol==1)&(wean$smoked==1),]
sf<-survfit(Surv(time,status),data=larynx,conf.type="plain")
summary(sf)
print(sf)
plot(sf,main='Plot of weaning with confidence limits')
# We can skip conf.type argument below, since log is default.
plot(survfit(Surv(time,status),data=larynx, conf.type="log"),
   main="Plot of weaning with log scale confidence limits")
#********************************************************/
#* Plot Nelson-Aalen estimator of the cumulative hazard */
#********************************************************/
plot(survfit(coxph(Surv(alch$time,alch$state)~1)), 
   fun="cumhaz")