#Commands to Practical exercise 2
# Read the data into R and attach survival library
leukemia=read.table("http://www.math.uio.no/~borgan/abg-2008/data/leukemia.txt", header=T)
library(survival)
# a) Different survival function estimates:
# Kaplan-Meier (default)
fit.ka=survfit(Surv(time,status)~treat, data=leukemia, type="ka", conf.type="none")
summary(fit.ka)
# exp{-Nelson-Aalen } with Nelson-Aalen given by (3.13):
fit.fl=survfit(Surv(time,status)~treat, data=leukemia, type="fl", conf.type="none")
summary(fit.fl)
# exp{-Nelson-Aalen } with Nelson-Aalen given by (3.12):
fit.fh=survfit(Surv(time,status)~treat, data=leukemia, type="fh", conf.type="none")
summary(fit.fh)
# Compare results:
cbind(fit.ka$surv, fit.fl$surv,
fit.fh$surv)
plot(fit.ka,mark.time=F)
lines(fit.fh,mark.time=F,lty=2)
lines(fit.fl,mark.time=F,lty=3)
# Note that fit.ka$surv <= fit.fh$surv
<= fit.fl$surv
# b) Different standard error estimates:
# Greenwood (default)
fit.g=survfit(Surv(time,status)~treat, data=leukemia, error="g", conf.type="none")
summary(fit.ka)
# Standard error estimate using (3.27):
fit.t=survfit(Surv(time,status)~treat, data=leukemia, error="t", conf.type="none")
summary(fit.fl)
# Comparison of standard
error estimates:
cbind(fit.g$surv*fit.g$std.err,
fit.g$surv*fit.t$std.err)
# Note that (e.g.) fit.g$std.err gives the standard error estimate divided by
estimated survival