#since event is a factor, survfit creates competing risk curves
pfit <- survfit(Surv(futime, event) ~ abo, transplant)
pfit[,2] #time to liver transplant, by blood type
plot(pfit[,2], mark.time=FALSE, col=1:4, lwd=2, xmax=735,
xscale=30.5, xlab="Months", ylab="Fraction transplanted",
xaxt = 'n')
temp <- c(0, 6, 12, 18, 24)
axis(1, temp*30.5, temp)
legend(450, .35, levels(transplant$abo), lty=1, col=1:4, lwd=2)
# competing risks for type O
plot(pfit[4,], xscale=30.5, xmax=735, col=1:3, lwd=2)
legend(450, .4, c("Death", "Transpant", "Withdrawal"), col=1:3, lwd=2)
Run the code above in your browser using DataLab