pbc {SMPracticals} | R Documentation |
Followup of 312 randomised and 108 unrandomised patients with primary biliary cirrhosis, a rare autoimmune liver disease, at Mayo Clinic.
data(pbc)
A data frame with 418 observations on the following 20 variables.
Fleming, T. R. and Harrington, D. P. (1991) Counting Processes and Survival Analysis. Wiley: New York.
Davison, A. C. (2003) Statistical Models. Cambridge University Press. Page 549.
data(pbc) # to make version of dataset used in book pbcm <- pbc[(pbc$trt!=-9),] pbcm$copper[(pbcm$copper==-9)] <- median(pbcm$copper[(pbcm$copper!=-9)]) pbcm$platelet[(pbcm$platelet==-9)] <- median(pbcm$platelet[(pbcm$platelet!=-9)]) attach(pbcm) library(survival) par(mfrow=c(1,2),pty="s") plot(survfit(Surv(time,status)~trt),ylim=c(0,1),lty=c(1,2), ylab="Survival probability",xlab="Time (days)") plot(survfit(coxph(Surv(time,status)~trt+strata(sex))),ylim=c(0,1),lty=c(1,2), ylab="Survival probability",xlab="Time (days)") lines(survfit(coxph(Surv(time,status)~trt)),lwd=2) # proportional hazards model fit fit <- coxph(formula = Surv(time, status) ~ age + alb + alkphos + ascites + bili + edtrt + hepmeg + platelet + protime + sex + spiders, data=pbcm) summary(fit) step.fit <- step(fit,direction="backward")