Note 6 - Stats for Clinical Trials, Math 150 Jo Hardin...

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Unformatted text preview: Stats for Clinical Trials, Math 150 Jo Hardin Survival Analysis, R code Apply survival functions in R using prostate cancer data with the following variables: Treatment group 1 = placebo; group 2 = 1mg diethylstilbestrol (DES) Time time died or censored Status 1 if censored; 0 if not censored Age in years Haem haemoglobin, iron containing protein, concentration measurement with normal levels in the teens g/dL Size of tumor, in mm Gleason score (ranges from 2 to 10 with 10 being the worst prognosis) Importing the data & using the survival library > library(survival) > prostate <- read.table("prostate.csv", header=T, sep=",") > attach(prostate) Fitting and plotting the Kaplan-Meier survival curve > pros.surv <- survfit(Surv(Time,Status)~Treatment) > plot(pros.surv, lty=2:3,xlab="time", ylab="survival function") > legend(10,.4, c("Treatment 1", "Treatment 2"),lty=2:3) 10 20 30 40 50 60 70 0.0 0.2 0.4 0.6 0.8 1.0 time survival function Treatment 1 Treatment 2 to plot only the first line...
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This note was uploaded on 02/17/2012 for the course MATH 151 taught by Professor Jo.h during the Fall '10 term at Pomona College.

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Note 6 - Stats for Clinical Trials, Math 150 Jo Hardin...

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