Adjusted survival curves. (Sample code here: https://rpubs.com/daspringate/survival ) Deep gratitude to Moderator/Admin! At David Winsemius prompt, more elegant working code:Thanks, Ted :) library(survival) library(survminer) df<-read.csv("F:/R/data/edgr-orig.csv", header = TRUE, sep = ";")
df2 <- df df2[,c('treatment', 'age', 'sex', 'stage')] <- lapply(df2[,c('treatment', 'age', 'sex', 'stage')], factor) model <- coxph (Surv(time = start, time2 = stop, event = censor)~ treatment + age + sex + stage, data = df2) treat <- with(df2, data.frame( treatment = levels(treatment), age = rep(levels(age)[1], 2), sex = rep(levels(sex)[1], 2), stage = rep(levels(stage)[1], 2))) plot(survfit(model, newdata = treat), las=1, xscale = 1.00, conf.int = TRUE, xlab = "Months after diagnosis", ylab = "Proportion survived", col = c("red", "green")) [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.