Ted Beginner (RStudio) r-subscribe at mail.ru
Mon Oct 9 11:52:12 CEST 2017

```Adjusted survival curves (Thanks to sample code:  https://rpubs.com/daspringate/survival )
Thanks to Moderator/Admin's Great Work! For a successful solution I used advice that could be understood:
1. Peter Dalgaard: The code does not work, because the covariates are not factors.
2. Jeff Newmiller: "Change the columns into factors before you give them to the coxph function, e.g. df\$treatment <- as.factor(df\$treatment)"
And I study David Winsemius's instructions.THANKS!!!
Code works:

library(survival)
library(survminer)

# "age" means the age groups
ID start stop censor sex age stage treatment
1   0    66    0     2   1   3     1
2   0    18    0     1   2   4     2
3   0    43    1     2   3   3     1
4   0    47    1     2   3   NA    2
5   0    26    0     1   4   3    NA

# Change continuous var. as factors
df\$sex<-as.factor(df\$sex)
df\$age<-as.factor(df\$age)
df\$stage<-as.factor(df\$stage)
df\$treatment<-as.factor(df\$treatment)

S <- Surv(
time = df\$start,
time2 = df\$stop,
event = df\$censor)

model <- coxph( S ~ treatment + age + sex + stage, data = df)

plot(survfit(model),
las=1,
xscale = 1.00,
xlab = "Months after diagnosis",
ylab = "Proportion survived",
main = "Baseline Hazard Curve")

treat <- with(df,
data.frame(
treatment = levels(treatment),
age = rep(levels(age), 2),
sex = rep(levels(sex), 2),
stage = rep(levels(stage), 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"))

legend(8, 0.9,
legend = c("Beta blockers",
"No beta blockers"),
lty = 1,
col = c("green", "red"))
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```