I'd like to plot a KM curve, but have very few events in the data set.This gives for a strange plot and i am wondering if it is possible to set the limits on the y-axis, highlighting the differences better.
Here is the dummy data:
set.seed(132456)
'dummy survival data'
df<-data.frame(id=seq(1,1000,1), event=rep(0,1000),time=floor(runif(1000,7,10)),group=floor(runif(1000,0,2)))
'set events for a few random subjects'
'only within the first 100 to check results more easily'
id_list<-c(as.numeric(floor(runif(10,1,100))))
df$event[df$id %in% id_list]<-1
'set survival times for events'
t_list<-c(as.numeric(floor(runif(8,1,5))))
df2<-df[df$event==1,]
df2
df2$time<-t_list
'combine data'
df<-rbind(df,df2)
summary(df)
'Set up surfit '
require(survminer)
KM_fit<-survfit(Surv(time , event) ~ 1 + strata(group),data= df)
ggsurvplot(KM_fit,
title="TEST",
risk.table = TRUE)
Any tips are much appreciated!