Reputation: 3242
To train with ggplot and to improve my skills in writing R functions I decided to build a series of functions that produces survival plots, with all kinds of extras. I managed to build a good working function for the basic survival plot, now I am getting to the extras. One thing I would like to do is an option that stacks an area plot of the number at risk at a given time point, on top of the survival plot. I would like it to look just like the facet_grid
option of ggplot, but I did not manage to do it with this function. I do not want the two plots binded, like we can do with grid.arrange
, but rather to have the same x-axis.
The following code produces the two (simplified) plots that I would like to stack on top of each other. I tried to do this with facet_grid
, but I don't think the solution lies in this
library(survival)
library(ggplot2)
data(lung)
s <- survfit(Surv(time, status) ~ 1, data = lung)
dat <- data.frame(time = c(0, s$time),
surv = c(1, s$surv),
nr = c(s$n, s$n.risk))
pl1 <- ggplot(dat, aes(time, surv)) + geom_step()
pl2 <- ggplot(dat, aes(time, nr)) + geom_area()
Upvotes: 11
Views: 9267
Reputation: 98429
First, melt your data to long format.
library(reshape2)
dat.long<-melt(dat,id.vars="time")
head(dat.long)
time variable value
1 0 surv 1.0000000
2 5 surv 0.9956140
3 11 surv 0.9824561
4 12 surv 0.9780702
5 13 surv 0.9692982
6 15 surv 0.9649123
Then use subset()
to use only surv
data in geom_step()
and nr
data in geom_area()
and with facet_grid()
you will get each plot in separate facet as variable
is used to divide data for facetting and for subsetting. scales="free_y"
will make pretty axis.
ggplot()+geom_step(data=subset(dat.long,variable=="surv"),aes(time,value))+
geom_area(data=subset(dat.long,variable=="nr"),aes(time,value))+
facet_grid(variable~.,scales="free_y")
Upvotes: 14