I have used the 'crr' function to fit the 'proportional subdistribution
hazards' regression model described in Fine and Gray (1999).
dat1 is a three column dataset where:
- ccr is the time to event variable
- Crcens is an indicator variable equal to 0 if the event was achieved, 1
if the event wasn't acheived due to death or 2 if the event wasn't achieved
due to disease progression
- pre is an indicator variable (and the covariate of interest)
I want to investigate if pre has a significant impact on time to event for
patients who died and for those who suffered disease progression (as well
as it's impact on the overall time to event).
In these cases I get p-values of 0 and 0.66 respectively.
What I would now like to do, is to plot two cumulative incidence curves -
one for the 'pre' variable status for patients who didn't acheive the event
due to death and one for those who didn't achieve it due to progression.
How can I do this? I can only see things involving plot.predict.crr which
doesn't seem to be what I need?