[R] competing risks survival analysis
wsi at gcal.ac.uk
Thu Oct 26 11:11:32 CEST 2000
I will have data in the following form:
Time resp type stim type
300 a A
200 b A
155 a B
250 b B
80 c A
1000 d B
c is left censored observation; d is right censored
This sort of problem is discussed in Chap 9 of Cox & Oakes Analysis of
Survival Data under the name "competing risks".
Observations are obtained from n independent individuals in the form
(t_i,r_i;s_i) where t_i is the time of the event (failure), r_i is the
response type (failure type), and s_i is the stimulus type (explanatory
I am wondering if it is possible to use survfit5 to fit parametric and
nonparametric models to data like these, and if so how to do it. I
read the documentation for survfit5 and Surv() did not seem to allow for
the type of model I need. If I can't use survfit5, any suggestions on how
to proceed? I am pretty ignorant of survival analysis at this point.
(Maybe I can just do separate survival analysis runs for the type a and
type b responses?)
Thanks very much for any help.
PS In the end I would like to have a plot of phat_a(t) vs t: probablity of
a failure of type a as a function of time (just like Cox and Oakes fig
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