On Jun 15, 2010, at 1:34 PM, Federico Calboli wrote:
Hi everyone,
I'm running a cox ph model on a dataset with a number of variables.
Each variable has a different number of missing data, so that
coxph() drops the individuals who are missing data at one or more
variables. Because of this dropping (totally fine btw) I want to
know how many events I am left with in the model. Is there a way of
extracting them from the coxph() fit? or in any other reasonably
efficient way?
Ideas:
a) This is perhaps "cheating", but I use Harrell's rms function cph()
which reports that number (as well as the number of missing from each
variable) by default as part of the print()-ed version of the cph-
object.
b) I would have thought that summing events after applying
complete.cases() to a subset containing just the variables of interest
would have done the job, if you wanted to remain "true" to "survival".
c) Or you could look at the older version of Harrell's work in the
Design package to see how he extracted the event count, since I
believe it made a call to cph().
d) Using the cph second example I seem to be getting success with
assigning the results of coxph call to cox.obj and doing:
> sum(cox.obj$y[,3])
[1] 7
Best,
Federico
--
Federico C. F. Calboli
David Winsemius, MD
West Hartford, CT
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
