On Nov 11, 2010, at 3:44 AM, Michael Haenlein wrote:
Dear all,
I'm struggling with predicting "expected time until death" for a
coxph and
survreg model.
I have two datasets. Dataset 1 includes a certain number of people
for which
I know a vector of covariates (age, gender, etc.) and their event
times
(i.e., I know whether they have died and when if death occurred
prior to the
end of the observation period). Dataset 2 includes another set of
people for
which I only have the covariate vector. I would like to use Dataset
1 to
calibrate either a coxph or survreg model and then use this model to
determine an "expected time until death" for the individuals in
Dataset 2.
For example, I would like to know when a person in Dataset 2 will
die, given
his/ her age and gender.
I checked predict.coxph and predict.survreg as well as the document "A
Package for Survival Analysis in S" written by Terry M. Therneau but
I have
to admit that I'm a bit lost here.
The first step would be creating a Surv-object, followed by running a
regression that created a coxph-object, using dataset1 as input. So
you should be looking at:
?Surv
?coxph
There are worked examples in the help pages. You would then run
predict() on the coxph fit with "dataset2" as the newdata argument.
The default output is the linear predictor for the log-hazard relative
to a mean survival estimate but other sorts of estimates are possible.
The survfit function provides survival curve suitable for plotting.
(You may want to inquire at a local medical school to find
statisticians who have experience with this approach. This is ordinary
biostatistics these days.)
--
David.
Could anyone give me some advice on how this could be done?
Thanks very much in advance,
Michael
Michael Haenlein
Professor of Marketing
ESCP Europe
Paris, France
David Winsemius, MD
West Hartford, CT
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