R help - Feb 2009 - predicting cumulative hazard for coxph using predict

Hi
I am estimating the following coxph function with stratification and
frailty?where each person had multiple events.

m<-coxph(Surv(dtime1,status1)~gender+cage+uplf+strata(enum)+frailty(id),xmodel)
?
> head(xmodel)
       id enum        dtime status gender     cage uplf
1 1008666    1 2259.1412037      1     MA    0.000    0
2 1008666    2   36.7495023      1     MA 2259.141    0
3 1008666    3    0.3026852      1     MA 2295.891    0
4 1008666    4   46.7493287      1     MA 2296.193    0
5 1008666    5   61.9772917      1     MA 2342.943    0
6 1008666    5  100.9964815      1     MA 2404.920    0


If I estimate predict(m,newdata,type="lp") does the output include
xbeta or does it include xbeta+frailty term?
?
I want to predict the cumulative hazard for each person for their next event at
a given time in future.What is the best way to compute it?

Currently I am doing it by pulling the different elements and putting them
together using my own code.
For example, I get the cumulative baseline hazard from the basehaz function
bh<-basehaz(m)
bh$hazard for the strata in which the predicted event is and the time that
matches to the prediction time.
xbeta from predict function
xbeta<-predict(m,newdata,type="lp")
fval<-m$frail 

Regards
Zainab

> I am estimating the following coxph function with stratification and 
> frailty, where each person had multiple events.
> m <- coxph(Surv(dtime1,status1) ~ gender +cage +uplf+ strata(enum)+ 
>               frailty(id), xmodel)
>I want to predict the cumulative hazard for each person for their next event
at
> a given time in future.What is the best way to compute it? 
 There are two issues.  The first is that what you are asking for -- it is not 
at all clear to me exactly how this should be computed, and as a consequence the
coxph routines/documentation are not clear.  When there is a random effect in 
the model, should the baseline hazard be computed before or after integrating 
out the random effect?  How should one define the cumulative hazard for a 
subject?  These are hard questions, or at least I've found them so.
 
 What is currently done: The basline hazard is computed treating each of the 
fitted random effects (one per id) as it if were a known fixed value.  The 
predict function treats the random effects as just another coefficient, which is
clearly the wrong thing to do wrt a new subject who was not in the original data
set. 
   If you think of the frailty term as a shrinkage estimator, with no particular
connection to random effects, then what is currently done makes reasonable 
sense.  The "random effects" are just more coefficients in the model.
   
   Terry Therneau