How do I specify a partially completed survival analysis model?

In reply to suggestion by David W., setting an offset parameter  
doesn't seem
to work as R is not recognizing the "X2" part of  coxph(
Surv(Time,Censor)~X1, offset=log(4.3*X2), data= a ). Also, here's some
sample data:

The problem, arising as a result of not having a dataset against which  
to test my memories of syntactic niceties, is that glm and coxph use  
different methods of supplying offsets. Thereau and Gramsch's book has  
examples, but if you did not have the book you still had alternatives.  
A bit of searching with the terms: coxph Therneau offset;  produced  
lots of hits for the occurrence of offset in warning messages so  
adding -warning to that search then produced a hit to the Google books  
look at T&G's text with a worked example:

 > a$logX2 <- log(a$X2)
 > coxph(Surv(Time,Censor)~X1 + offset(logX2), data= a )
Call:
coxph(formula = Surv(Time, Censor) ~ X1 + offset(logX2), data = a)

      coef exp(coef) se(coef)     z    p
X1 -0.885     0.413     1.43 -0.62 0.54

#Or just:

 > coxph(Surv(Time,Censor)~X1 + offset(log(4.3*X2)), data= a )
  X1         X2         Time            Censor
1   1 0.40619454  77.00666      0
2   1 0.20717868 100.00000      0
3   1 0.77360963  79.03463      1
4   1 0.62221954 100.00000      0
5   1 0.32191280 100.00000      0
6   1 0.73790704  72.84842      0
7   1 0.65012237 100.00000      0
8   1 0.71596105 100.00000      0
9   1 0.74787202  84.00172      0
10  1 0.66803790  41.65760      0
11  1 0.79922364  92.41999      0
12  1 0.76433736  90.99983      0
13  1 0.57014524 100.00000      0
14  1 0.39642235 100.00000      0
15  1 0.55756045 100.00000      0
16  0 0.60079340 100.00000      0
17  0 0.43630695 100.00000      0
18  0 0.09388013 100.00000      0
19  0 0.55956791 100.00000      0
20  0 0.52491597  97.71884      1

where we set the coefficient of X2 to be 8.

RWilliam wrote:
Sorry for being impatient but is there really no way of doing this  
at all?
It's quite urgent so any help is very much appreciated. Thank you.

RWilliam wrote:
Hello,

I just started using R to do epidemiologic simulation research  
using the
Cox proportional hazard model. I have 2 covariates X1 and X2 which  
I want
to model as h(t,X)=h0(t)*exp(b1*X1+b2*X2). I assume independence  
of X
from t.

After I simulate Time and Censor data vectors denoting the  
censoring time
and status respectively, I can call the following function to fit  
the
data into the Cox model (a is a data.frame containing 4 columns  
X1, X2,
Time and Censor):
b = coxph (Surv (Time, Censor) ~ X1 + X2, data = a, method =  
"breslow");

Now the purpose of me doing simulation is that I have another  
mechanism
to generate the number b2. From the given b2 (say it's 4.3), Cox  
model
can be fit to generate b1 and check how feasible the new model is.  
Thus,
my question is, how do I specify such a model that is partially  
completed
(as in b2 is known). I tried things like  
Surv(Time,Censor)~X1+4.3*X2, but
it's not working. Thanks very much.

-- 
View this message in context: http://old.nabble.com/How-do-I-specify-a-partially-completed-survival-analysis-model--tp26421391p26443562.html
Sent from the R help mailing list archive at Nabble.com.

______________________________________________
R-help at r-project.org 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.
David Winsemius, MD
Heritage Laboratories
West Hartford, CT

How do I specify a partially completed survival analysis model?

Thread (8 messages)