[R] How do I specify a partially completed survival analysis model?

[RWilliam]

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:

   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.
>> 
> 
> 

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