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

David Winsemius dwinsemius at comcast.net
Fri Nov 20 16:15:54 CET 2009


On Nov 20, 2009, at 9:57 AM, David Winsemius wrote:

>
> On Nov 20, 2009, at 9:46 AM, 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.
>>
>
> The general method with glm's to specify a model with fixed  
> coefficients is to use an offset. I believe that the coxph function  
> also has that facility and seem to remember that Therneau uses  
> offsets in some of the examples he offers in his books and technical  
> reports.
>
> Perhaps:
> cmod <- coxph( Surv(Time,Censor)~X1, offset=4.3*X2, data= <dfname>  )

Or much more likely:
cmod <- coxph( Surv(Time,Censor)~X1, offset=log(4.3*X2), data=  
<dfname>  )

I forgot what scale I should be thinking on. Sorry.

-- 
David

>
> Further requests about specifics should be accompanied (as suggested  
> by the Posting Guide) by some code that sets up a reproducible  
> example.
>
> -- 
> David.
>>
>>
>> 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--tp26421391p26441878.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
>
> ______________________________________________
> 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




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