[R] Proportional Hazard Function and Competing risks

[Ravi Varadhan]

Hi,

If you are interested in building regression models for the sub-distribution
functions (or cumulative incidence function), then you may want to look at
the "cmprsk" package by Gray.  It is based on the article: Fine and Gray
(JASA 1999).  There is also the approach based on multi-state models (see
the work of the Danish group led by Andersen) for modeling state
probabilities.

If you are interested only in the cause-specific hazard models, then you
don't need anything other than the standard Cox relative risk model or
something like that, where events from other causes are simply treated as
censoring.

If, however, you are interested in the net hazard or net probabilities, then
you enter the dangerous and highly controversial realm of the "classical"
competing risk problem.  You have to overcome a lot of conceptual,
philosophical, and statistical (e.g. identifiability) issues, before
attempting to model it using latent failure time models.  For a cogent
critique of this approach, see Prentice et al. (Biometrics 1978).  Crowder's
(2001) book presents a somewhat more pragmatic view of the classical
competing risks problem.

Hope this helps,
Ravi.

--------------------------------------------------------------------------
Ravi Varadhan, Ph.D.
Assistant Professor,  The Center on Aging and Health
Division of Geriatric Medicine and Gerontology
Johns Hopkins University
Ph: (410) 502-2619
Fax: (410) 614-9625
Email:  rvaradhan at jhmi.edu
Webpage: http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html 
--------------------------------------------------------------------------

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-
> bounces at stat.math.ethz.ch] On Behalf Of Thomas Lumley
> Sent: Tuesday, July 11, 2006 10:56 AM
> To: Sharon.Mazurel at ing.com
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] Proportional Hazard Function and Competing risks
> 
> On Tue, 11 Jul 2006, Sharon.Mazurel at ing.com wrote:
> > How can I model coxph() in combination with competing risks
> >
> > i.e. I have two events and for event the object will leave the data set.
> > So :
> >
> > Coxph(Surv(time,event)~....) the event is for all my objects 1.
> >
> > How can I model this?
> 
> There is nothing built in. Some proposals for competing risks analysis
> involve Cox models and generalized linear models and so can be implemented
> in R.  It depends on what you want to do -- there isn't a standard
> solution because a lot of what people want to do with competing risks is
> provably impossible.
> 
>  	-thomas
> 
> Thomas Lumley			Assoc. Professor, Biostatistics
> tlumley at u.washington.edu	University of Washington, Seattle
> 
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