[R] Competing risks Kalbfleisch & Prentice method

[Terry Therneau]

Ravi's last note finished with
>  I am wondering why Terry Therneau's "survival" package doesn't
>  have this option.  

  The short answer is that there are only so many hours in a day.  

  I've recently moved the code base from an internal Mayo repository to R-forge, 
one long term goal with this is to broaden the developer base to n>2 (me and 
Thomas Lumley).  
  
  A longer statistical answer:
  
  I'm not sure if the "this" of Ravi's question is a. smoothed hazards, b. the 
K&P cumulative incidence or c. the Fine & Gray model.
  
  b. I like the CI model and am using it more.  We also have local code. The 
latest version of survival (on rforge, likely in the next default R release) has 
added simple CI curves to the survfit function.  Adding code for survfit on Cox 
models is on the todo list.  But -- this release also fixes up survfit.coxph to 
handle weighted Cox models and that was on my list for approx 10 years, i.e., 
don't hold your breath.  I don't release something until it also has a set of 
worked out test cases to add to the 'tests' directory.
  
  a. smoothed hazards.  For the case at hand I don't see any particular 
advantage of this.  On the other hand, I often would like to display hazard 
functions instead of CI functions for Cox models; with time dependent covariates 
I don't think a survival curve makes sense.  But I haven't had the time to think 
through exactly which methods should be added.
  
  c. Fine & Gray model, i.e., where covariates have a direct influence on the 
competing risk.  I find the model completely untenable from a biologic point of 
view, so have no interest in adding it.  (Due to finite time, everything in the 
survival package is code that I needed for an analysis; medical research is what 
pays my salary.)  Assume that I have competing processes/risks, say progression 
of a tumor and heart disease;  I expect that the tumor process pays no attention 
whatsoever to what is going on in the heart.  But this is necessary if 
"type=squamous" is modeled as an absolute beta=__ increase in the CI for cancer. 
 The squamous cells need to "step up the pace" of invasion if heart failure 
threatens, like jockeys in a horse race. 
  
   Terry T.