[R] predict.coxph

[Therneau, Terry M., Ph.D.]

Jim,
  I respectfully disagree, and there is 5 decades of literature to back
me up.  Berkson and Gage (1950) is in response to medical papers that
summarized surgical outcomes using only the observed deaths, and shows
important failings of the method.  Ignoring the censored cases usually
gives biased answers, often so badly so that they are misleading and
worse than no answer at all.  The PH model is surprisingly accurate in
acute disease (I work in areas like multiple myeloma and liver
transplant so see a lot of this) and is also used in economics (duration
of unemployment for instance), the accelerated failure time models have
proven very reliable predictors in industry work.  Censored linear
regression (e.g. "Tobit" model) is not uncommon.  I am not aware of any
cases where ignoring the censored cases gives a competitive answer.
Blindly using a coxph model without checking into or at least thinking
about the proportional hazards assumption is dangerous, but so is blind
use of any other model.

Terry T.

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Terry,

My point was that if you are asking the question:  What is the average
time to death based on a set of variables? The only logical approach for
calculating actual time to death is to use uncensored cases, because we
do not know the time to death for the censored cases and can only
estimate them.  While actual time to death for uncensored cases may not
be a very useful piece of information, it can indeed be calculated.
However, as you point out predicted values for time to death can be
estimated using the survival function which incorporates both censored
and uncensored data.  However, the assumption of proportional hazards is
rarely defensible.

Best,

Jim