[R] what is the difference between survival analysis and (...)

[Eric Elguero]

Hi everybody,

recently I had to teach a course on Cox model, of which I am
not a specialist, to an audience of medical epidemiologists.
Not a good idea you might say.. anyway, someone in the
audience was very hostile. At some point, he sayed that
Cox model was useless, since all you have to do is count
who dies and who survives, divide by the sample sizes
and compute a relative risk, and if there was significant
censoring, use cumulated follow-up instead of sample
sizes and that's it!
I began arguing that in Cox model you could introduce
several variables, interactions, etc, then I remembered
of logistic models ;-)
The only (and poor) argument I could think of was that
if mr Cox took pains to devise his model, there should
be some reason...

but the story doesn't end here. When I came back to my office,
I tried these two methods on a couple of data sets, and true,
crude RRs are very close to those coming from Cox model.

hence this question: could someone provide me with a
dataset (preferably real) where there is a striking
difference between estimated RRs and/or between
P-values? and of course I am interested in theoretical
arguments and references.

sorry that this question has nothing to do with R
and thank you in advance for your leniency.

Eric Elguero
GEMI-UMR 2724 IRD-CNRS,
Équipe "Évolution des Systèmes Symbiotiques"
911 avenue Agropolis, BP 64501,
34394 Montpellier cedex 5 FRANCE