Re: Subject: Re: st: Survival function of regression Cox model postestimation

[Maarten Buis <maartenlbuis@gmail.com>]

--- On Fri, Jul 8, 2011 at 8:13 PM,  Mario Petretta wrote:
>>> I know that the baseline survival function of the Cox model without
>>> covariates is the same as the Kaplan Meier survival function.
>>> However, it is unclear for me why the survival function of a Cox model with
>>> covariates obtained at the mean values of the covariates is different from
>>> baseline survival function of the Cox model without covariates.

--- Maarten Buis answered
>> Because the relationship between the covariates and the survivor
>> function is a non-linear one. Remember that applying a non-linear
>> transformation to a variable x and than compute the mean is not the
>> same as computing the mean of variable x and than apply that
>> non-linear transformation.

--- On Tue, Jul 12, 2011 at 6:40 PM, Mario Petretta wrote me privately:
> Anyway, there is a rule for applying a non-linear transformation to a
> continuous covariate in order to obtain a survival function of a Cox model
> with that covariate obtained at its mean value not different from
> baseline survival function of the Cox model without covariates?

It is better to respond to the Statalist and not privately because if
you find my answer unclear, chances are that other people following
this thread may also find it unclear.

No, Cox regression has a baseline hazard function not a baseline
survival function, and the baseline hazard function is the hazards at
different points in time when all explanatory/independent/x-variables
are 0 not fixed at the mean.

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/