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Re: st: Survival function of regression Cox model postestimation


From   Maarten Buis <maartenlbuis@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Survival function of regression Cox model postestimation
Date   Mon, 11 Jul 2011 08:41:08 +0200

On Fri, Jul 8, 2011 at 8:13 PM,  <petretta@unina.it> 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.

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.

If this is new to you, try the example below:

*---------- begin example ----------
sysuse nlsw88, clear
gen ln_w = ln(wage)
sum ln_w
sum wage
di ln(r(mean))
*------------ end example ----------

Hope this helps,
Maarten

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


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