Nice trick. However what I´m looking for is a way to find the exact
time analytically from where the curves are parallel. I believe the PH
assumption is fulfilled before and after this point.
M
On Mon, Aug 31, 2009 at 12:44 AM, Maarten buis<[email protected]> wrote:
> --- On Sun, 30/8/09, moleps islon wrote:
>> I´m investigating the effect of a dichotomous variable on
>> survival. Looking at the graphs they are parallell after
>> the first 48 hrs, but there is a difference within the
>> first 48 hrs. Is it reasonable to present the cox
>> regression analysis with all the patients and then
>> discard the patients dead within 48 hrs and redo the
>> analysis-(this gives a significant effect in the first
>> analysis and non-significant in the latter as suspected
>> from the graphs)? Or is there a more analytical way to find
>> the exact time from which the two groups no longer differ?
>
> I would do something like in the example below. In this example
> the effect of age is allowed to change linearly over time for
> the first 10 months, and afterwards the proportional hazard
> assumption is maintained. The trick is that -(_t < 10)- is a
> logical statement, so it evaluates to 1 if it is true, and 0
> if it is false (for more on this, see:
> http://www.stata.com/support/faqs/data/trueorfalse.html ). So
> for the first 10 months age is interacted with 1*_t, while for
> the remaining months age is interacted with 0*_t. The effect
> age in "rh equation" is the effect of age after 10 months, i.e.
> after 10 months the hazard of death increased 12% for every
> year of age. The effect of age in t equation tells you that in
> the first 10 months the effect of age increased every month by
> .0033%.
>
> *--------- begin example -----------
> sysuse cancer, clear
> stset studytime, failure(died)
> xi: stcox i.drug age, ///
> tvc(age) texp((_t < 10)*_t)
> *---------- end example -------------
> ( For more on how to use examples I sent to statalist see:
> http://www.maartenbuis.nl/stata/exampleFAQ.html )
>
> 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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>
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