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Re: st: correct for selection bias in survival analysis


From   Marguerite Duponchel <Marguerite.Duponchel@malix.univ-paris1.fr>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: correct for selection bias in survival analysis
Date   Wed, 05 May 2010 12:03:27 +0200

Thanks Maarten,

It's just that as I am the one creating the selection bias on a full available
sample, I thought there might be a way to correct it while using the info in
the complete data which frailty would not integrate. Am I wrong?

Quoting Maarten buis <maartenbuis@yahoo.co.uk>:

> --- On Wed, 5/5/10, Marguerite Duponchel wrote:
> > I am running a loglog survival analysis as such:
> >
> > streg duration_event vars, dist(loglog) cluster(y)
> >
> > I need to correct for a selection bias in the sample using
> > a probit on the probability of the event happening.
> >
> > probit event varsbis
> >
> > Does anyone know an easier way to correct for a potential
> > selection bias that calculating the IMR from the probit
> > and introducing it in the survival analysis as an
> > explanatory variable?
>
> The trick with including the inverse Mills ratio (I presume
> that that is what you mean with IMR) only works in linear
> models, so it won't work in survival models. You could
> instead take a look at the -frailty()- option in -streg-.
>
> 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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--
Marguerite Duponchel

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