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Re: st: Correcting for self selection

From   Maarten buis <[email protected]>
To   [email protected]
Subject   Re: st: Correcting for self selection
Date   Fri, 28 Jan 2011 08:20:52 +0000 (GMT)

--- On Fri, 28/1/11, [email protected] wrote:
> Based on an unbalanced panel data set of organizations
> competing with projects in a monthly competition, I try to
> model the likelihood of an organization winning (binary
> outcome) given explanatory variables. However, the
> organizations with the highest scores on the main
> explanatory variables (orgs a) participate more often in the
> contest than organizations with lower scores (orgs b).
> Since (orgs a) participate often, they enter many projects
> that lose and some projects that win. As a consequence, even
> though (orgs a) win the most in the contest overall, the
> models produce negative coefficients for these (orgs a)
> organizations.

Warning, this is just loose association on my part, so treat 
this post as a suggestion on where you could look for a possible 
answer and not as "the answer" or even "a answer".

What you want to do looks to me a lot like what people do when
they enter an offset to their -logit- or -poisson- model: some
units are longer or more often exposed to the risk than others.
I have never been in a position where I had data where I needed
to use this, so I only know it from reading about it, hence the
warning above. I have the impression this trick is more commonly
used in medical/biological fields, so maybe someone from these
fields can shed some light on this.

Hope this helps,

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


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