Re: st: Correcting for self selection

[Maarten buis <maartenbuis@yahoo.co.uk>]

--- On Fri, 28/1/11, erik.aadland@bi.no 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

--------------------------
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/