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Re: st: Identifying interaction effect in probit


From   frone@ria.buffalo.edu
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Identifying interaction effect in probit
Date   Tue, 30 Mar 2010 12:58:42 -0400

> --- On Tue, 30/3/10, Urmi Bhattacharya wrote:
> > I am using a probit model and a few of my regressors are
> > continuous but most of them are dummy variables(takes
> > value 1 or 0).I also have interaction term for the dummy
> > variables in the probit model.
> > how do i find the estimated change in probability of
> > success if associated with the interaction term.i.e if
> > the interaction term is [siginificant]
> 

Maarten Buis reponded in part:


> This is actually a surprisingly hard question. There are
> two solutions: 
> 
> 1) You could use -inteff-, which you can download by 
> typing in Stata -findit inteff- and follow the links and 
> the instructions. This approach is discussed in Edward 
> Norton, Hua Wang and Chunrong Ai (2004) "Computing 
> interaction effects and standard errors in logit and 
> probit models", The Stata Journal, 4(2), p.p. 154--167. 
> <http://www.stata-journal.com/article.html?article=st0063>


For a different take on the issue, you might consider:


http://w4.stern.nyu.edu/economics/docs/workingpapers/2009/Interaction-Terms-in-Nonlinear-Models.pdf


http://ideas.repec.org/p/iza/izadps/dp3478.html



Mike Frone

****************************************************************
Michael R. Frone, Ph.D.
Senior Research Scientist
Research Institute on Addictions
State University of New York at Buffalo
1021 Main Street
Buffalo, New York 14203

Office:    716-887-2519
Fax:        716-887-2477
E-mail:     frone@ria.buffalo.edu
Internet: http://www.ria.buffalo.edu/profiles/frone.html
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