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Re: st: probit with interaction dummies (significance and marginal effects)


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: probit with interaction dummies (significance and marginal effects)
Date   Thu, 17 Jul 2008 17:13:47 +0100 (BST)

Regarding problem 1, this is just a matter of interpretation, as long
as you interpret the effects in terms of the effect on the latent
variable you are ok in simply using the output from -probit-, if you
want to interpret the results in terms of the probability you should
use -inteff-. 

Problem 2 is much harder to solve. Any solution would in one way or
another try to controll for things that haven't been observed. It
should not come as a surprise that that is hard (read: impossible). So,
the fact that "the solution" hasn't been implemented yet in Stata is
not so much a problem with Stata but with the state of the statistical
science: we know the problem, but we just don't know the answer. Though
Rich Williams discusses one solution on his website.

-- Maarten

--- Andrea Bennett <mac.stata@gmail.com> wrote:
> Thanks for the link! Still, I wonder if there's really no Stata  
> command I could use to "simply" test if the interaction is
> significant and what influence (direction) it has on the dependent 
> variable. I'd be just rather surprised if this does not exist
> because it seems to me this is a very common issue in any regression
> design (interaction effects).

--- Maarten buis wrote:
> > There are two distinct issues when interpreting interaction effects
> > in a probit:
> >
> > 1) a significant positive (negative) interaction in terms of the  
> > latent
> > variable does not mean a significant positive (negative)
> > interaction effect in terms of the probability that y = 1.
> >
> > 2) The scale of the latent variable is identified by setting the
> > residual variance at 1. If the residual variance differs between
> > the groups than that means that the scale of the latent variable
> > differs between the groups and when comparing differences in
> > effects across the groups you are basically comparing apples and
> > oranges.


-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands

visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434

+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------


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