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RE: st: testing differences between coefficients


From   Ebru Ozturk <ebru_0512@hotmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: testing differences between coefficients
Date   Thu, 20 Dec 2012 11:49:22 +0200

As far as I understand your e-mail, I want to do the comparison by looking at the difference. I do not do any group separation as I just focus on two different dependent variables. In terms of what is being compared (means, probabilities, odds etc.) I really do not know. How can I decide about that? or Does it depend on the model I use? 

> ----------------------------------------
> > Date: Thu, 20 Dec 2012 10:21:33 +0100
> > Subject: Re: st: testing differences between coefficients
> > From: maartenlbuis@gmail.com
> > To: statalist@hsphsun2.harvard.edu
> >
> > On Thu, Dec 20, 2012 at 9:58 AM, Ebru Ozturk wrote:
> > > Thank you Maarten. I looked at the examples given in Stata after suest. They also run testnl in Example 3 A nonlinear Hausman-like test. Do I need that?
> >
> > That depends on the exact hypothesis you are testing "the effects are
> > the same" is typically not precise enough, as you have to define what
> > you mean with "effect". Remember that an effect is a comparison of
> > (hypothetical or counterfactual) groups. So you need to define the
> > groups (probably the most important and most difficult decision),
> > what is being compared (means, probabilities, odds, latent scores,
> > ...), and how you want to do the comparison (difference or ratio).
> > Than you can look at the different kinds of statistical models to
> > figure out what "effect" they are estimating. Than you can decide
> > which one gets close enough to what you want to do (and its
> > limitations). Once you have done that, it will become obvious whether
> > you need a linear or non-linear test. So, the answer to this question
> > is that you really need to figure this one out for yourself, as you
> > are the only one who can make these decisions.
> >
> > > Another question is after suest test we get the results table and how do we interpret it? Do we just compare the coefficients for different models? For example, if one coefficient (variable) in X model is higher than the coefficient in Y model, the effect of this variable is greater for X model relative to Y model. Is this right interpretation?
> >
> > Again, this depends on what it is exactly you want to do, and what you
> > mean exactly with "effect". Once you have gone through the steps
> > specified above, the answer will be obvious. So, again you need to
> > figure this one out on your own, because it critically depends on
> > decisions only you can make.
> >
> > -- Maarten
> >
> > ---------------------------------
> > Maarten L. Buis
> > WZB
> > Reichpietschufer 50
> > 10785 Berlin
> > Germany
> >
> > http://www.maartenbuis.nl
> > ---------------------------------
> >
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