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RE: st: test of significant between coefficients


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
Subject   RE: st: test of significant between coefficients
Date   Tue, 27 Sep 2011 15:49:50 -0400

I might suggest having a look at:
Gelman, A., & Stern, H. (2006). The difference between “significant” and “not significant” is not itself statistically significant. The American Statistician, 60(4), 328-331.http://www.stat.columbia.edu/~gelman/research/published/signif4.pdf

Cam
> Date: Tue, 27 Sep 2011 16:35:47 +0100
> Subject: Re: st: test of significant between coefficients
> From: njcoxstata@gmail.com
> To: statalist@hsphsun2.harvard.edu
> 
> Richard's answer overlaps with mine, which is fine.
> 
> I want to underline the idea that often coefficients should be thought
> as being bundled together. For example, if a cosine term is included
> in a model a sine term should be too. Leaving out one or the other can
> omit some useful information about phase even if one coefficient is
> not significant. A more widely familiar example is a set of
> indicators. Degrading them so that all are significant just coarsens a
> model.
> 
> Come to think of it, we've have had this discussion before. Just
> search for "Richard Williams" in the Statalist archives.
> 
> Nick
> 
> On Tue, Sep 27, 2011 at 3:48 PM, Richard Williams
> <richardwilliams.ndu@gmail.com> wrote:
> > At 10:35 AM 9/27/2011, Andrea Rispoli wrote:
> >>
> >> Dear Statalisters,
> >> I am running a test of significance between two coefficients of the
> >> same OLS regression.
> >> My question is : if the two coefficients are not significant, does it
> >> still make sense to conduct the test? I am asking because sometimes
> >> while the individual coefficients are not significant the difference
> >> between them is significant, so I was trying to understand the meaning
> >> of this result.
> >> Thank you!
> >> AR
> >
> > It can happen. The individual tests are testing whether the coefficients
> > equal zero. The equality test might be testing whether, say, -.5
> > significantly differs from .5. In any event, there is nothing that says all
> > your tests have to be logically consistent with each other. The overall F or
> > chi-square statistic might be significant for a model, while none of the
> > individual coefficients are.
> >
> > A more common situation might be where a coefficient is significant in one
> > group but not in another. I always warn my students to be careful about
> > saying X is important for one group but not the other. If, say, you are
> > comparing whites and black, your white sample size might be much larger,
> > which can help the effect to achieve significance for whites but not blacks.
> > The actual estimated coefficients, however, may be quite similar.
> >
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