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st: Re:


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re:
Date   Sat, 7 Feb 2009 18:30:05 +0100

<>

Stata reserves its most comprehensive postestimation suite of commands for -regress- accessible via -help regress_postestimation-. Make use of them...

BTW, are you sure OLS is appropriate for your underlying theoretical model? I grew up with the OLS estimator during my econometrics education, but have concluded that it simply does not get you published...

HTH
Martin
_______________________
----- Original Message ----- From: "Antonio Silva" <asilva100@live.com>
To: "Stata list" <statalist@hsphsun2.harvard.edu>
Sent: Saturday, February 07, 2009 5:29 PM


Hello Statlist:
I have an OLS model that looks like this: y = constant + b + c + d + e + f. c is the variable in which I am most interested. In the basic model, c turns out NOT to be significant (it is not even close). However, when I include an interaction term in the model, c*f, c turns out to be highly significant. So the new model looks like this: y = constant + b + c + d + e + f + c*f. The interaction term, c*f, is highly significant as well (though in many versions f is NOT significant). My question is this: Is it defensible JUST to report the results of the fully specified model--that is, the one with the interaction? I kind of feel bad knowing that the first model does not produce the results I desire (I am very happy c ends up significant in the full model--it helps support my hypothesis). I have heard from others that if the variable of interest is NOT significant without the interaction term in the model but IS significant WITH the interaction term, I should either a) report the results of both models; or b) assume the data are screwy and back away...
What do you all think?
Thanks so much.
Antonio Silva
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