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
_________________________________________________________________
Windows Live?: Keep your life in sync.
http://windowslive.com/howitworks?ocid=TXT_TAGLM_WL_t1_allup_howitworks_022009
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
