[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Antonio Silva <[email protected]> |

To |
Stata list <[email protected]> |

Subject |
st: Interaction term in OLS regression |

Date |
Sat, 7 Feb 2009 16:34:02 -0500 |

List: sorry for the earlier post that did not have a subject line. My mistake. Here is the original post: 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 Anyway, I received several good responses. And here are my responses to those responses. Any further feedback is appreciated. First, OLS seems appropriate, though I udnerstand the desire to do something more. The DV is a continuous variable that is normally distributed. Diagnostics show the model works well... So I really don't think any other method makes sense here. Second, the interaction is exactly what the theory holds, which is nice. I guess my confusion lies here...why would the variable not be significant without the interaction term included? Th etheory holds that c would affect everyone, but would affect different values of f differently. So I would expect that the model without the interaction would also produce some good results on c, but it does not. Thanks again... _________________________________________________________________ Windows Live?: E-mail. Chat. Share. Get more ways to connect. http://windowslive.com/howitworks?ocid=TXT_TAGLM_WL_t2_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/

**Follow-Ups**:**Re: st: Interaction term in OLS regression***From:*Robert A Yaffee <[email protected]>

- Prev by Date:
**st: FWD: poisson regression on aggrgregated data** - Next by Date:
**Re: st: Interaction terms in fixed effects analysis** - Previous by thread:
**st: FWD: poisson regression on aggrgregated data** - Next by thread:
**Re: st: Interaction term in OLS regression** - Index(es):

© Copyright 1996–2024 StataCorp LLC | Terms of use | Privacy | Contact us | What's new | Site index |