Date: Thu, 30 Jul 2009 15:55:05 -0400
Reply-To: Kevin Viel <citam.sasl@GMAIL.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: Kevin Viel <citam.sasl@GMAIL.COM>
Subject: Re: Interaction
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On Wed, 29 Jul 2009 07:58:01 -0400, Billy Thompson
>Hopefully some of you stats ‘gurus’ can help me solve my problem.
>I have a project in which the PI is interested in the interaction effects
>among certain variables and not the main effects. The problem results
>that when I run the ‘full’ factorial model with all effects the
>interaction effects are non significant and the main effects are
>significant. If I then remove the significant main effects the
>interaction effects then become significant.
>Is it appropriate to run the model with interaction effects only, thus
>ignoring the main effects?
Shawn Haskell calls it the heredity principle(1), I call in a
heirarchically well-formulated model.
One thing to establish is *why* you are running the model. What is the
variable of interest? What does the science say the model should be?
Having diverted, I will say no; you should include lower order terms.