Date:         Wed, 17 Dec 2008 11:27:55 -0500
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: Regression: do you always need main effects with interactions?

On Wed, 17 Dec 2008 10:33:14 -0500, Peter Flom
<peterflomconsulting@MINDSPRING.COM> wrote:

>I don't think it's a strict dichotomy.  I don't think any data analysis is
>purely exploratory, and very few are purely confirmatory.  We almost
>always have *some* idea what we are expecting, and we almost never have a
>very exact idea.

A worthy and interesting discussion, but we have drifted from the original
question :)

The few analysis that are confirmatory, or intended to test a specific a
priori hypothesis, may be dominated by experiments.  Anyone who has
conducted an experiment knows that error and other forms of variation
occur, thus introducing the potential for additional factors :)

Either way, I think the term parsimonious needs to mean that lower order
terms and base factors of interactions are included in the model.

Kevin

PS FWIW, I have argued for the past three years that the talent in science
is acquiring the data with which to test (or to explore <vbseg>)
hypotheses.  Most students can adequately analyze a research question given
data.  I think this is true even for ongoing studies; obtaining permission
and funding to collect the samples and analyze them is an art...