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Re: st: RE: Insignificant coefficient in prediction

From   Richard Williams <>
To, "''" <>
Subject   Re: st: RE: Insignificant coefficient in prediction
Date   Wed, 01 Dec 2010 17:27:06 -0500

At 01:12 PM 12/1/2010, Nick Cox wrote:
3. Often there are scientific and/or statistical grounds for including bundles of predictors, even if some or all don't qualify individually as significant. A perhaps esoteric example is that a sine and a cosine term usually belong together, even if one is not significant. A more common example, for many readers of this list, is that a bunch of indicators usually belong together, ditto.

Good list. To this particular item I would add interaction terms and main effects, e.g. if you've got x1*x2 in the model you generally want x1 and x2, even if their effects aren't significant. Likewise with things like X and X^2.

Richard Williams, Notre Dame Dept of Sociology
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