Date: Wed, 30 Mar 2011 23:08:29 -0400
Reply-To: Rich Ulrich <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Rich Ulrich <firstname.lastname@example.org>
Subject: Re: significant F change,
but nonsignificant regression model overall
Content-Type: text/plain; charset="iso-8859-1"
> Date: Wed, 30 Mar 2011 15:56:30 -0400
> From: email@example.com
> Subject: Re: significant F change, but nonsignificant regression model overall
> To: SPSSX-L@LISTSERV.UGA.EDU
> On Wednesday, March 30, 2011 2:55 PM, Rich Ulrich wrote:
> >Mike Palij wrote:
> >> No, I didn't miss this comment. Let's review what we might know about
> >> the situation (at least from my perspective):
> >> (1) The analyst is doing setwise regression, comparable to an ANCOVA,
> >> entering 4 variables/covariates as the first set. As mentioned elsewhere,
> >> these covariates are NOT significantly related to the dependent variable.
> >No, they are not "doing setwise regression", whatever that new
> >phrase means, if that is what you intended.
> That "new phrase" can be found in Cohen and Cohen (1975) in their
> Chapter 4 "Sets of Independent Variables". Of particular relevance
> is section 4.2 "The simultaneous and hierarchical models for sets".
> What you and the OP described was a hierarchical or sequential
> setwise regression analysis.
Fine. I would not have stumbled over the phrase, if you had not
continued on so differently, with an explicit description of "stepwise"
that expects decreasing contributions of the next variables. Cohen &
Cohen is a book I own, I've read, and I've recommended multiple times.
Based on your comments here, and discussion in later posts, we are
now discussing the same model. But you were way off, in what I responded to.
See pp127-144 if you have a copy
> handy. If anything, you should say "whatever that arcane phrase
> As for your description of the analysis, do you really keep variables
> that don't provide any useful information in the equation?
Yes. In my area (research in psychiatry), when the prescribed testing
controls for several variables, that is what is ordinarily reported --
especially if there is discernible difference in outcomes. Sometimes
the coefficients vary a tad, even for "nonsignificant" nuisance
covariates. Depending on the circumstances, it is sometimes acceptable
to report the simpler equation; considering that option raises the risk
or suspicion of cherry-picking of results.
I hope you
> report shrunken or adjusted R^2 when you report your results because
> they should be considerably smaller than R^2 as a result of the additional
> useless predictors. It should give a person pause.
For 2 variables with 75 subjects, the reduction is not large. Of course,
the effect for 6 variables is larger, but that R^2 is clearly of no interest.
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