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Date:         Wed, 30 Mar 2011 23:08:29 -0400
Reply-To:     Rich Ulrich <>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Rich Ulrich <>
Subject:      Re: significant F change,
              but nonsignificant regression model overall
Comments: To:
In-Reply-To:  <FB6C87DE199A46F08A914F58C47679C9@NARAYAM>
Content-Type: text/plain; charset="iso-8859-1"

> Date: Wed, 30 Mar 2011 15:56:30 -0400 > From: > 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. > > > >Mike, > >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 > means". > > 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.

-- Rich Ulrich

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