LISTSERV at the University of Georgia
Menubar Imagemap
Home Browse Manage Request Manuals Register
Previous messageNext messagePrevious in topicNext in topicPrevious by same authorNext by same authorPrevious page (March 2011)Back to main SPSSX-L pageJoin or leave SPSSX-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Wed, 30 Mar 2011 23:08:29 -0400
Reply-To:     Rich Ulrich <rich-ulrich@live.com>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Rich Ulrich <rich-ulrich@live.com>
Subject:      Re: significant F change,
              but nonsignificant regression model overall
Comments: To: mp26@nyu.edu
In-Reply-To:  <FB6C87DE199A46F08A914F58C47679C9@NARAYAM>
Content-Type: text/plain; charset="iso-8859-1"

> Date: Wed, 30 Mar 2011 15:56:30 -0400 > From: mp26@nyu.edu > 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

===================== To manage your subscription to SPSSX-L, send a message to LISTSERV@LISTSERV.UGA.EDU (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD


Back to: Top of message | Previous page | Main SPSSX-L page