Date:         Tue, 4 Dec 2007 19:51:48 -0600
Reply-To:     ajshackman@gmail.com
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         "Alexander J. Shackman" <shackman@wisc.edu>
Subject:      Re: Question
Comments: To: Ormalik@aol.com
In-Reply-To:  <c39.20788a15.348758ff@aol.com>
Content-Type: text/plain; charset=ISO-8859-1

i would try looking in tabachnick & fidell, cohen cohen west & aiken (where
they discuss how to deal with multicolinearity), or maybe gorsuch's factor
analysis textbook

the approach you describe is related to discriminant analysis and
pca-regression (which is widely used in analytic chemistry).

the main reason for not doing what you suggest (& instead sticking with sum
or mean of z-transformed vars) is that (i) it will be difficult for others
to exactly replicate your results, and (ii) the factor scores may not be
stable if you have a small sample (<10 Ss x number of items)...there are
approaches (based on permutation) for dealing with the latter problem in the
dedicated pca-regression software packages, but most of them do not allow
you to rotate the solutions. you can experiment with them, s most have free
30 d demos.

hth, ajs

On Dec 4, 2007 7:29 PM, <Omar Malik> <Ormalik@aol.com> wrote:

> Hello,
>
> Does anyone know of any citations that support the use of regression
> factor
> scores as composite measures of factors rather than using means of
> variables
> or  sums of variables as measures of a factor?
>
> Thanks in advance.
>
> Omar R. Malik
> Assistant Professor of Management
> School of  Business Administration
> Philadelphia University
> School House Lane &  Henry Avenue
> Philadelphia PA 19144
> Tel: (215) 951 2812
> Email:  MalikO@PhilaU.edu
>
>
>
>
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--
Alexander J. Shackman
Laboratory for Affective Neuroscience
Waisman Laboratory for Brain Imaging & Behavior
University of Wisconsin-Madison
1202 West Johnson Street
Madison, Wisconsin 53706

Telephone: +1 (608) 358-5025
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EMAIL: shackman@wisc.edu
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