Posted by
Zdaniuk, Bozena on
Jan 10, 2007; 5:43pm
URL: http://spssx-discussion.165.s1.nabble.com/correspondence-analysis-with-multiple-response-set-tp1073070p1073074.html
Could someone be so kind and comment on the connection between beta
coefficient in multiple regression and the effect size. I am familiar
with using Rsq as an estimate of the effect size but I think it relates
to the effect size of the overall model. But if I want to estimate the
effect size of one particular predictor, I should use the beta, right?
But how does beta translate into the effect size? Thanks for your help
and patience in advance :)
Bozena
Bozena Zdaniuk, Ph.D.
University of Pittsburgh
UCSUR, 6th Fl.
121 University Place
Pittsburgh, PA 15260
Ph.: 412-624-5736
Fax: 412-624-4810
email:
[hidden email]
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
Kooij, A.J. van der
Sent: Wednesday, January 10, 2007 12:22 PM
To:
[hidden email]
Subject: Re: correspondence analysis with multiple response set
Jon is right (but MCA was introduced in 13). Some more clarification:
HOMALS performs MULTIPLE CORRESPONDENCE, the algorithm is the same in
both procedures; MCA offers more analysis options and more output than
HOMALS.
Anita van der Kooij
Data Theory Group
Leiden University
________________________________
From: SPSSX(r) Discussion on behalf of Peck, Jon
Sent: Wed 10/01/2007 16:49
To:
[hidden email]
Subject: Re: correspondence analysis with multiple response set
A little clarification: HOMALS has been superseded by MULTIPLE
CORRESPONDENCE in newer versions of SPSS (introduced in 14, if memory
serves), and the Optimal Scaling menu will take you to that procedure
now, although HOMALS is still in the system.
-Jon Peck
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
Babinec, Tony
Sent: Wednesday, January 10, 2007 9:35 AM
To:
[hidden email]
Subject: Re: [SPSSX-L] correspondence analysis with multiple response
set
In the menus, specify
Data Reduction -> Optimal Scaling
and work with All Variables Multiple Nominal
and One Set of variables.
This specifies HOMALS, also called
homogeneity analysis or multiple correspondence analysis.
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