It reminds of the third option under Dimension Reduction: OPTIMAL SCALING.
Many times, we analyze likert-scale data using the FACTOR platform. But probably, the OPTIMAL SCALING procedure is a better option which does nonlinear principal component analysis, among other things.
So, it is a very nice procedure. But it does not seem to be emphasized enough.
Sorry about deviating from the main topic! It just came to my mind. J
Patrick Yang, University of Kentucky
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Jon K Peck
Sent: Tuesday, August 13, 2013 12:41 PM
To: [hidden email]
Subject: Re: Multi Correspondence Analysis
Multiple correspondence analysis is available in the Categories option (Analyze > Dimension Reduction > Correspondence Analysis).
You can read the help for this online in the IBM Info Center at
http://pic.dhe.ibm.com/infocenter/spssstat/v21r0m0/index.jsp
under the Categories option.
Jon Peck (no "h") aka Kim
Senior Software Engineer, IBM
[hidden email]
phone: <a href="tel:720-342-5621" value="+17203425621" target="_blank">720-342-5621
From: Vik Rubenfeld <[hidden email]>
To: [hidden email],
Date: 08/13/2013 10:27 AM
Subject: Re: [SPSSX-L] Multi Correspondence Analysis
Sent by: "SPSSX(r) Discussion" <[hidden email]>
Last time I looked into it, I did not find a way to do correspondence analysis with SPSS. However that was a few years ago. I would love to find a way to do CA in SPSS and I look forward to following this thread to find out if there is one at this time.
However, you can do CA using R Project, using an R Project package such as "CA". http://www.r-project.org/
Best,
-Vik
On Aug 13, 2013, at 4:31 AM, mils <[hidden email]> wrote:
Hi everyone,
I would like to run a Multi Correspondence Analysis (MCA). I used to run MCA
with xlstat, so I am a bit confused on how to use it in SPSS. I've attached
a file with the raw data and variables description.
Do I have to transform the data?
Any suggestions will be really appreciate it.
Thanks in advance,
Mils
Multi_Correspondence_Analysis.xlsx
<http://spssx-discussion.1045642.n5.nabble.com/file/n5721553/Multi_Correspondence_Analysis.xlsx>
-----
mils
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