Yes, I was leaning toward some of the latent class models as well, but note that latent class is probably a bit more like cluster analysis (for objects) than factor analysis (for variables).
I believe that the Penn State center also makes their R-code available as well.
The other though that I had was to ask you about the theoretical implications of the nominal level variables. I have often found it theoretically compelling to suggest that the nominal measures have a statistical interaction effect on the measurement model. As such I might move to the LISREL multi-group model and estimate a ML model within each group, attempting to constrain to equality parameters across-groups, relaxing those constraints only as necessary for the measurement model.
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David Mangen
Owner
Mangen Research Associates, Inc.
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Original Message:
Sent: 05-15-2014 18:37
From: Ihor Kowalysko
Subject: Factor analysis
Try using Latent Class Models which are analogous to factor analysis using categorical data. Penn State makes the SAS code available for free. I haven't checked out the software in awhile but I think that they have expanded the use to ordinal variables.
The Methodology Center
204 East Calder Way, Suite 400
State College, PA 16801
Phone: 814-865-3253
Fax: 814-863-0000
methodology.psu.edu
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Ihor Kowalysko
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Original Message:
Sent: 05-15-2014 18:26
From: Chris Barker
Subject: Factor analysis
Its a mix of all kinds, nominal, ordinal, categorical.
Its a dataset collected by a surgeon for his transgender patients in the process of undergoing gender change.
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Chris Barker, Ph.D.
Consultant and
Adjunct Associate Professor of Biostatistics
www,barkerstats.com
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"In composition you have all the time you want to decide what to say in 15 seconds, in improvisation you have 15 seconds."
-Steve Lacy
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Original Message:
Sent: 05-15-2014 17:57
From: Chris Barker
Subject: Factor analysis
I may be preparing a factor analysis for a dataset with continuous and categorical variables.
My reading of the literature so far, is to use a polychoric method and it seems I can prepare that in both SAS and R.
I'd appreciate pointers/suggestions to current methodology in factor analysis, or alternative methods, for a mix of variables.
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Chris Barker, Ph.D.
Consultant and
Adjunct Associate Professor of Biostatistics
www,barkerstats.com
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"In composition you have all the time you want to decide what to say in 15 seconds, in improvisation you have 15 seconds."
-Steve Lacy
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