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Re: st: Multiple correspondence analysis & PCA with ordinal variables


From   Laura Gibbons <gibbonsl@u.washington.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Multiple correspondence analysis & PCA with ordinal variables
Date   Thu, 13 May 2010 11:32:00 -0700 (PDT)

Did you consider using -gllamm-? I've not done this, but you could search for messages about IRT and gllamm. Another alternative would be to call the R -ltm- package.

The other options I know of involve purchasing a separate program, like Mplus, Parscale, etc.

-Laura

On Thu, 13 May 2010, Owen Corrigan wrote:

I am trying to extract a single index from a set of 7/8 ordinal
variables measured over three categories (low, med, high). I
understand that MCA (multiple correspondence analysis) is an analogue
of PCA (principal components analysis) for categorical/ordinal data,
and so have been using that in Stata 10. My concern is that I am not
properly 'telling' Stata that the data is ordinal, and thus Stata may
not be taking into account that category 3 > category 2 > category 1.
I have read through the help file and options, but see no way to
'force ordinality' on the program; so I am worried that the analysis
is merely treating each of the categories of the variables as
independent, and not related.

Is there a way to force ordinality? Should I be using a different method?
All assistance greatly appreciated.
Owen.
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Laura E. Gibbons, PhD
General Internal Medicine, University of Washington
Box 359780, Harborview Medical Center, 325 Ninth Ave, Seattle, WA 98104
phone: 206-744-1842, fax: 206-744-9917, Office address: 401 Broadway, Suite 5122
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