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st: RE: Factor analysis with binary data
From
"David Radwin" <[email protected]>
To
<[email protected]>
Subject
st: RE: Factor analysis with binary data
Date
Wed, 2 Mar 2011 17:08:02 -0800 (PST)
Walt,
The usual advice on this list is to not dichotomize or categorize
continuous variables at all, much less do so based on an "arbitrary
guess."
See, for example:
http://www.stata.com/statalist/archive/2010-02/msg00871.html
http://www.stata.com/statalist/archive/2010-11/msg00443.html
Is there some way to use the variables as continuous?
David
--
David Radwin
Research Associate
MPR Associates, Inc.
2150 Shattuck Ave., Suite 800
Berkeley, CA 94704
Phone: 510-849-4942
Fax: 510-849-0794
www.mprinc.com
> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of Data Analytics Corp.
> Sent: Wednesday, March 02, 2011 9:10 AM
> To: [email protected]
> Subject: st: Factor analysis with binary data
>
> Hi,
>
> I have to do a factor analysis with binary survey data. I have no
> problem doing the factor analysis per se (I'll develop a correlation
> matrix using tetrachoric correlations), but I do have a question about
> the predicted scores. They will be continuous, but I need them for
> other analysis to be binary. Any suggestions for how I can take the
> scores for a factor and recode them into 0/1 values. I thought of
> looking at the distributions and making an arbitrary guess for a
> cut-off: anything above is 1; below is 0. A first guess for a cut-off
> would be 0: anything positive is 1; negative is 0. Does anyone have a
> better suggestion?
>
> Thanks,
>
> Walt
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