Re: st: RE: Factor analysis with binary data

["Data Analytics Corp." <walt@dataanalyticscorp.com>]

Hi,

I'm leaning to using the scores as continuous variables since I'm 
concerned about the arbitrary dichotomization.  I was planning to do 
latent class clustering in Latent Gold and that will use continuous 
factors.

By the way, does Stata have any latent class clustering?

Thanks for the help,

Walt

________________________

Walter R. Paczkowski, Ph.D.
Data Analytics Corp.
44 Hamilton Lane
Plainsboro, NJ 08536
________________________
(V) 609-936-8999
(F) 609-936-3733
walt@dataanalyticscorp.com
www.dataanalyticscorp.com
_____________________________________________________

On 3/2/2011 8:08 PM, David Radwin wrote:
> 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: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
> > statalist@hsphsun2.harvard.edu] On Behalf Of Data Analytics Corp.
> > Sent: Wednesday, March 02, 2011 9:10 AM
> > To: statalist@hsphsun2.harvard.edu
> > 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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