[R] Re: Factor analysis of categorical or mixed categorical/continuousdata in [R]

[John Fox]

Dear Peter,

At 05:27 PM 2/21/2002 +0100, Peter Dalgaard BSA wrote:
>John Fox <jfox at mcmaster.ca> writes:
>
> > At 11:18 AM 2/21/2002 +0000, Dr Stuart Leask wrote:
> > >I am looking to fit one or more latent categorical variables to data 
> that is
> > >a mixture of categorical and continuous variables. Factor analysis would
> > >work for continuous data, latent class analysis for categorical data. I
> > >understand that in a package such as MPlus I could perform a single 
> analysis
> > >of both data types. Are there similar routines available in R?
> >
> > Dear Stuart,
> >
> > If memory serves me, a common approach is to use tetrachoric
> > correlations (for dichotomous data), polychoric correlations (for
> > ordered-category data), and point-biserial and polyserial correlations
> > (for mixed data). If you want to do inference, then this approach gets
> > complicated (requiring asymptotic sampling covariances for the
> > correlations), but for a descriptive factor analysis, it should be
> > reasonably straightforward.
> >
> > I'm not aware of any facility for calculating these kinds of
> > correlations in R, but programming them shouldn't be too hard. I may
> > add this at some point to the sem package.
>
>On the face of it (which is as far as I am able to see), it would seem
>fairly easy to set up an MLE procedure if you treat all discrete
>variables as obtained by setting cutpoints on continuous latent
>variables. I suspect this is what MPlus is doing. The requisite normal
>integrals should be available through library(mvtnorm).

Indeed, this is what tetrachoric, etc., correlations do.

John


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