Re: [R] path analysis

From: John Fox <jfox_at_mcmaster.ca>
Date: Mon 15 Aug 2005 - 04:33:40 EST


Dear Manuel,

Polychoric correlations imply only that the *latent* variables are continuous -- the observed variables are ordered categories. Tetrachoric and point-biserial correlations are special cases respectively of polychoric and polyserial correlations. As long as you're willing to think of the dichotomous variable as the dissection into two categories of a latent continuous variable (and assuming multinormality of the latent variables), you can use the approach that I suggested. This isn't logistic regression, but it's similar to a probit model.

Regards,
 John



John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox

> -----Original Message-----
> From: r-help-bounces@stat.math.ethz.ch
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Manel Salamero
> Sent: Sunday, August 14, 2005 12:34 PM
> To: r-help@stat.math.ethz.ch
> Subject: Re: [R] path analysis
>
> This solves part of my problem with the independent ordinal
> variables, but my dependent variable is truly categorial
> (illness/no illness). Polychoric correlation implies that
> data are continuous, which in not the case. Is possible to
> implement logistic regression in the path model?
>
> Thanks,
>
> Manel Salamero
>
> ---------- Original Message ----------------------------------
> De: "John Fox" <jfox@mcmaster.ca>
> Data: Sat, 13 Aug 2005 19:35:24 -0400
>
> Dear Manel,
>
> > -----Original Message-----
> > From: r-help-bounces@stat.math.ethz.ch
> > [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of
> SALAMERO BARO,
> > MANUEL
> > Sent: Saturday, August 13, 2005 2:02 PM
> > To: r-help@stat.math.ethz.ch
> > Subject: [R] path analysis
> >
> > Someone knows if it is possible to perform a path analysis with sem
> > package (or any other) to explain a dependent
> > *dichotomus* variable?
> >
>
> Yes -- you can use the hetcor() function in the polycor
> package to generate
> a correlation matrix and boot.sem() in the sem package to get standard
> errors or confidence intervals. Make sure that the
> dichotomous variables are
> represented as factors. See ?boot.sem for an example.
>
> I hope this helps,
> John
>
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R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Mon Aug 15 04:41:52 2005

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