Dear Manuel and list, I see that I wrote "point-biserial" when I meant "biserial."
Sorry, John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -------------------------------- > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of John Fox > Sent: Sunday, August 14, 2005 1:34 PM > To: [EMAIL PROTECTED] > Cc: r-help@stat.math.ethz.ch > Subject: Re: [R] path analysis > > 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: [EMAIL PROTECTED] > > [mailto:[EMAIL PROTECTED] 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" <[EMAIL PROTECTED]> > > Data: Sat, 13 Aug 2005 19:35:24 -0400 > > > > Dear Manel, > > > > > -----Original Message----- > > > From: [EMAIL PROTECTED] > > > [mailto:[EMAIL PROTECTED] 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 > > > > ______________________________________________ > > 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 > > ______________________________________________ > 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 ______________________________________________ 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