path analysis

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch 
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Manel Salamero
Sent: Sunday, August 14, 2005 12:34 PM
To: r-help at 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 at mcmaster.ca>
Data:  Sat, 13 Aug 2005 19:35:24 -0400

Dear Manel,

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch 
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of 

SALAMERO BARO, 

MANUEL
Sent: Saturday, August 13, 2005 2:02 PM
To: r-help at 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

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch 
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of John Fox
Sent: Sunday, August 14, 2005 1:34 PM
To: 10133msb at comb.es
Cc: r-help at 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: r-help-bounces at stat.math.ethz.ch 
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of 

Manel Salamero

Sent: Sunday, August 14, 2005 12:34 PM
To: r-help at 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 at mcmaster.ca>
Data:  Sat, 13 Aug 2005 19:35:24 -0400

Dear Manel,

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch 
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of

SALAMERO BARO,

MANUEL
Sent: Saturday, August 13, 2005 2:02 PM
To: r-help at 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