Thank you John. I got it now. 
Regarding the model I specified below, I totally agree with you. I listed only portions of my model the illustrate the point of my questions. Therefore, I showed only the arrow part. No correlations are listed here. However, I have those in my complete model.
Thank you so much for your help. It was really helpful.

- adschai

----- Original Message -----
From: John Fox 
Date: Sunday, April 15, 2007 8:31 am
Subject: RE: [R] Fit sem model with intercept
To: adschai@optonline.net
Cc: r-help@stat.math.ethz.ch

> Dear adschai,
> 
> You needn't look too far, since the last example in ?sem is for 
> a model with
> an intercept. One would use the raw-moment matrix as input to 
> sem(), either
> entered directly or calculated with the raw.moments() function 
> in the sem
> package. The row/column of the raw-moment matrix is given a name 
> just like
> the other columns. You could use the name "1"; in the example, 
> the name is
> "UNIT".
> 
> As you say, however, you're using polychoric and polyserial 
> correlations as
> input. Since the origin and scale of the latent continuous variables
> underlying the ordinal variables are entirely arbitrary, I can't 
> imaginewhat the purpose of a model with an intercept would be, 
> but it's possible
> that I'm missing something. If you think that this makes some 
> sense, then
> you could convert the correlations to raw moments by using the 
> means and
> standard deviations of the observed variables along with the 
> means and
> standard deviations that you assign to the latent variables 
> derived from the
> ordinal variables (the latter on what basis I can't imagine, but 
> I suppose
> you could fix them to 0s and 1s).
> 
> Finally, if the sem model that you show is meant to be a complete
> specification, I notice that it includes no covariance 
> components; moreover,
> if this is the complete structural part of the model, then I 
> think it is
> underidentified, and the two parts of the model (those involving 
> eta1 and
> eta2) appear entirely separate.
> 
> I hope this helps,
> 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 
> > adschai@optonline.net
> > Sent: Sunday, April 15, 2007 4:28 AM
> > To: r-help@stat.math.ethz.ch
> > Subject: [R] Fit sem model with intercept
> > 
> > Hi - I am trying to fit sem model with intercepts. Here is 
> > what I have in my model.
> > 
> > Exogeneous vars: x1 (continous), x2 (ordinal), x3 (ordinal), 
> > x4(continuous) Endogeneous vars: y1 (continuous), y2 
> > (ordinal), y3 (ordinal)
> > 
> > SEM model:
> > x1 -> eta1; x2 -> eta1; x3 -> eta2; x4 -> eta2; eta1 -> 
> > y1, eta1 -> y2, eta2 -> y2, eta2 -> y3 
> > 
> > However, in these arrow models, I don't know how to add 
> > intercept onto it. I am trying to find an example code using 
> > sem package on how to incorporate intercept but cannot find 
> > any documents on the web. Or we can simply add something like 
> > this? '1 -> eta1'? This is my first question. 
> > 
> > Also, note that since my y2 and y3 are ordinal, I used the 
> > 'hetcor' to calculate correlation of observed variables. 
> > However, from the document, I would need to use the 
> > covariance matrix rather then the correlation. And I need 
> > additional column for 1. I am not sure how this matrix should 
> > look like and how I can obtain this? If there is any example 
> > you could point me to, I would really appreciate. Thank you.
> > 
> > - adschai
> > 
> > [[alternative HTML version deleted]]
> > 
> > ______________________________________________
> > 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
> > and provide commented, minimal, self-contained, reproducible code.
> > 
> 
> 
> 

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