Hi John,Additional two questions on this sem package:(1) The tsls is based on
maximum likelihood or OLS?(2) I am trying to find goodness of fit for the
result of tsls. Somehow, I don't see it in the documentation. Would you please
provide some examples? (3) If I would like to diagnostic of model selection,
says use AIC criteria, it is a bit unclear for me how I can apply this on
structural equation model as it is composed of multiple equations rather than
one. And is there any functionality in sem that does this? Any help would be
really appreciated. Thank you.- adschai----- Original Message -----From: John
Fox Date: Monday, April 9, 2007 8:04 amSubject: RE: [R] Dealing with large
nominal predictor in sem packageTo: [EMAIL PROTECTED]:
[email protected]> Dear adschai,> > It's not possible to know from your
description exactly what > you're doing,> but perhaps the following will help:
> > (1) I presume that your nominal variable is exogenous, since > otherwise
it>!
wouldn't be sensible to use 2SLS. > > (2) You don't have to make your own
dummy regressors for a > nominal variable;> just represent it in the model as a
factor as you would, e.g., > in lm(). > > (3) Do you have at least as many
instrumental variables > (including the dummy> regressors) as there are
structural coefficients to estimate? If > not, the> structural equation is
underidentified, which will produce the > error that> you've encountered.> > 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:
[EMAIL PROTECTED] > > [mailto:[EMAIL PROTECTED] On Behalf Of > > [EMAIL
PROTECTED]> > Sent: Sunday, April 08, 2007 11:07 PM> > To:
[email protected]> > Subject: [R] Dealing with large nominal predictor
in sem p!
ackage> > > > Hi,> > > > I am using tsls function from sem package to
estimate a model > > which includes large number of data. Among its predictors,
it > > has a nominal data which has about 10 possible values. So I > > expand
this parameter into 9-binary-value predictors with the > > coefficient of base
value equals 0. I also have another > > continuous predictor. > > > > The
problem is that, whenever I run the tsls, I will get > > 'System is
computationally singular' error all the time. I'm > > wondering if there is
anyway that I can overcome this > > problem? Please kindly suggest. Thank you
so much in advance.> > > > - adschai> > > > [[alternative HTML version
deleted]]> > > > ______________________________________________> >
[email protected] 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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