Hi John,Thank you. I think (2) from your explanation hits the right point. The
reason is that when I made my own dummy variables and my original nominal
variable has 10 possible values, it makes each each observed exogeneous
variable vector of mine has 9 zeros and 1 one value. And I have about 400000
observations. So it will make the matrix almost zero.One more question. If I
have a nominal response, I guess the tsls would no longer work. How can I go
around with this? Says, I have 3 equations in my structure model whose
responses are continuous whereas another one has multinominal response. Thank
you so much.- 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 no!
minal 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 package> > > > 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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