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: adschai@optonline.netCc: r-help@stat.math.ethz.ch> 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: r-help-bounces@stat.math.ethz.ch > > [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of > > adschai@optonline.net> > Sent: Sunday, April 08, 2007 11:07 PM> > To: r-help@stat.math.ethz.ch> > 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]]> > > > ______________________________________________> > 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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