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: 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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