Re: [R] sem question

From: Spencer Graves <>
Date: Mon 17 Jul 2006 - 10:28:33 EST

MODEL UNDERIDENTIFIED?           I've looked at 'sem' for many years but never found that application that seemed to me to require that machinery. However, I know that it's very easy to get models that are "underidentified." One of the simplest cases is the classical "errors in x regression" problem:


	  X = xi + e.x, e.x~N(0, s2.x)
	  Y = eta + e.y, e.y~N(0, s2.y)
	  eta = a+b*xi

	  If I'm not mistaken, I believe that it is theoretically impossible to 
estimate a, b, s2.x, and s2.y without additional information, like for example the ratio between s2.x and s2.y.

LAGS IN BOTH TIME AND SPACE?           I've copied John Fox, the 'sem' package author and maintainer, on this reply. He might educate us both on how to include lags in both time and space into an 'sem' model.

          Failing that, are you familiar with Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). This book and the companion 'nlme' packages include facilities for linear and nonlinear models in both space and time. The follow-on 'lme4' package and accompanying 'lmer' function will also handle non-normal response distributions. I'm a firm believer in trying the simple things first, and I think the mixed-effects models are simpler than 'sem', though Prof. Fox may wish to disabuse me of my ignorance on that point.

MORE HELP?           If you would like more from this listserve than just this, please submit another post. When you do, however, please include a simple, self contained example to illustrate briefly what you want, what you tried, and the deficiencies with what you tried, as suggested in the posting guide! "".

	  Hope this helps.
	  Spencer Graves 	  	

Denis Fomchenko wrote:
> Dear all,
> I am trying to estimate simultaneous equation model concerning growth in russian regions.
> I run the analysis by means of FIML in R sem package.
> I am not familiar with SEM yet, but I've just got several suitable estimated specifications.
> Nevertheless, sometimes R gives the following warning message:
> Warning message:
> Negative parameter variances.
> Model is probably underidentified.
> in: sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars,
> I check for rank condition - all three equations in the system are turned out to be exact...
> Does anybody know what it means? and how to handle with that problem?
> P.S.
> Do you know any examples of models estimated in SEM by means of FIML, incorporating spatial lag on endogenous variable?
> Thanks, in advance
> Denis Fomchenko
> research fellow
> Department for Economic Development Problems
> Institute for the Economy in Transition
> 5, Gazetny lane, Moscow 125993, Russia
> e-mail:
> [[alternative HTML version deleted]]
> ______________________________________________
> mailing list
> PLEASE do read the posting guide! mailing list PLEASE do read the posting guide! Received on Mon Jul 17 10:36:09 2006

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