[R] sem question

Spencer Graves spencer.graves at pdf.com
Mon Jul 17 02:28:33 CEST 2006


	  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.


	  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.


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	  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: fomchenko at iet.ru
> http://www.iet.ru
> 	[[alternative HTML version deleted]]
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