[R] sem question
jfox at mcmaster.ca
Mon Jul 17 04:01:07 CEST 2006
Dear Spencer and Denis,
I've been traveling for a while and away from r-help, so I didn't see
Denis's question until now.
I'm not familiar with applications of SEMs that have lags in time and space.
As to the identification status of Denis's model, it's hard to know about
that in the abstract. What's the model?
Department of Sociology
Canada L8S 4M4
> -----Original Message-----
> From: Spencer Graves [mailto:spencer.graves at pdf.com]
> Sent: Sunday, July 16, 2006 7:29 PM
> To: Denis Fomchenko
> Cc: r-help at stat.math.ethz.ch; John Fox
> Subject: Re: [R] sem question
> 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: fomchenko at iet.ru
> > http://www.iet.ru
> > [[alternative HTML version deleted]]
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