[R-sig-ME] Can lme allow for serial correlation and 'pure' measurement error?

[Jonathan Baron]

Min Gong supplied me with the following (which might also work in lmer
in the lme4 package):

I think you are probably referring to this. He can use subject as a
grouping factor when measuring the serial correlation between
periods..

http://stat.ethz.ch/R-manual/R-patched/library/nlme/html/corAR1.html


On 05/30/08 10:46, Andrew Robinson wrote:
> I don't think that lme can do that out of the box.
> 
> One hack to get around the problem would be to use the mean of the
> multiple measurements, also record the standard error of measurements
> within examination and feed the latter into a variance model using the
> weights argument.
> 
> I hope that this helps,
> 
> Andrew
> 
> On Thu, May 29, 2008 at 03:29:29PM +0100, Jonathan.Bartlett at lshtm.ac.uk wrote:
> > Dear mixed models list
> >  
> > Could someone please confirm my belief that lme does not allow one to
> > fit models with separate serial correlation and measurement error
> > components? In SAS proc Mixed, one can use serial correlation with a
> > "repeated", and adding the option "local" to this state adds an
> > additional independent error term. As far as I can tell from Pinheiro
> > and Bates, lme only allows specification of a single level of residual
> > covariance structure. As far as I understand, a nugget effect does not
> > give the same residual covariance structure that I want.
> >  
> > Just to give the context, I'm analysing a dataset in which subjects are
> > measured repeatedly over time. Subjects are measured at a number of
> > examinations, with multiple measurements made at each examination
> > (though not always the same number-otherwise I would just take the
> > mean). Conditional on a set of random effects, I believe there is serial
> > correlation, but since I have multiple measurements at identical times
> > for each subject, I need an additional measurement error component,
> > since for a model with just serial correlation a subject's measurements
> > at the same time point must be identical.
> >  
> > My apologies if the answer is obviously no, but I just wanted to check
> > I wasn't missing something obvious.
> >  
> > Many thanks
> > Jonathan Bartlett
> > 
> > 	[[alternative HTML version deleted]]
> > 
> > _______________________________________________
> > R-sig-mixed-models at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> 
> -- 
> Andrew Robinson  
> Department of Mathematics and Statistics            Tel: +61-3-8344-6410
> University of Melbourne, VIC 3010 Australia         Fax: +61-3-8344-4599
> http://www.ms.unimelb.edu.au/~andrewpr
> http://blogs.mbs.edu/fishing-in-the-bay/
> 
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

-- 
Jonathan Baron, Professor of Psychology, University of Pennsylvania
Home page: http://www.sas.upenn.edu/~baron
Editor: Judgment and Decision Making (http://journal.sjdm.org)