[R-sig-ME] Is there any chance of development ofmultivariate linear mixed models for lme4

[Doran, Harold]

I'm interested in seeing this as well. I too have a paper showing how to
estimate multivariate mixed models. But, I think it is necessary to
construct a patterned covariance matrix for the residual error and this
is not available in lmer.

@article{dora:lock:2006,
year			={2006},
author		={Harold C. Doran and J.R. Lockwood},
title			={Fitting value-added models in {R}},
volume		={31}.
number		={2},
journal		={Journal of Educational and Behavioral Statistics}
} 

> -----Original Message-----
> From: r-sig-mixed-models-bounces at r-project.org 
> [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf 
> Of Andrew Robinson
> Sent: Thursday, February 01, 2007 6:31 PM
> To: Ian Dworkin
> Cc: r-sig-mixed-models at r-project.org
> Subject: Re: [R-sig-ME] Is there any chance of development 
> ofmultivariate linear mixed models for lme4
> 
> Hi Ian,
> 
> I've been able to trick lme() into fitting multivariate 
> mixed-effects models, and I don't think that I relied on any 
> functionality that is not available within lmer at the 
> present.  I can send you what I did if you're interested.  I 
> wrote it up in:
> 
> Robinson, A.P., 2004. Preserving correlation while modelling diameter
>   distributions. Canadian Journal of Forest Research 34, 221--232.
> 
> Mind you, the code was ugly and not terribly intuitive!
> 
> Cheers
> 
> Andrew
> 
> On Thu, Feb 01, 2007 at 05:59:54PM -0500, Ian Dworkin wrote:
> > Hi,
> > 
> >   From what I gather this is a list primarily dedicated to the 
> > development of mixed model libraries for R. So I apologize 
> if this is 
> > not the appropriate place for this.
> > 
> >   I am in the process of making the transition from SAS to 
> R. One of 
> > the major procedures I use(d) in SAS was PROC MIXED, and I 
> am slowly 
> > getting familiar with lmer.
> > 
> >  I was wondering if there is any discussion of working on the 
> > development of multivariate mixed models? Most of the data I am 
> > interested with is multivariate in nature, and univariate 
> methods tend 
> > to be less useful. Not that PROC MIXED does this very 
> effectively, but 
> > you can trick MIXED to do some multivariate models using 
> the repeated 
> > statement and specifying an unstructured covariance matrix etc..
> > However the code is ugly and not very intuitive.
> > 
> >   Anyways, I am asking in the vain hope that something is being 
> > developed in lme4 for multivariate models.
> > 
> > Thanks
> > 
> > Ian
> > 
> > _______________________________________________
> > 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: 
> +61-3-8344-9763
> 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
>