[R-sig-ME] [R] lme nesting/interaction advice

[Federico Calboli]

On 12 May 2008, at 14:37, Doran, Harold wrote:
>
> I haven't followed this thread carefully, so apologies if I'm too off
> base. But, in response to Rolf's questions/issues. First, SAS cannot
> handle models with crossed random effects (at least well at all).  
> SAS is
> horribly incapable of handling even the simplest of models (especially
> generalized linear mixed models). I can cite numerous (recent)  
> examples
> of SAS coming to a complete halt (proc nlmixed) for an analyses we  
> were
> recently working on. R (and Ubuntu) was the only solution to our
> problem

First off, let's keep SAS out of this. I never used it, never wanted  
to use it and did not mention anywhere I wanted to get SAS-like  
results! Although, seeing how easily it creeps up, I can sympathise  
with those who have strog feelings about it! [for those with strong  
feelings about me, this is meant to be something joke-like]

> Now, lme is not optimized for crossed random effects, but lmer is.  
> That
> is why lmer is supported and lme is not really supported much. lmer is
> optimized for models with nested random effects and crossed random
> effects.
>
> When working with models with nested random effects, and software
> optimized for those problems (e.g., HLM, SAS, mlWin) the
> variance/covariance matrix forms a special, and simple structure that
> can be easily worked with. This is not the case for models with  
> crossed
> random effects.
>
> Software packages designed for nested random effects can be tricked  
> into
> handling models with crossed random effects, but this kludge is  
> slow and
> really inefficient.
>
> If you want complete transparency into the why and how, here is a
> citation for your review.

Thank you very much. I'll read the paper and hopefully get the  
answers I was looking for.

Best,

Federico


>
> Best
> Harold
>
> @article{Doran:Bates:Bliese:Dowling:2007:JSSOBK:v20i02,
>   author =	"Harold  Doran and Douglas  Bates and Paul  Bliese and
> Maritza   Dowling",
>   title =	"Estimating the Multilevel Rasch Model: With the lme4
> Package",
>   journal =	"Journal of Statistical Software",
>   volume =	"20",
>   number =	"2",
>   pages =	"1--18",
>   day =  	"22",
>   month =	"2",
>   year = 	"2007",
>   CODEN =	"JSSOBK",
>   ISSN = 	"1548-7660",
>   bibdate =	"2007-02-22",
>   URL =  	"http://www.jstatsoft.org/v20/i02",
>   accepted =	"2007-02-22",
>   acknowledgement = "",
>   keywords =	"",
>   submitted =	"2006-10-01",
> }
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

--
Federico C. F. Calboli
Department of Epidemiology and Public Health
Imperial College, St. Mary's Campus
Norfolk Place, London W2 1PG

Tel +44 (0)20 75941602   Fax +44 (0)20 75943193

f.calboli [.a.t] imperial.ac.uk
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