R help - Nov 2006 - Rank transformation and the linear mixed model

Hello,
I am looking for references about mixed models built on rank transformed 
data.
Did anybody ever consider this topic?

Thank you,
    Bruno


~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Bruno L. Giordano, Ph.D.
CIRMMT
Schulich School of Music, McGill University
555 Sherbrooke Street West
Montr?al, QC H3A 1E3
Canada
http://www.music.mcgill.ca/~bruno/

Bruno L. Giordano wrote:
> Hello,
> I am looking for references about mixed models built on rank transformed 
> data.
> Did anybody ever consider this topic?
> 
> Thank you,
>     Bruno
If you are speaking about the response variable, it's better to use a 
formal model such as the proportional odds model (generalization of the 
Wilcoxon test).  That way you can do meaningful interaction tests and 
much more, plus handle ties elegantly with likelihood ratio tests.  Some 
researchers have developed mixed effects prop. odds models (which I 
haven't used yet).

Frank
> 
> 
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> Bruno L. Giordano, Ph.D.
> CIRMMT
> Schulich School of Music, McGill University
> 555 Sherbrooke Street West
> Montr?al, QC H3A 1E3
> Canada
> http://www.music.mcgill.ca/~bruno/
> 
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> 

-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

Bruno L. Giordano <bruno.giordano <at> music.mcgill.ca> writes:
> 
> I am looking for references about mixed models built on rank transformed 
> data.

To complement Frank H: Try lrm in package Design.

Dieter