[R] Rank transformation and the linear mixed model

[Bruno L. Giordano]

----- Original Message ----- 
From: "Frank E Harrell Jr" <f.harrell at vanderbilt.edu>
To: "Bruno L. Giordano" <bruno.giordano at music.mcgill.ca>
Cc: <r-help at stat.math.ethz.ch>
Sent: Friday, November 03, 2006 8:22 AM
Subject: Re: [R] Rank transformation and the linear mixed model


> 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
>

That's a nice start indeed!!

However, I am referring both to rank transformation of response variables
and covariates.

The reference to this idea is the work by Conover and Iman (e.g., Conover
and Iman - 1981 - Rank transformations as a bridge between parametric and
nonparametric statistics).

The need would be to handle robustly monotone and nonlinear 
response-covariates relationships.

    Bruno

>>
>>
>> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>> Bruno L. Giordano, Ph.D.
>> CIRMMT
>> Schulich School of Music, McGill University
>> 555 Sherbrooke Street West
>> Montréal, 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
>