----- Original Message -----
From: "Frank E Harrell Jr" <[EMAIL PROTECTED]>
To: "Bruno L. Giordano" <[EMAIL PROTECTED]>
Cc: <[email protected]>
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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>> PLEASE do read the posting guide
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>>
>
>
> --
> Frank E Harrell Jr Professor and Chair School of Medicine
> Department of Biostatistics Vanderbilt University
>
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