[R] Two-way non-parametric ANOVA?

[David Airey]

.

Just goes to show that Frank Harrell beats Google for statistics any  
day of the week!

I have got to try that PO model!!

On Jan 23, 2008, at 4:45 PM, Frank E Harrell Jr wrote:

> David Airey wrote:
>> While I defer to Frank as far as expertise goes, not having access  
>> to  his paper, I googled, and I just read that this kind of model  
>> is not  possible when there are a lack of ties for ranks in the  
>> data, and adds  an intercept for every rank in the data set. So  
>> while interpretation  doesn't get more difficult with additional  
>> ranks, unlike the  multinonimal model, Frank's suggestion would not  
>> fly for continuous  data that was transformed to ranks, as opposed  
>> to data collected as  ordered categories, where it would be  
>> preferable.
>
> That is incorrect, except for the part about needing one intercept  
> per unique value of Y, less one.  This only presents a RAM and  
> execution time problem.  Sometimes I put continuous data into 100  
> quantile groups to make this fast.  SAS JMP (after I suggested this  
> to them in 1982) handles an arbitrarily high number of unique Y  
> values as they made use of a patterned covariance matrix, which I  
> didn't in lrm.
>
> So the PO model is a competitor of ordinary regression.  A new  
> option in predict.lrm makes it easy to get the predicted mean in  
> this situation.
>
> Frank
>> On Jan 23, 2008, at 10:52 AM, Frank E Harrell Jr wrote:
>>> David Airey wrote:
>>>>> We need a two-way non-parametric ANOVA in order to analysis   
>>>>> properly  some ecological data, do you know any reference in R?  
>>>>> or  how to do  it? Thank you very much All the best diana
>>>>>
>>>> A couple more references here are below. I liked the Scheirer   
>>>> reference.
>>>> /*
>>>> Scheirer CJ, Ray WS, Hare N (1976) The analysis of ranked data   
>>>> derived
>>>> from completely randomized factorial designs. Biometrics 32:429-434
>>>> Groggel DJ, Skillings JH (1986) Distribution-free tests for main   
>>>> effects
>>>> in multifactor designs. American Statistician 40:99-102
>>>> */
>>> My guess is that those are a bit out of date, especially the  
>>> first  one, when compared to the PO model.
>>> Cheers
>>> Frank
>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>> -- 
>>> Frank E Harrell Jr   Professor and Chair           School of  
>>> Medicine
>>>                   Department of Biostatistics   Vanderbilt  
>>> University
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>
> -- 
> Frank E Harrell Jr   Professor and Chair           School of Medicine
>                     Department of Biostatistics   Vanderbilt  
> University

--
David C. Airey, Ph.D.
Pharmacology Research Assistant Professor
Center for Human Genetics Research Member

Department of Pharmacology
School of Medicine
Vanderbilt University
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