[R] normality test

[Frank E Harrell Jr]

Achim Zeileis wrote:
> On Thu, 28 Apr 2005 08:52:33 -0500 roger koenker wrote:
> 
> 
>>For my money,  Frank's comment should go into fortunes.  It seems a
>>rather Sisyphean battle to keep the lessons of robustness on the 
>>statistical table but nevertheless well worthwhile.
> 
> 
> Added.
> 
> On more comment: maybe it's also worth noting that you don't necessarily
> have to rank-transform the data. Instead you can also use a permutation
> test based on the original observations.

That deals with type I error but not necessarily type II error.  -Frank

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> This approach is implemented in the coin package for conditional
> inference.
> </advertisment>
> 
> Z
> 
> 
> 
>>url:    www.econ.uiuc.edu/~roger                Roger Koenker
>>email   rkoenker at uiuc.edu                       Department of
>>Economics vox:    217-333-4558                            University
>>of Illinois fax:    217-244-6678                            Champaign,
>>IL 61820
>>
>>On Apr 28, 2005, at 7:46 AM, Frank E Harrell Jr wrote:
>>
>>
>>>Usually (but not always) doing tests of normality reflect a lack of 
>>>understanding of the power of rank tests, and an assumption of high 
>>>power for the tests (qq plots don't always help with that because of
>>>their subjectivity).  When possible it's good to choose a robust 
>>>method.  Also, doing pre-testing for normality can affect the type I
>>>error of the overall analysis.
>>>
>>>-- 
>>>Frank E Harrell Jr   Professor and Chair           School of
>>>Medicine
>>>                     Department of Biostatistics   Vanderbilt 
>>>University
>>>
>>>______________________________________________
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>>
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> 
> 


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