[R] Bartlett's Test of Sphericity

[peter dalgaard]

On Jun 18, 2011, at 10:48 , (Ted Harding) wrote:

> To add to Jeremy's comment below: The Bartlett test is very
> sensitive to non-normality in the data, so can readily give
> "significant" results even for non-correlated data.

Hmm, I wouldn't bet on that. Correlation tests are usually fairly robust. 

More likely, it's that the null hypothesis of complete independence is rather extreme, especially in a context where you are contemplating PCA or FA. (I.e., "Of _course_ they are correlated, dummy!"). 

> 
> Ted.
> 
> On 18-Jun-11 06:47:52, Jeremy Miles wrote:
>> cortest.bartlett() in the psych package.
>> 
>> I've never seen a non-significant Bartlett's test.
>> 
>> Jeremy
>> 
>> 
>> 
>> On 17 June 2011 12:43, thibault grava <thibault.grava at gmail.com> wrote:
>>> Hello Dear R user,
>>> 
>>> I want to conduct a Principal components analysis and I need to
>>> run two tests to check whether I can do it or not. I found how
>>> to run the KMO test, however i cannot find an R fonction for the
>>> Bartlett's test of sphericity. Does somebody know if it exists?
>>> 
>>> Thanks for your help!
>>> 
>>> Thibault
> 
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> E-Mail: (Ted Harding) <ted.harding at wlandres.net>
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> Date: 18-Jun-11                                       Time: 09:48:13
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-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
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