[R] ANOVA non-sphericity test and corrections (eg, Greenhouse-Geisser)

Simon Blomberg s.blomberg1 at uq.edu.au
Mon Jun 25 09:53:59 CEST 2007

If you use lme, you can fit a general correlation structure to the
within-subject data, and compare the fit to a model assuming
uncorrelated within-subjects errors. That should tell you whether your
data are Aren't the G-G and H-F corrections only approximate fixes?
Surely it is better to work with a model that actually fits your data,
rather than using ad hoc adjustments towards a model that doesn't quite
fit. But I'm no psychologist. :-)



 On Mon, 2007-06-25 at 08:22 +0200, Peter Dalgaard wrote:
> DarrenWeber wrote:
> > I'm an experimental psychologist and when I run ANOVA analysis in
> > SPSS, I normally ask for a test of non-sphericity (Box's M-test).  I
> > also ask for output of the corrections for non-sphericity, such as
> > Greenhouse-Geisser and Huhn-Feldt.  These tests and correction factors
> > are commonly used in the journals for experimental and other
> > psychology reports.  I have been switching from SPSS to R for over a
> > year now, but I realize now that I don't have the non-sphericity test
> > and correction factors.
> >   
> This can be done using anova.mlm() and mauchly.test()  which work on 
> "mlm" objects, i.e., lm() output where the response is a matrix. There 
> is no theory, to my knowledge, to support it for general aov() models, 
> the catch being that you need to have a within-subject covariance matrix.
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Simon Blomberg, BSc (Hons), PhD, MAppStat. 
Lecturer and Consultant Statistician 
Faculty of Biological and Chemical Sciences 
The University of Queensland 
St. Lucia Queensland 4072 

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T: +61 7 3365 2506 
email: S.Blomberg1_at_uq.edu.au 

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be extracted from a given body of data. - John Tukey.

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