[pymvpa] OneWayAnova for feature selection: how it works?

[Brian Murphy]

Hello Vadim,

you're right that the Anova feature selection is univariate. And also
for a two-class problem it gives an identical result to that you would
get with a t-test (F statistic is different from t-statistic, but what
matters is the ranking, which will be identical). I suppose the reason
PyMVPA uses Anova rather than t or z statistics, is so that it also
works for more than two classes.

> In one-way ANOVA with data analysis we might have subjects as
> between-group factor and treatment as within-group factor. But
> treating voxels as "subjects" does not help me because there is no
> grouping for voxels (grouping is for condition). 
> 
Hmmm, not sure, but if I read your analogy correctly, I think you should
be thinking of *trials* as being equivalent to subjects. 

best,

Brian
> 
> Any ideas? Any links for explanation would be also appreciated!
> 
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> Thanks,
> Vadim
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-- 
Dr. Brian Murphy
Lecturer (Assistant Professor)
Knowledge & Data Engineering (EEECS)
Queen's University Belfast
brian.murphy at qub.ac.uk