[pymvpa] effect size (in lieu of zscore)

[Yaroslav Halchenko]

On Thu, 22 Dec 2011, Mike E. Klein wrote:
> got rid of 2 of my 3 "sound" conditions. The experiment involved 81
> presentations of each of 3 sound conditions (243 total), and 81
> presentations of of rest/baseline. After some averaging, this is reduced to
> 27 of each.
> ...
> *The old line was:*
> zscore(dataset, chunks_attr='chunks', param_est=('targets', ['rest']),
> dtype='float32')
> which I just ripped off from one of the website's tutorial pages.
> The new line removed the "param_est=('targets', ['rest'])" and left
> everything else the same.

so  here is the catch ;-)  from above I deduce that you had only 81/27=3
samples of 'rest' within each chunk... so mean/variance estimation
was not really "good" (I think some time recently I even added a warning
for such cases [1] -- which version are you using? ;-))

[1]
https://github.com/PyMVPA/PyMVPA/blob/master/mvpa2/mappers/zscore.py#L149

> Just to be clear: 9 runs, each containing 39 volumes (this was slow
> event-related sparse sampling). 3 of these were used for an orthogonal
> behavioral task and thrown out. The remaining 36 (in each run) were
> 9xsilence, 9xSound1, 9xSound2, and 9xSound3. For my "against silence" MVPA
> sanity check above, I threw out 2 of the sound conditions, so the remaining
> sound and silence should be balanced. For my more empirically interesting
> analyses, I've been throwing out the rest and one of the sound conditions,
> so the classifier looks at 2 balanced sound conditions.

d'oh -- I wrote above first before reading this... but I guess ok -- so
you used 3 volumes after each stimuli onset, that is why for 3 'rest'
conditions in each run you had 9 volumes?  then pretty much the same
logic applies on "why it didn't work", although the warning obviously
wouldn't be triggered for such cases


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