[pymvpa] Balancing with searchlight and statistical issues.

[Roberto Guidotti]

Hi all mvpaers,

I need some theoretical help!

I did some analysis on a unbalanced dataset, 12 runs with 10 trials (5
condition A, 5 condition B), so I got 120 samples. Since I had an
unbalanced dataset, I could have a run with 7A vs 3B or also a 9A vs 1B
samples and/or viceversa.
I analyzed the dataset balancing samples in each run, using a leave TWO run
cross-validation (L2ROCV) searchlight, in order to have more combination of
samples to train the dataset and the same for the testing set, I didn't
analyze the dataset using different balancing since the searchlight in a
L2ROCV is high time consuming and I had 25 subjects with 3 unbalanced
dataset per subject!! :\

Now, my questions are these:

1) I used a good approach to analyze the dataset or you suggest a different
approach?

2) I did an average map of the 66 cross-validation map I obtained for each
subject; to do a first exploratory analysis I did a simple t-test versus
chance level (I didn't do the Stelzer's method because of the computational
time) and I had almost all voxels significative (not corrected), because of
the L2ROCV, I think. So do you think I can do other more robust statistical
tests using these maps? Or I have to do the Stelzer's method? Or throw away
the searchlight maps?

Thank you!!
Roberto
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