[Mne_analysis] permutation_t_test

[Eric Larson]

        External Email - Use Caution        

> Does this function average over p-values from each subject, and because
of the high variance, the corresponding electrodes won't be significant?

No it does a permutation over the subjects (using sign flips), and the p
value is the proportion of time the (absolute) t score from the true data
was greater than the maximum (absolute) t value from the permutations. The
result for parametric data should be like what you get from just doing
`scipy.stats.ttest_1samp` on your data. For background, see:

https://mne.tools/dev/auto_tutorials/discussions/plot_background_statistics.html#non-parametric-tests

Eric



On Wed, Feb 19, 2020 at 11:29 AM Maryam Zolfaghar <
Maryam.Zolfaghar at colorado.edu> wrote:

>         External Email - Use Caution
>
> Hi all,
>
> I am wondering how the procedure behind "permutation_t_test" works. I have
> used the example here
> <https://mne.tools/stable/auto_examples/stats/plot_sensor_permutation_test.html#sphx-glr-auto-examples-stats-plot-sensor-permutation-test-py>
> for EEG data (averaged over time window with size [subjects X electrodes])
> and after plotting p-values, there are some areas that have red color (mean
> significant p-value) but without any significant electrodes. How could this
> be possible? Does this function average over p-values from each subject,
> and because of the high variance, the corresponding electrodes won't be
> significant?
>
>
> Thank you,
> -Maryam
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