mne.stats.
permutation_t_test
(X, n_permutations=10000, tail=0, n_jobs=1, seed=None, verbose=None)[source]¶One sample/paired sample permutation test based on a t-statistic.
This function can perform the test on one variable or simultaneously on multiple variables. When applying the test to multiple variables, the “tmax” method is used for adjusting the p-values of each variable for multiple comparisons. Like Bonferroni correction, this method adjusts p-values in a way that controls the family-wise error rate. However, the permutation method will be more powerful than Bonferroni correction when different variables in the test are correlated (see [1]).
Parameters: |
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Returns: |
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Notes
If n_permutations >= 2 ** (n_samples - (tail == 0))
,
n_permutations
and seed
will be ignored since an exact test
(full permutation test) will be performed.
References
[1] | (1, 2) Nichols, T. E. & Holmes, A. P. (2002). Nonparametric permutation tests for functional neuroimaging: a primer with examples. Human Brain Mapping, 15, 1-25. |
mne.stats.permutation_t_test
¶