spectral_connectivity.statistics.adjust_for_multiple_comparisons#

adjust_for_multiple_comparisons(p_values, alpha=0.05, method='Benjamini_Hochberg_procedure')[source]#

Corrects for multiple comparisons and returns the significant p-values.

Parameters:

  • p_values (array_like) –

  • alpha (float, optional) – The expected proportion of false positive tests.

  • method (string, optional) – Name of the method to use to correct for multiple comparisons. Options are “Benjamini_Hochberg_procedure”, “Bonferroni_correction”

Returns:

is_significant – A boolean array the same shape as p_values indicating whether the null hypothesis has been rejected (True) or failed to reject (False).

Return type:

boolean nd-array