mne.stats.fdr_correction¶

mne.stats.fdr_correction(pvals, alpha=0.05, method=’indep’)[source]¶

P-value correction with False Discovery Rate (FDR).

Correction for multiple comparison using FDR.

This covers Benjamini/Hochberg for independent or positively correlated and Benjamini/Yekutieli for general or negatively correlated tests.

Parameters:	pvals : array_like set of p-values of the individual tests. alpha : float error rate method : ‘indep’ | ‘negcorr’ If ‘indep’ it implements Benjamini/Hochberg for independent or if ‘negcorr’ it corresponds to Benjamini/Yekutieli.
Returns:	reject : array, bool True if a hypothesis is rejected, False if not pval_corrected : array pvalues adjusted for multiple hypothesis testing to limit FDR

Notes

Reference: Genovese CR, Lazar NA, Nichols T. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage. 2002 Apr;15(4):870-8.

Examples using mne.stats.fdr_correction¶

FDR correction on T-test on sensor data

Mass-univariate twoway repeated measures ANOVA on single trial power