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 [1].

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

Parameters

pvalsarray_like: Set of p-values of the individual tests.
alphafloat: Error rate.
method‘indep’ | ‘negcorr’: If ‘indep’ it implements Benjamini/Hochberg for independent or if ‘negcorr’ it corresponds to Benjamini/Yekutieli.

Returns

rejectarray, bool: True if a hypothesis is rejected, False if not.
pval_correctedarray: P-values adjusted for multiple hypothesis testing to limit FDR.

References

1: 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`¶

Mass-univariate twoway repeated measures ANOVA on single trial power — Mass-univariate twoway repeated measures ANOVA on single trial power¶

Statistical inference — Statistical inference¶

FDR correction on T-test on sensor data — FDR correction on T-test on sensor data¶

Analysing continuous features with binning and regression in sensor space — Analysing continuous features with binning and regression in sensor space¶