test results and p-value correction for multiple tests
pvals : array_like
alpha : float
method : string
is_sorted : bool
returnsorted : bool
reject : array, boolean
pvals_corrected : array
alphacSidak: float :
alphacBonf: float :
There may be API changes for this function in the future.
Except for ‘fdr_twostage’, the p-value correction is independent of the alpha specified as argument. In these cases the corrected p-values can also be compared with a different alpha. In the case of ‘fdr_twostage’, the corrected p-values are specific to the given alpha, see fdrcorrection_twostage.
The ‘fdr_gbs’ procedure is not verified against another package, p-values are derived from scratch and are not derived in the reference. In Monte Carlo experiments the method worked correctly and maintained the false discovery rate.
All procedures that are included, control FWER or FDR in the independent case, and most are robust in the positively correlated case.
fdr_gbs: high power, fdr control for independent case and only small violation in positively correlated case
Most of the time with large arrays is spent in argsort. When we want to calculate the p-value for several methods, then it is more efficient to presort the pvalues, and put the results back into the original order outside of the function.
Method=’hommel’ is very slow for large arrays, since it requires the evaluation of n partitions, where n is the number of p-values.