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statsmodels.sandbox.stats.multicomp.multipletests

statsmodels.sandbox.stats.multicomp.multipletests(pvals, alpha=0.05, method='hs', returnsorted=False)

test results and p-value correction for multiple tests

Parameters :

pvals : array_like

uncorrected p-values

alpha : float

FWER, family-wise error rate, e.g. 0.1

method : string

Method used for testing and adjustment of pvalues. Can be either the full name or initial letters. Available methods are

`bonferroni` : one-step correction
`sidak` : on-step correction
`holm-sidak` :
`holm` :
`simes-hochberg` :
`hommel` :
`fdr_bh` : Benjamini/Hochberg
`fdr_by` : Benjamini/Yekutieli

returnsorted : bool

not tested, return sorted p-values instead of original sequence

Returns :

reject : array, boolean

true for hypothesis that can be rejected for given alpha

pvals_corrected : array

p-values corrected for multiple tests

alphacSidak: float :

corrected pvalue with Sidak method

alphacBonf: float :

corrected pvalue with Sidak method

Notes

all corrected pvalues now tested against R. insufficient “cosmetic” tests yet new procedure ‘fdr_gbs’ not verified yet, p-values derived from scratch not reference

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

there will be API changes.

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