statsmodels.stats.multitest.fdrcorrection_twostage¶
- statsmodels.stats.multitest.fdrcorrection_twostage(pvals, alpha=0.05, method='bky', iter=False, is_sorted=False)[source]¶
(iterated) two stage linear step-up procedure with estimation of number of true hypotheses
Benjamini, Krieger and Yekuteli, procedure in Definition 6
- Parameters:
- pvalsarray_like
set of p-values of the individual tests.
- alpha
float
error rate
- method{‘bky’, ‘bh’)
see Notes for details
- ‘bky’ - implements the procedure in Definition 6 of Benjamini, Krieger
and Yekuteli 2006
‘bh’ - the two stage method of Benjamini and Hochberg
- iterbool
- Returns:
Notes
The returned corrected p-values are specific to the given alpha, they cannot be used for a different alpha.
The returned corrected p-values are from the last stage of the fdr_bh linear step-up procedure (fdrcorrection0 with method=’indep’) corrected for the estimated fraction of true hypotheses. This means that the rejection decision can be obtained with
pval_corrected <= alpha
, wherealpha
is the original significance level. (Note: This has changed from earlier versions (<0.5.0) of statsmodels.)BKY described several other multi-stage methods, which would be easy to implement. However, in their simulation the simple two-stage method (with iter=False) was the most robust to the presence of positive correlation
TODO: What should be returned?