[pymvpa] FDR adjustment after permutation testing
n.n.oosterhof at googlemail.com
Thu Jun 18 12:41:53 UTC 2015
On 18 Jun 2015, at 14:10, H.Y. Chan <chan at rsm.nl> wrote:
> Maybe it's not related to the toolbox, but I'd be grateful if there's anyone who might have advice for me on multiple comparisons.
> I've done permutation testing using the toolbox and got a whole brain map of p values. I wonder if the only FDR procedure possible is voxel-wise?
I consider FDR as pretty evil for whole-brain multiple comparison correction. A strong cluster in one part of the brain can make another, very weak cluster elsewhere, survive.
> Is it possible to do cluster-wise FDR or threshold-free cluster enhancement (TCFE) (I don't know how FSL implements it)?
PyMVPA supports fixed-threshold Monte Carlo cluster-based correction in mvpa2/algorithms/group_clusterthr.py  for volumetric data.
If you are comfortable using Matlab / GNU Octave, consider CoSMoMPVA’s cosmo_montecarlo_cluster_stat [2,3] function, which supports both fixed-threshold and threshold-free cluster enhancement (TFCE) for volumetric and surface-based data.
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