[FieldTrip] Permutation test design matrix for grand-averaged ERPs

Eelke Spaak e.spaak at donders.ru.nl
Tue Oct 23 14:59:26 CEST 2018

Hi Kate,

You can't do permutation statistics if you've already consumed the
degrees of freedom you want to do statistics across (i.e., subjects in
this case).

Did you use cfg.keepindividual = 'yes' in the call to
ft_timelockgrandaverage? If so, then the design matrix should be
specified exactly as in the tutorial; just as if you had been using
the individual subjects' data structures. If not, then indeed you only
have a grand-average left, and no permutation stats can be performed.

On Tue, 23 Oct 2018 at 14:04, Kate Stone <katemsto at gmail.com> wrote:
> Hi all,
> I've been following the tutorial here to do a time-locked perm test on ERP data: www.fieldtriptoolbox.org/tutorial/cluster_permutation_timelock
> I have computed grand averages for my two conditions and am using indepsamplesT with ft_timelockstatistics(cfg, GA_1, GA_2).
> But what should the design matrix be? The example in the tutorial doesn't apply as I am using grand averages and the reference for ft_timelockstatistics doesn't mention the design matrix, although it is definitely required. I have tried design = [1,2], but this doesn't seem to give sensible results.
> Thanks in advance,
> Kate
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> https://doi.org/10.1371/journal.pcbi.1002202

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