[FieldTrip] Two-way permutation test

David Groppe david.m.groppe at gmail.com
Fri Aug 28 17:08:55 CEST 2015

Hi Matthias,
   If I understand you correctly, you can use a t-score based permutation
test to solve your problem. This procedure can test for an effect of factor
A, factor B, and their interaction as described here:



On Fri, Aug 28, 2015 at 9:31 AM, Fritsche, M. (Matthias) <
m.fritsche at student.ru.nl> wrote:

> Dear Fieldtrip mailing list,
> my name is Matthias Fritsche and I'm a research intern in Floris de
> Lange's 'Prediction & Attention' group at the Donders Center for Cognitive
> Neuroimaging. I'm currently working on my Master's project and have got a
> question I hope you might be able to help me with.
> I'm currently at the data analysis stage of a behavioral experiment and
> wondered whether there is a possibility to conduct a two-way permutation
> test (ANOVA-style, but without actually using ANOVAs/F-values).
> My experiment has two independent variables, let’s call them A and B, and
> one dependent variable. Every participant was tested in all of the four
> conditions, A1B1, A2B1, A1B2 and A2B2. The dependent variable is a
> parameter of a model that is fit to the data. However, due to unstable
> fitting at the subject level, I can only obtain this parameter from the
> group-averaged data.
> When only interested in effects between two specific conditions, e.g. A1B1
> vs A2B1, the test is straightforward. In order to create the null
> distribution, I randomly swap the condition labels, A1B1 and A2B1, for each
> participant and compute the resulting group test statistic (difference of
> the dependent variable between A1B1 and A2B1) for that permutation. One
> option would be to test the difference between every two conditions in this
> way.
> However, I wondered whether there is also a way to use a permutation test
> similar to a 2-way ANOVA, i.e. testing the main effects of factor A and
> factor B, as well as the interaction effect. For that purpose, there seem
> to be permutation tests that use ANOVAs to generate permutation
> distributions of F-values. However, I cannot use ANOVAs since I only have
> the dependent variable for the whole group and not for individual
> participants. Do you know of any method to solve this?
> Thanks for your help.
> Best,
> Matthias
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> fieldtrip at donders.ru.nl
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