[FieldTrip] Cluster-based permutation tests for between-subject design

[Eric Maris]

Hi Steve,



Have a look here: 
http://fieldtrip.fcdonders.nl/faq/how_can_i_test_an_interaction_effect_using_cluster-based_permutation_tests



Best,



Eric Maris



From: Stephen Politzer-Ahles [mailto:spa268 at nyu.edu]
Sent: woensdag 24 september 2014 11:18
To: fieldtrip at science.ru.nl
Subject: Re: [FieldTrip] Cluster-based permutation tests for between-subject 
design



Hi Eelke,



Thanks for this information. I just wanted to jump in and ask: what about 
for interactions in a mixed 2x2 design? For example, say I expect a 
difference between conditions A and B for group 1, but not group 2. Would 
the correct way to do this be to



1) make difference waves (A-B) for each participant, then

2) do a between-UO test on the difference waves using indepsamplesT?



In the past I have always tested within-UO interactions using basically this 
method (based on 
http://mailman.science.ru.nl/pipermail/fieldtrip/2011-January/003447.html), 
but I was under the impression that this is not OK for mixed designs (from 
this post: 
http://mailman.science.ru.nl/pipermail/fieldtrip/2011-September/004244.html)



Thanks,

Steve



>
> ------------------------------
>
> Message: 12
> Date: Wed, 24 Sep 2014 07:59:31 +0200
> From: Eelke Spaak <eelke.spaak at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Cluster-based permutation tests for
>         between-subject design
> Message-ID:
> 
> <CABPNLUomYPTw6m__+Wx8jRJc8HvyU-Pqc4Q7+G7czOjD502dfA at mail.gmail.com 
> <mailto:CABPNLUomYPTw6m__%2BWx8jRJc8HvyU-Pqc4Q7%2BG7czOjD502dfA at mail.gmail.com> 
>  >
> Content-Type: text/plain; charset=UTF-8
>
> Hello Dylan,
>
> You can analyse a between-subjects design exactly as you would a
> between-trials design (at least as far as the statistics step is
> concerned), in both cases the two conditions correspond to two groups
> of observations, and not to the same group of observations measured in
> two separate conditions (which would be a within-UO design). In
> FieldTrip, you would typically compute averages per subject, then use
> an "indepsamplesT" (or indepsamplesF with >2 conditions) statistic
> (not depsamples). indepsamplesT only requires one row in the design
> matrix, indicating the condition.
>
> Note that if you have e.g. timelock structures in two (or more) cell
> arrays, corresponding to the conditions, you can input them into the
> statistics function as follows:
>
> stat = ft_timelockstatistics(cfg, tlCondA{:}, tlCondB{:});
>
> without having to call ft_timelockgrandaverage. In fact, the above is
> the preferred way to do statistics now. (The same holds for
> ft_freqstatistics.)
>
> Hope that helps,
> Best,
> Eelke
>
> On 24 September 2014 02:32, Dylan DeLosAngeles
> <dylan.delosangeles at gmail.com> wrote:
> > Hello,
> >
> > So far, the tutorial on "Cluster-based permutation tests on 
> > time-frequency
> > data" has been very helpful.
> >
> > Out of the four combinations from the two UO-types (subjects and trials) 
> > and
> > the two experimental designs (between- and within-UO), the tutorial 
> > covers
> > statistics on data in two conditions in a between-trials, in a 
> > within-trials
> > and in a within-subjects design. However, I am wondering if there is any
> > information about the fourth type of experiment design: 
> > between-subjects.
> >
> > I have data for 2 groups with 12 subjects in each group. Both groups are
> > measured during 11 conditions.
> > Can I approach this in a similar fashion to within-subjects design 
> > (multiple
> > subjects in multiple experimental conditions), such that my design is
> > multiple groups in multiple experimental conditions. Is it a case of 
> > first
> > averaging over all trials belonging to each of the experimental 
> > conditions
> > for each subject (as instructed in tutorial), and then averaging over 
> > all
> > subjects in each group?
> >
> > Configuration code for setting up the design currently looks like this;
> > grp = 2;
> > subj = 11;
> > design = zeros(2, subj*grp);
> >
> > for i = 1:grp
> >     design(1,i:2:end) = i;
> > end
> >
> > idx = 1;
> > for i = 1:subj
> >     design(2,idx:idx+1) = i;
> >     idx = idx+2;
> > end
> >
> > Is there anything else I need to take into consideration when doing 
> > these
> > statistics?
> >
> > Thank you,
> > Dr Dylan DeLosAngeles
> > Research Fellow
> > Brain Signal Laboratory
> > Flinders University
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>

>
>
> All the forward modelling in FieldTrip is based on a user-specified
> MRI (preferably an individual one, but can be a template brain if an
> individual MRI is not available). You probably will want to have a
> look at this tutorial:
> http://fieldtrip.fcdonders.nl/tutorial/headmodel_eeg
>

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