[FieldTrip] 6d15

[Dr. Stephan Frisch]

Guten Tag, 
Hi, 

Ich bin vom 23.03.2023 bis 02.04.2023 nicht im Büro und kann die Emails nur sehr unregelmäßig lesen und beantworten. Die Emails werden auch nicht weitergeleitet.  

I am out of the office from 03/23/2023 to 04/022023 and can only read and answer emails very sporadically. The emails are also not being forwarded.  

Viele Grüße / Best regards
Stephan Frisch


Am 28.03.2023 um 14:42 schrieb philip Joadavi via fieldtrip <fieldtrip at science.ru.nl>:

> 
> Dear Dr.Maris/ Schoffelen /Oostenveld
> 
> I posted a question on the mailing list about 2x2 ANOVA at the source level (please see below my email).
> It's been 2 weeks and I have not found if there is anything wrong with my code.  I would really really appreciate it if you could have a look at my code and let me know if I have done all the steps correctly.
> 
> Thanks a lot,
> Philip
> 
> 
> 
> ---------- Forwarded message ---------
> From: philip Joadavi <p.joadavi at gmail.com>
> Date: Wed, Mar 15, 2023 at 5:14 PM
> Subject: 2x2 ANOVA at source level using cluster based permutation
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> 
> 
> Dear all,
> 
> I would like to run ANOVA  to test the main and interaction effects on my beamforming results. (I used DISC beamformer)
> I've already looked at the FAQ on the FieldTrip website and also the questions in the mailing list.
> 
> To check if I have done the steps correctly, I have also done the 2x2 ANOVA using SPM and I got significant results, but without FWE/FDR correction for multiple comparisons at the voxel level.
> 
> When I apply the steps described in the FieldTrip and also the mailing list (for cluster-based permutation) I could not get any significant clusters. This is surprising for me because I get always nicer results from permutation tests than I do not get from SPM.
> 
> I think I'm doing something wrong and I would appreciate any help.
> 
> So, as far as I understood, I can not use F statistics for 2x2 ANOVA, and therefore I used dependent sample T statistics for within-subject design as explained by Eric in the mailing list. 
> 
> here is my code :
> So, I have 2 conditions A and B, each with 2 levels (I & II).
> For the averages, I used ft_ grandaverage for 2 conditions/levels, and I got a matrix of pow = [number of subjects x number of voxels] = [12x 411477]
> 
> Here is the code:
> 
> my data is arranged such that the columns are the conditions (A/B) and the rows are the levels (I/II).
>  
> % Main effect of levels (I/II)
> I  = ft_sourcegrandaverage([],GA{1,1:2});
> II = ft_sourcegrandaverage([],GA{2,1:2});
>  
> % Main effect of conditions (A/B)
> A = ft_sourcegrandaverage([],GA{1:2,1});
> B = ft_sourcegrandaverage([],GA{1:2,2});
>  
> % Interaction effect
> cfg           = [];
> cfg.operation = 'subtract';
> cfg.parameter = 'pow'; 
>  
> INA = ft_math(cfg, GA{1,1}, GA{2,1}); % I - II (A)
> INB = ft_math(cfg, GA{1,2}, GA{2,2}); % I - II (B)
>  
>  
> %% prepare the hypothesis testing
> cfg                  = [];
> cfg.dim              = GA{1}.dim;
> cfg.method           = 'montecarlo';
> cfg.correctm         = 'cluster';
> cfg.spmversion       = 'spm12';
> cfg.parameter        = 'pow';
> cfg.numrandomization = 'all'; 
> cfg.correcttail      = 'alpha';
> 
> 
> cfg.statistic        = 'depsamplesT';
> cfg.alpha            = 0.05/2; % two tails
> cfg.clusteralpha     = 0.01;
> cfg.tail             = 0; % I also tried 1 for one tail
> cfg.clustertail      = cfg.tail;
> cfg.uvar             = 1; % subject
> cfg.ivar             = 2; % conditions
> cfg.design           = [repmat(1:numel(subjects),1,2); repelem([1 2],numel(subjects))];
>  
> 
> 
> stat{1}   = ft_sourcestatistics(cfg,I,II); % main effect (I/II)
> 
> stat{2}   = ft_sourcestatistics(cfg,A,B);  % main effect (A/B)
> 
> stat{3}   = ft_sourcestatistics(cfg,INA,INB); % Interaction
> 
> 
> Side note: I also tried the one-tail option, but the results were not significant eighter. 
> 
> 
> 
> 
> 
> 
> I would appreciate any help!
> Best,
> Philip
> 
>   
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