[Eeglablist] questions about statcond and Permutation test

[Arnaud Delorme]

Dear Yamil,

in answer to your questions, the permutation used in EEGLAB is a randomization test. "Monte Carlo permutation" as you call it is what we call bootstrap (in which samples can be use more than once). And yes, you still have to apply FDR on the resulting p-values. This is performed using the following code snippet:

p_corrected = fdr(p_uncorrected);

Best regards,

Arno

On May 13, 2011, at 5:27 PM, Hector Yamil Vidal Dos Santos wrote:

> Hello everyone
> I'm using eeglab to perform a permutation test and I have some questions.
> I'm comparing eeg data acquired under two different conditions
> so
> DATA= {[nelectrodes x timepoints x ntrials under cond 1]  ,  [nelectrodes x timepoints x ntrials under cond 2]}
> 
> I'm using the statcond command as follow
> 
> [t df pvals] = statcond(DATA,'mode','perm','paired','off','naccu', 5000);
> 
> and this are my questions:
> What type of permutation test is this command running? Is a Monte Carlo permutation test (in which permutations can be use more than ones)? or is it a approximate randomization test (in which permutations does not repeat)?
> 
> I'm using 5000 permutation, but how can I calculate how many permutations is necessary to use depending on the amount of trials?
> 
> Last question: Do I still need to calculate False Discovery Rate and do something about it?
> 
> Best,
> Yamil
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