[Eeglablist] Bootstrap significance probability level

[Francesco Versace]

you can also look at: 
Randomization tests for ERP topographies and whole 
spatiotemporal data matrices
Eric Maris
Psychophysiology
 January 2004 - Vol. 41 Issue 1 

francesco



Quota Christopher Summerfield 
<summerfd at paradox.psych.columbia.edu>:

> dear Adrian, the familywise error rate can be 
calculated for bootstrap
> stats in the following way:
> 
> 1) calculate your statistics at every 
timepoint/voxel/whatever (we'll call
> these 'point estimate statistics')
> 2) shuffle and permute
> 3) for each permutation, enter the *maximum* 
permuted value from across
> all the sampled timepoints/voxels into a distibution
> 4) 'point estimate' statistics falling within the 
95% confidence interval
> of this distribution can be considered significant, 
adjusted for
> familywise error.
> 
> for more information, see Burgess & Gruzelier, 1999
> Methodological advances in the analysis of event-
related desynchronization
> data.	in Event-Related Desynchronization ed Gert 
Pfurtscheller, F H
> Lopes Da Silva.
> 
> this process could be adapted to provdide false 
discovery rate correction
> (see Genovese et al 2002).
> http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?
cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=11906227
&query_hl=1
> 
> good luck,
> Chris
> 
> 
> 
> Christopher Summerfield
> summerfd at psych.columbia.edu
> 
> On Mon, 31 Oct 2005, Adrian Guggisberg wrote:
> 
> > Hello
> >
> > I wonder, whether anyone has some practical 
considerations about which
> level
> > of significance probability should be chosen for 
bootstrap statistics.
> >
> > Since we have to deal with multiple comparisons, 
the significance
> threshold
> > should be decreased, but the question is how much. 
As much as I
> understand,
> > the Bonferroni correction for multiple testing 
would correspond to a
> level
> > of p < 0.05/(number of time points * number of 
frequency bins). However,
> > this would require a very high amount of surrogate 
data.
> >
> > Most of the studies seem to use p-values < 0.01. 
What's the argumentation
> > for this?
> >
> > In their J Neurosci Meth; 2004:9-21 Paper, Arnaud 
Delorme and Scott
> Makeig
> > write that they have
> > "implemented a method to fit the observed data 
distribution using a forth
> > order distribution fit. This feature will be 
available in a near-term
> release
> > of EEGLAB."
> > Does this feature allow a significance level of 
0.05? Is there a way to
> obtain
> > it?
> >
> > Thank you very much for your help.
> >
> >
> > Adrian Guggisberg, MD
> > Neurologische Klinik und Poliklinik
> > Inselspital
> > CH-3010 Bern
> > Switzerland
> >
> > 
_______________________________________________________
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geo.org/
> >
> >
> >
> >
> >
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-------------------------------------
Francesco Versace
NIMH Center for the Study of Emotion and Attention 
 University of Florida  P.O. Box 100165 HSC  
 Gainesville, FL  32610-0165    
 352.392.2439 phone
 352.392.6047 fax  
 fversace at ufl.edu 
------
Dipartimento di Psicologia
Università degli Studi di Trieste
Via S. Anastasio,12
34134 Trieste, Italy
e-mail versace at psico.univ.trieste.it
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