[Eeglablist] toolboxes for multiple testing of time-frequency data

cyril pernet cyril.pernet at ed.ac.uk
Thu Jan 23 01:42:55 PST 2014


Hi Arnaud,

> According to Guillaume Rousselet and Cyril Pernet, this is the only 
> method that adequately control for type I error rate when correcting 
> for multiples comparisons (so if you have an uncorrected threshold 
> p-value at 0.05, you corrected p-value threshold will be exactly 0.05 
> corrected for multiple comparisons - which might not be the case when 
> using other methods). I tend to agree with them.

In fact, in our LIMO EEG paper we show that F max also correct well, and 
in fact so does TFCE (in prep - will also be presented at OHBM this year).
So max statistics, cluster-mas, and TFCE are three methods which 
provides a good control over the family-wise type 1 error rate, that is 
at e.g. p=0.05 you will have about 5% false positives under the null 
hypothesis (H0). All three techniques however do differ in terms of 
power (i.e. under H1) with cluster-mass better than stat max, but at the 
cost of losing inferential power as cluster-mass only allows drawing 
conclusions about clusters. For TFCE it is not clear yet, but some 
results show it performs just as well as cluster-mass, and provides 
inference at the cell (time frame - electrode) level.

All 3 methods are available in the LIMO EEG toolbox
Cyril



-- 
Dr Cyril Pernet,

Academic Fellow
Brain Research Imaging Center
http://www.bric.ed.ac.uk/
Division of Clinical Neurosciences
University of Edinburgh
Western General Hospital
Crewe Road
Edinburgh
EH4 2XU
Scotland, UK

cyril.pernet at ed.ac.uk
tel: +44(0)1315373661
http://www.sbirc.ed.ac.uk/LCL/
http://www.sbirc.ed.ac.uk/cyril


The University of Edinburgh is a charitable body, registered in
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