[Eeglablist] permutation and FDR

[Eric Fields]

 Hi Szilvia,

If you are trying to correct for multiple comparisons across time points
and/or electrodes, there are permutation-based methods for doing this
available in the Mass Univariate Toolbox and the Factorial Mass Univariate
Toolbox:

https://openwetware.org/wiki/Mass_Univariate_ERP_Toolbox

https://github.com/ericcfields/FMUT/wiki

For background, see:

https://onlinelibrary.wiley.com/doi/full/10.1111/j.1469-8986.2011.01273.x

Eric

-----
Eric Fields, Ph.D.
Postdoctoral Fellow
Cognitive and Affective Neuroscience Laboratory
<https://www2.bc.edu/elizabeth-kensinger/>, Boston College
Aging, Culture, and Cognition Laboratory <http://www.brandeis.edu/gutchess/>,
Brandeis University
eric.fields at bc.edu

On Mon, Jun 11, 2018 at 10:24 AM, Ramtin Mehraram (Student) <
R.Mehraram2 at newcastle.ac.uk> wrote:

> Dear Szilvia,
>
> To my knowledge, the permutation-based statistics "corrects" for
> non-normal sample distribution. This allows you to use parametric tests
> (such as t-test) with any sample distribution. It does not correct for
> multiple comparisons.
>
> The false discovery rate (FDR) is not very conservative as Bonferroni is.
> FDR is usually recommended whether you have huge amount of data (like
> genetic data) or in exploratory stage of your study. A more "strict"
> correction is recommended when finalizing the obtained results.
>
> A good variant of the Bonferroni correction is the Holm-Bonferroni, which
> is slightly more powerful.
>
> I hope this helps.
>
> B.
>
> Ramtin Mehraram
> PhD Student @ramtinTVT
> Biomedical Research Building 3rd floor
> Institute of Neuroscience
> Newcastle University
> NE4 5PL, United Kingdom
> www.lewybodylab.org
> https://www.newcastlebrc.nihr.ac.uk/research-themes/dementia/
>
> -----Original Message-----
> From: eeglablist [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of
> Szilvia Linnert
> Sent: 08 June 2018 09:37
> To: EEGLABLIST <eeglablist at sccn.ucsd.edu>
> Subject: [Eeglablist] permutation and FDR
>
> Hi everyone,
>
> I am planning to use permutation-based statistics using the study function
> in EEGLAB.
>
> I am confused whether I need to correct for multiple comparisons (using
> FDR) additionally, or the permutation method itself also corrects for
> multiple comparisons. I've got contradictory suggestions about this.
>
> Many thanks ,
>
> Szilvia
>
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