[Eeglablist] FDR parameters

Nils Hachmeister nils.hachmeister at uni-bielefeld.de
Fri Jan 27 04:40:09 PST 2017

Hello all,

at least for the pop_newtimef function I was able to confirm that, yes, 
the content of the p-value threshold field is fed into the fdr as alpha 
value. I feel confident that this is consistently done for STUDY plots 
using FDR.

Actually, when you use pop_newtimef with FDR it outputs something like 
"ERSP correction for multiple comparisons using FDR, alpha_fdr = 
0.024876" which I I find a little misleading. Because the number printed 
is actually the return value of the fdr function, namely the p-value 

Regardless, thanks for the support

Best Nils

Am 26.01.2017 um 23:00 schrieb Makoto Miyakoshi:
> Dear Nils,
> I pasted the results from 'help fdr'. Apparently, it takes only two 
> inputs, p-values and alpha. So if you use any value other than 
> p-values, that should be alpha.
> Makoto
> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> >> help fdr
>   fdr() - compute false detection rate mask
>   Usage:
>     >> [p_fdr, p_masked] = fdr( pvals, alpha);
>   Inputs:
>     pvals   - vector or array of p-values
>     alpha   - threshold value (non-corrected). If no alpha is given
>               each p-value is used as its own alpha and fdr corrected
>               array is returned.
>     fdrtype - ['parametric'|'nonParametric'] fdr type. Default is
>               'parametric'.
>   Outputs:
>     p_fdr    - pvalue used for threshold (based on independence
>                or positive dependence of measurements)
>     p_masked - p-value thresholded. Same size as pvals.
>   Author: Arnaud Delorme, SCCN, 2008-
>           Based on a function by Tom Nichols
>   Reference: Bejamini & Yekutieli (2001) The Annals of Statistics
> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> On Wed, Jan 25, 2017 at 12:55 AM, Nils Hachmeister 
> <nils.hachmeister at uni-bielefeld.de 
> <mailto:nils.hachmeister at uni-bielefeld.de>> wrote:
>     Hi everyone,
>     I'm using the study structure and aim to generate different plots
>     including statistical testing (non-parametric) with multiple
>     comparison correction, namely FDR. I used FDR before (in a context
>     unrelated to eeglab) and it is my understanding that you pass a
>     parameter alpha to it. FDR returns a (common) threshold for
>     p-values which guarantees that the expected rate of type-I errors
>     among all rejections of the 0-hypothesis is smaller or equal to alpha.
>     Now, in the statistics menu in the eeglab gui and the
>     documentation at
>     https://sccn.ucsd.edu/wiki/Chapter_06:_Study_Statistics_and_Visualization_Options
>     <https://sccn.ucsd.edu/wiki/Chapter_06:_Study_Statistics_and_Visualization_Options>
>     I cannot really find that notion. There is no mention of a
>     parameter nor any constraints regarding the rate of type-I errors.
>     However, I noticed that when passing a value to the edit-field
>     labeled threshold the results change pretty much in a way
>     consistent with that field being used as FDR-alpha. But from the
>     documentation I cannot confirm this assumption. Can anybody here
>     confirm this?
>     Best
>     Nils
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> -- 
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego

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