[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
threshold.
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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