[Eeglablist] FDR parameters

[Nils Hachmeister]

Hello,

thanks for your reply. I agree: The only way I could imagine how to pass 
an alpha value from the GUI to the function is by putting it in the only 
remaining field which is related to that topic. That would be the field 
where I would put my p-value threshold when I were using FDR (or some 
other means of multiple comparison correction). Hence, my, and 
apparently also your assumption is that the field for p-value threshold 
is somewhat double use: It changes its meaning (albeit not its label) 
when you are doing FDR, now taking the FDR alpha value. However, because 
the alpha parameter of the fdr-function is optional it would also be 
possible that you cannot put the alpha value at all, using the GUI. 
However, then the results should not change depending on the value I put 
into the p-value threshold field, as FDR determines its own p-value 
threshold and the value I put into the p-value threshold field should be 
ignored. But the results clearly depend on the value I put into that 
field, which is, in my opinion, a strong indication that our assumption 
is, indeed, true.

Can anyone confirm Makoto's and my assumption?

Thanks

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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