[Eeglablist] FDR parameters
mmiyakoshi at ucsd.edu
Fri Jan 27 09:52:56 PST 2017
> Can anyone confirm Makoto's and my assumption?
> 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.
See the highlighted parts below.
This is from newtimef() line 1439
if strcmpi(g.mcorrect, 'fdr')
alphafdr = fdr(exactp_ersp, g.alpha);
This is from 'help fdr'
>> help fdr
fdr() - compute false detection rate mask
>> [p_fdr, p_masked] = fdr( pvals, alpha);
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
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
So you are right, alphafdr should be the 'pvalue used for threshold'
On Fri, Jan 27, 2017 at 12:52 AM, Nils Hachmeister <
nils.hachmeister at uni-bielefeld.de> wrote:
> 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?
> 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.
> >> help fdr
> fdr() - compute false detection rate mask
> >> [p_fdr, p_masked] = fdr( pvals, alpha);
> 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
> 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> 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
>> 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?
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> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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