[Eeglablist] statistics in EEGLAB

Fri Nov 13 10:48:49 PST 2009

I agree. For example, if there are 3 subjects, then simple binomial
probability can give no better a result than p <= 12.5%.  However, in the
case that each single-subject effect, across single trials, is significant
(e.g., at the p < .001% level), a much stronger inference can be derived
using reasonable subject distribution assumptions.

Scott

On Thu, Nov 12, 2009 at 4:03 AM, Robert Brown <bobrobbrown at googlemail.com>wrote:

> Dear Arno and All,
>
> thank you very much for your enlightening response.
>
> maybe one idea: let's say that I only have 4 subjects. the statistics based
> on "subject means" would be unreliable and I would not get any results.
> however, it could be that in case of each single subject there is a
> significant difference based on trials in the same time window, which would
> actually be a strong evidence for differences between the conditions and
> which could be written as "in case of each single subject p < .05
> (corrected)". I am sorry if this is not right, but I assume that there could
> be instances where the group statistics with 3-4 subjects would not show
> anything but the single trial statistics would. (good examples of important
> studies with so few subjects would be Tong & Engel, 2001 in Nature with 4
> subjects fMRI and Resulaj et al., 2009 in Nature with 3 subjects behavior.).
>
>
> to conclude: maybe the single trial statistics would work, if it a) would
> be calculated individually for each subject based on only this subjects
> single trials and then b) the (time-frequency) regions would be plotted,
> where all the subjects have significant differences based on their single
> trial analysis.
>
> thank you for your attention and good luck,
>
> Bob
>
> 2009/11/11 Arnaud Delorme <arno at ucsd.edu>
>
>> Dear Bob,
>>
>> thanks for the comments. I think you are using the statmode option "trial"
>> from the command line. This option is quite experimental. It was implemented
>> a while ago and is probably not forward compatible with more recent changes.
>> Also, the "statmode", "trials" option (assuming it was working) should only
>> be used to plot a single subjects. The reason is based on the type of null
>> hypothesis.
>>
>> When testing with 'statmode', 'subject' for two conditions, the NULL
>> hypothesis is: given the subjects I have recorded and given that these
>> subjects are a good representation of the general population of all possible
>> subjects, there is no difference between the ERP/spectrum/ERSP/ITC between
>> the two experimental conditions in the general subject population. Using
>> parametric, permutation, or bootstrap statistics (and assumptions) you may
>> either accept or reject this hypothesis at a given confidence level.
>>
>> When testing with 'statmode', 'trial' on a single subject (still two
>> conditions), the NULL hypothesis is : given the trials I have recorded and
>> given that these trials are a good representation of all the population of
>> trials for this subject, there is no difference between the
>> ERP/spectrum/ERSP/ITC between the two experimental conditions for this
>> subject. Again, using parametric, permutation, or bootstrap statistics (and
>> assumptions) you may either accept or reject this hypothesis at a given
>> confidence level.
>>
>> As you can see the two hypothesis are quite different. One makes an
>> inference about the population of subjects and the other one about the
>> population of trials.
>>
>> Now if you pool the trials from different subjects and attempt to perform
>> statistics, this is going to be more complex. The new hypothesis would then
>> be: given the trials I have recorded from my subjects and given that these
>> trials are a good representation of all the population of trials from the
>> general population of subjects, there is no difference between the
>> ERP/spectrum/ERSP/ITC between the two experimental conditions in the general
>> population of subjects. But the hypothesis is relatively biased because I
>> personally think that all the trials are *not* a good representation of
>> all the population of trials from the general population of subjects. The
>> trials are a good representation of all the trials from all the subjects
>> being presently recorded but not necessarily of the general subject
>> population. Therefore the real NULL hypothesis would be : given the trials I
>> have recorded from all of my subjects and given that these trials are a good
>> representation of all the population of trials from these subjects, there is
>> no difference between the ERP/spectrum/ERSP/ITC between the two experimental
>> conditions in the recorded subjects. As you see, rejecting the NULL this is
>> relatively limited as we care about the general population of subjects and
>> not the recorded subjects.
>>
>> If anybody has some better ideas (or Matlab function) of how to handle the
>> subject/trial problem (because it would be nice to include trials in
>> statistical analysis in order to make them more powerful), we will take
>> them.
>>
>> Best,
>>
>> Arno
>>
>> ps: we will remove the 'statmode', 'trial' option for now.
>> pps: for basic inferential statistics, you may also refer to this book
>> chapter http://sccn.ucsd.edu/~arno/mypapers/statistics.pdf<http://sccn.ucsd.edu/%7Earno/mypapers/statistics.pdf>
>>
>> On Nov 11, 2009, at 12:29 AM, Robert Brown wrote:
>>
>> Dear Arno & others,
>>
>> this does not seem to be as simple as Arno suggested (but thanks),
>>
>> 1. I have precomputed the values of these channels (with "savetrials",
>> "on")
>> 2. these channels all have data
>> 3. I can plot the data of the same channels when I use "statmode",
>> "subjects"
>> 4. I'm using EEGLAB v7.1.3.13b
>> 5. I now tried it with v7.1.7.18b and I still get the log of zero error
>> (you guys might be interested that in addition I now get, in case of
>> permutations and bootstrap, "??? Error using ==> reshape" in
>> statcond>surrogate at 438 and statcond at 301 and with this latest version
>> the reshape error even happens with the "statmode", "subjects")
>>
>> thus any other suggestions of what could be happening with my single trial
>> analysis in study would be very much appreciated.
>>
>> thank you very much and take care,
>> Bob
>>
>> 2009/11/11 Arnaud Delorme <arno at ucsd.edu>
>>
>>> Dear Bob,
>>>
>>> I think this might be because you are trying to plot ERSP of a channel
>>> that contains only 0. This error was also arising in old versions of EEGLAB
>>> when masking for significance.
>>>
>>> Hope this helps,
>>>
>>> Arno
>>>
>>>
>>> On Nov 7, 2009, at 11:38 AM, Robert Brown wrote:
>>>
>>>  Hi guys,
>>>>
>>>> I've been trying to get the study ersp analysis working on single trials
>>>> but I've not succeeded.
>>>>
>>>> in the function "std_readdata" I get the "Warning: Log of zero." error,
>>>> which is on the line ersp{c,g} = 20*log10(abs(ersp{c,g})); meaning that the
>>>> absolute value at some point is 0.
>>>> (This leads to) further errors:
>>>>
>>>> ??? Error using ==> set
>>>> Bad value for axes property: 'CLim'
>>>> Values must be increasing and non-NaN.
>>>>
>>>> Error in ==> caxis at 80
>>>>            set(ax,'CLim',arg);
>>>>
>>>> Error in ==> tftopo at 714
>>>> caxis([g.limits(5:6)]);
>>>>
>>>> I've tried to fix it but I'm not clever enough. any help would be
>>>> appreciated.
>>>>
>>>> thank you so much,,
>>>> Bob <ATT00001.txt>
>>>>
>>>
>>>
>>
>>
>
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-- 
Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation, University of
California San Diego, La Jolla CA 92093-0961, http://sccn.ucsd.edu/~scott
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