[Eeglablist] Grand Average

[Alexander J. Shackman]

I would agree with Steve and Steve with this.

However, I wanted to underscore that "Giving some subjects more weight than
others" has a legitimate place. Robust regression, which is increasingly
used in neuroimaging, effectively weights subjects based on the residuals
as a means of down-weighting outlying cases.

See e.g.,
http://wagerlab.colorado.edu/files/papers/Wager_2005_Neuroimage_2.pdf

Take care,
Alex


On Tue, Oct 23, 2012 at 1:24 PM, Steve Luck <sjluck at ucdavis.edu> wrote:

> I agree with Steve Politzer-Ahles about this.  Giving some subjects more
> weight than others could lead to bizarre results, whereas differences in
> number of trials (and hence differences in measurement error) are likely to
> simply reduce statistical power (and only modestly in typical situations).
>
> More generally, the idea of using a sample of subjects to estimate the
> parameters of a larger population would be greatly distorted by giving some
> subjects greater weight than others.
>
> Steve Luck
>
> *From: *Stephen Politzer-Ahles <politzerahless at gmail.com>
> *Subject: **Re: [Eeglablist] Grand Average*
> *Date: *October 22, 2012 5:18:30 PM PDT
> *To: *Alberto Gonzalez V <vilanova5 at hotmail.com>
> *Cc: *<eeglablist at sccn.ucsd.edu>
>
>
> Hello Alberto,
>
> There may be discussion of this issue in Luck (2005) and/or Handy (2004);
> if there is, you can ignore what I say and check those instead.
>
> My assumption, though, is that the reason we typically average them the
> way we do, instead of using a weighted average, is that more epochs does
> not necessarily mean better data. It's true that an insufficient number of
> epochs (and/or subjects) will make the ERP noisy. But once you reach a
> certain point, adding more epochs does not make the data a lot better (see
> Luck's (2005) discussion of the signal-to-noise ratio). Each subject is
> meant to be one datapoint, so once a given subject reaches the threshhold
> after which she has "enough" trials to make a good ERP, then it's fair to
> make that subject a datapoint.
>
> Also, of course, the characteristics of the ERP components you are
> interested in are likely to differ across subjects; some people may have a
> bigger P300 or N400 or whatnot overall. There is not necessarily a
> straightforward relationship between this and how clean their data are
> (i.e., it's not necessarily the case that someone who has a bigger/smaller
> P300 also happens to blink more/less during the experiment). Thus, by
> weighting subjects differently because of how many clean epochs they
> happened to have, you may be inadvertently biasing your grand averages
> towards certain individuals. At least when you treat all subjects equally,
> you are neutral as far as that is concerned.
>
> Those are just my impressions; I don't know if there is published
> literature discussing this topic, and if there is then it of course is a
> better reference than my impressions!
>
> Best,
> Steve
>
> On Mon, Oct 22, 2012 at 7:51 AM, Alberto Gonzalez V <vilanova5 at hotmail.com
> > wrote:
>
>> Hi to all,
>>
>> I have a question about ERP methodology. Consider that we record the EEG
>> during and task  in 3 subjects, then we do the averages  ( considering that
>> the task has 60 epochs):
>>         Subject 1  did a perfect task, so we did the average with 60
>> epochs.
>>         Subject 2 had some problems during the recording, and the average
>> was done with 40 epochs.
>>         Subject 3 had only 20 epochs, but we think that it´s enough and
>> did the average.
>>
>> So the Subj 1 has all the epochs =1, Subj 2 has = 2/3 of the epochs, and
>> Subj 3 has only =1/3. But in the grand averages we treat them as they had
>> all the epochs (=1). Isn't better to give each subject a proportional value
>> (considering it's number of epochs) in the grand average(something like:
>>  ([Subj1*1]+[Subj2*2/3]+[Subj3*1/3])/2)?.
>>
>> Thanks for your time!!!
>>
>
>
>
>
>
>
>
>
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-- 
Alexander J. Shackman, Ph.D.
HealthEmotions Research Institute | Lane Neuroimaging Laboratory
Wisconsin Psychiatric Institute & Clinics
University of Wisconsin-Madison
6001 Research Park Boulevard
Madison, Wisconsin 53719

Telephone: +1 (608) 358-5025
Fax: +1 (608) 265-2875
Email: shackman at wisc.edu
http://psyphz.psych.wisc.edu/~shackman
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