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Hi José,<br>
<br>
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<div class="headerdisplayname" style="display:inline;">Subject:
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[Eeglablist] comparing normal and clinical populations</td>
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<div class="headerdisplayname" style="display:inline;">From:
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Jose Rebola <a class="moz-txt-link-rfc2396E" href="mailto:jrebola@gmail.com"><jrebola@gmail.com></a></td>
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<div class="headerdisplayname" style="display:inline;">Date:
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04/12/2011 19:02</td>
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<div class="headerdisplayname" style="display:inline;">To: </div>
<a class="moz-txt-link-abbreviated" href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a></td>
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<div class="moz-text-html" lang="x-western">>Hi
<div>>I am running a study to investigate differences between
williams syndrome patients and controls in a visual task. I
have eight subjects of each >population.</div>
<div>>How do I compare the amplitude of the P100 between the
populations?</div>
<div>>Should i include only one value (the peak around 100ms on
each of the subject's average) per subject ? </div>
<div>>It seems to me that if i do this i will only have one
value per subject and i am "throwing away" the 100 trials per
condition that i have</div>
<div>>Isn't there a way that i can compare between populations
while retaining within-subject variability?<br>
<br>
<br>
This is indeed a very valid point, if you only compute the
average and take 1 value you do not account for within subject
variance.<br>
We have a toolbox LIMO_EEG which is fully compatible with EEGLAB
and does hierarchical linear modeling, thus accounting for
within and between subject variance - this handles pretty much
any kind of design you may have. For a simple group comparison,
you model the activity in your visual task for each subject
(assuming either at least 2 conditions or 1 condition with some
covariate like luminance, contrast, phase, etc) and then compare
the parameters obtained between groups - at this stage LIMO_EEG
use robust statistics making your inference much stronger.<br>
<br>
You can access and download the toolbox @
<a class="moz-txt-link-freetext" href="https://gforge.dcn.ed.ac.uk/gf/project/limo_eeg/">https://gforge.dcn.ed.ac.uk/gf/project/limo_eeg/</a><br>
<br>
<br>
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<div>> Otherwise, how does it compensate to perform 1000 trials
instead of 10?<br>
<br>
mathematically speaking it is the same (in terms of variance)
but of cource the average with 10 trials will be a poor
representation of the neural activity.<br>
<br>
<br>
Cyril<br>
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