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Hi there,<br>
<br>
we just published a new toolbox (LIMO EEG) which allows to this kind
of analysis no problem - indeed it deals with any designs :-)<br>
you will have to analyze each subject (1st level) specifying the 2
conditions which will allow you to obtain beta parameters (or
regression coef if you prefer) for each condition (and electrodes
and time frames). Then perform a second level analysis you can do
the repeated measure x gp anova on those beta parameters (see
hierarchical linear model in wikipedia). At this stage our toolbox
uses bootstrap and spatial-temporal clustering to correct for
multiple comparisons. Such analysis will tell you if, at the
population level, you have gp differences, conditions differences
and interactions (again for all electrodes and time frames if you
wish).<br>
<br>
You can find the toolbox here
<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>
and paper here <a class="moz-txt-link-freetext" href="http://www.hindawi.com/journals/cin/2011/831409/">http://www.hindawi.com/journals/cin/2011/831409/</a><br>
<br>
Best<br>
Cyril<br>
<br>
<blockquote
cite="mid:93DB8219-40CE-497C-A3CC-D8AEE8469C7D@psy.gla.ac.uk"
type="cite">
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<div>2) Non-bootstrap options: for permutation or
parametric, and calculating stats on first and
second variable, the matlab window output suggests
that I should not be running this type of ANOVA on
the parametric/permutation data, e.g.:</div>
<div><br>
</div>
<div>... (2 balanced 1-way ANOVAS and then 4 paired
t-tests)</div>
<div>4 x 2, unpaired data, computing F values</div>
<div>Using balanced 2-way ANOVA<b><i> (not suitable
for parametric testing, only bootstrap)</i></b></div>
<div>...</div>
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<div>You have a mixed design (paired for one variable
and unpaired for the other one). Therefore the
balanced Anova is not strictly correct (both variables
should be unpaired). For permutation, it does not
really matter (the ANOVA computation is just a way to
compute a combined 2x2 measure - and the pairing of
values is preserved based on your settings during the
permutation). There is no functions in Matlab to
handle this special case to our knowledge, but there
is one in "R". Email David Groppe for more info <<a
moz-do-not-send="true"
href="mailto:dgroppe@cogsci.ucsd.edu">dgroppe@cogsci.ucsd.edu</a>>.</div>
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<br>
<pre class="moz-signature" cols="72">--
Dr Cyril Pernet,
Academic Fellow
SBIRC fMRI Manager
SFC Brain Imaging Research Center
Division of Clinical Neurosciences
University of Edinburgh
Western General Hospital
Crewe Road
Edinburgh
EH4 2XU
Scotland, UK
<a class="moz-txt-link-abbreviated" href="mailto:cyril.pernet@ed.ac.uk">cyril.pernet@ed.ac.uk</a>
tel: +44(0)1315373661
<a class="moz-txt-link-freetext" href="http://www.sbirc.ed.ac.uk/cyril">http://www.sbirc.ed.ac.uk/cyril</a>
<a class="moz-txt-link-freetext" href="http://www.sinapse.ac.uk/">http://www.sinapse.ac.uk/</a>
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