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<div class="headerdisplayname" style="display:inline;">Subject:
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Re: [Eeglablist] Statistical test</td>
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<div class="headerdisplayname" style="display:inline;">From:
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Makoto Miyakoshi <a class="moz-txt-link-rfc2396E" href="mailto:mmiyakoshi@ucsd.edu"><mmiyakoshi@ucsd.edu></a></td>
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<div class="headerdisplayname" style="display:inline;">Date:
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25/01/2017 01:53</td>
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<div class="headerdisplayname" style="display:inline;">To: </div>
ali zahedi <a class="moz-txt-link-rfc2396E" href="mailto:ali.zahedi.bham@gmail.com"><ali.zahedi.bham@gmail.com></a></td>
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<div class="headerdisplayname" style="display:inline;">CC: </div>
EEGLAB List <a class="moz-txt-link-rfc2396E" href="mailto:eeglablist@sccn.ucsd.edu"><eeglablist@sccn.ucsd.edu></a></td>
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<br>
Dear Ali,
<div><br>
</div>
<div>It is not totally clear, but the attached figure looks as if
you have 2 x 2 x 2 design. In this case, what you need is 3 way
ANOVA. Of course, you can apply t-test from the beginning as
planned test, but that can be recommended only when a small subset
of the t-tests are of your interest (you don't want to repeat it
too many times because of multiple comparison correction issues.)</div>
<div><br>
</div>
<div>So, why don't you try repeated measures 3 way, 2 x 2 x 2 ANOVA.<br>
Makoto</div>
<div><br>
<br>
--> just to add that this can easily be done using the LIMO EEG
toolbox (model the 6 conditions per subject then do an ANOVA
across subjects)<br>
<br>
Cyril<br>
<br>
<br>
<div class="gmail_quote">On Mon, Jan 23, 2017 at 10:05 AM, ali
zahedi <span dir="ltr"><<a
href="mailto:ali.zahedi.bham@gmail.com" target="_blank">ali.zahedi.bham@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">
<div dir="ltr">Dear List,
<div><br>
</div>
<div>
<div style="font-size:12.8px">I am working on EEG signal
processing and I need to apply statistical test on my
findings (paired t-test). However, I am not confident in
selecting the significance level which is usually set as
0.05 or 0.01, and I am not completely sure if the paired
t-test I have used is correct or not.</div>
<div style="font-size:12.8px"><br>
</div>
<div style="font-size:12.8px">I have 20 EEG datasets
collected from 20 individuals, and want to classify
relaxation versus stress. For pre-processing the data I
applied a chain of 3 different filters (F2,F3 and F4 as
shown in the attached figure); which resulted in 8
different pre-processing modes. After filtering I used 2
different classification method (Red and Green bars in
the attached figure) on the preprocessed data to see
which classification method works best. Furthermore, I
want to see if different filters that I have used have
significant effect on the performance of the
classification methods. </div>
<div style="font-size:12.8px"><br>
</div>
<div style="font-size:12.8px">As you can see I have three
different factors which may affect performance of the 2
classification methods.</div>
<div style="font-size:12.8px">In order to evaluate the
obtained results I performed a paired t-test on the
results.</div>
<div style="font-size:12.8px">In the first step, I wanted
to check if performance of the 2 classification methods
is different significantly. Therefore, I divided my data
into 2 groups of each having 160 samples (20 subjects *
8 modes) and performed a paired t-test.</div>
<div style="font-size:12.8px">In the next step, I wanted
to check if different filters have significant effect on
the performance of the classification methods or not.
Therefore, I divided the data into the following paired
groups:</div>
<div style="font-size:12.8px"><br>
</div>
<div style="font-size:12.8px">Pair1= Group 1: F2 is
applied (F21) Group 2: F2 is not applied (F20)</div>
<div style="font-size:12.8px">Pair2= Group 1: F3 is
applied (F31) Group 2: F3 is not applied (F30)</div>
<div style="font-size:12.8px">Pair3= Group 1: F4 is
applied (F41) Group 2: F4 is not applied (F40)</div>
<div style="font-size:12.8px"><br>
</div>
<div style="font-size:12.8px">Each of the groups in the
pairs consist of 160 samples (20 subjects * 2
classification methods * 4 modes).</div>
<div style="font-size:12.8px"><br>
</div>
<div style="font-size:12.8px">In my test I considered
p<0.05 as the significant level. I heard that 0.05 is
not always correct to be selected and it might be
divided by the number of measurements/repetitions due to
Bonferroni correction. For example here 0.05/3. </div>
<div style="font-size:12.8px">Is Bonferroni correction
necessary to be applied? and what would be the
significance level here? Is the paired t-test correct to
use here?</div>
<div style="font-size:12.8px"><br>
</div>
<div style="font-size:12.8px"><span
style="font-size:12.8px">I really appreciate it if you
could help me with this.</span><br>
</div>
<div style="font-size:12.8px"><br>
</div>
<div style="font-size:12.8px">Regards,</div>
<div style="font-size:12.8px">Ali </div>
</div>
</div>
</blockquote>
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