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day14.html
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<div class="section" id="day-14-random-effects-choosing-models">
<h1>Day 14: random effects, choosing models<a class="headerlink" href="#day-14-random-effects-choosing-models" title="Permalink to this headline">¶</a></h1>
<p>5 / 29 / 2015</p>
<p>Reading:</p>
<ul class="simple">
<li>random versus fixed effect in neuroimaging literature
<a class="reference external" href="ftp://193.62.66.20/spm/data/face_rfx/RFXabstract.pdf">ftp://193.62.66.20/spm/data/face_rfx/RFXabstract.pdf</a>
<a class="reference external" href="http://www.fil.ion.ucl.ac.uk/spm/doc/books/hbf2/pdfs/Ch12.pdf">http://www.fil.ion.ucl.ac.uk/spm/doc/books/hbf2/pdfs/Ch12.pdf</a></li>
<li>a simple tutorial on cross validation
<a class="reference external" href="http://www.autonlab.org/tutorials/overfit.html">http://www.autonlab.org/tutorials/overfit.html</a></li>
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<dt>Recall t and F tests: what are they doing exactly. Where does my variability come from?</dt>
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<li>example within run (from previous course)</li>
<li>example random effect (between subjects).</li>
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<li>Wait a second: What is a model exactly ?</li>
<li>I am choosing a very wrong model: Consequences on the results of t/F tests.</li>
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<dt>How do I know my model is - is not very wrong? the good, the bad, the ugly (reverse order)</dt>
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<li>the ugly: p-hacking. Let’s try it.</li>
<li>the bad: use R2.</li>
<li>the good: model validation</li>
</ul>
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<li>Model validation: Principle. Example of “random effect” model testing the effect of “grumpiness”.</li>
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