<html dir="ltr">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=Windows-1252">
<style>
<!--
@font-face
{font-family:"Cambria Math"}
@font-face
{font-family:Calibri}
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0cm;
margin-bottom:.0001pt;
font-size:11.0pt;
font-family:"Calibri",sans-serif}
a:link, span.MsoHyperlink
{color:#0563C1;
text-decoration:underline}
a:visited, span.MsoHyperlinkFollowed
{color:#954F72;
text-decoration:underline}
span.EmailStyle17
{font-family:"Calibri",sans-serif;
color:windowtext}
.MsoChpDefault
{font-family:"Calibri",sans-serif}
@page WordSection1
{margin:72.0pt 72.0pt 72.0pt 72.0pt}
-->
</style><style type="text/css" id="owaParaStyle"></style>
</head>
<body lang="EN-GB" link="#0563C1" vlink="#954F72" fpstyle="1" ocsi="0">
<div style="direction: ltr;font-family: Helvetica;color: #000000;font-size: 10pt;">
Dear Alex,
<div><br>
</div>
<div>In your case the easiest is to just use depsamplesT. For testing the main effects you can then use the average of the 2 conditions, and for testing the interaction you can use the two difference scores.</div>
<div><br>
</div>
<div>Good luck,</div>
<div>Tineke</div>
<div><br>
</div>
<div><br>
<div style="font-family: Times New Roman; color: #000000; font-size: 16px">
<hr tabindex="-1">
<div id="divRpF577968" style="direction: ltr;"><font face="Tahoma" size="2" color="#000000"><b>From:</b> fieldtrip-bounces@science.ru.nl [fieldtrip-bounces@science.ru.nl] on behalf of Alex Sel [alex.sel@psy.ox.ac.uk]<br>
<b>Sent:</b> Monday, May 16, 2016 8:55 PM<br>
<b>To:</b> fieldtrip@science.ru.nl<br>
<b>Subject:</b> [FieldTrip] depsamplesF<br>
</font><br>
</div>
<div></div>
<div>
<div class="WordSection1">
<p class="MsoNormal">Dear list,</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">I would like to run a non-parametric cluster-based permutation analysis. My experiment has a 2X2 within-subject design, i.e. I would like to compare more than two experimental conditions. I am using the cfg.statistics = ‘depsamplesFmultivariate’.
I wonder if this would be the correct option considering that I only have ONE dependent variable (i.e. ANOVA) and not multiple dependent variables (i.e. MANOVA). If this is not the correct statistic, would you be able to tell me what is the correct statistic
that should be apply to tests differences between more than 2 experimental conditions in a within subject design?</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">Any insight on this would be much appreciated.</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">Best wishes,</p>
<p class="MsoNormal"><span style="">Alex Sel, PhD</span></p>
<p class="MsoNormal"><span style="">Postdoctoral Researcher</span></p>
<p class="MsoNormal"><span style="">Department of Experimental Psychology,</span></p>
<p class="MsoNormal"><span style="">University of Oxford,</span></p>
<p class="MsoNormal"><span style="">9 South Parks Road,</span></p>
<p class="MsoNormal"><span style="">OX1 3UD</span></p>
<p class="MsoNormal"><span style="">Tel: 01865 271 340</span></p>
<p class="MsoNormal"><span style="">Email: Alex.sel@psy.ox.ac.uk</span></p>
<p class="MsoNormal"> </p>
</div>
</div>
</div>
</div>
</div>
</body>
</html>