<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:x="urn:schemas-microsoft-com:office:excel" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><head><meta http-equiv=Content-Type content="text/html; charset=us-ascii"><meta name=Generator content="Microsoft Word 15 (filtered medium)"><style><!--
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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal>Dear Fieldtrippers,<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I have a scenario as depicted below with a oversimplified example.<o:p></o:p></p><p class=MsoNormal>Condition-1 has subjects-A (n=30),B (n=45),C(n=100)and D(n=50)<o:p></o:p></p><p class=MsoNormal>Condition-2 has subjects-X (n=90), Y(n=75) and Z(n=60)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Basically there are two conditions with <o:p></o:p></p><p class=MsoNormal>1. totally different subjects (ABCD in condition-1, XYZ in condition-2)<o:p></o:p></p><p class=MsoNormal>2. different number of subjects (4 in condition-1, 3 in condition-2)<o:p></o:p></p><p class=MsoNormal>3. different number of trials per subject (as indicated by n next to each subject)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I would like to perform cluster based time frequency comparisons between the two conditions.<o:p></o:p></p><p class=MsoNormal>I have come across studies where same subjects are studied over two conditions and have differing trial numbers. But, here I have different subjects in each condition, different number of subjects percondition and different number of trials per subject. <o:p></o:p></p><p class=MsoNormal>Does group comparison of condition-1 vs condition-2 using cluster based permutation analysis based on differing t-statistic hold valid in the above mentioned experimental design? Any input would be of great help.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I was following some advice from a previous thread and paper from Groppe et al. that permutation statistics are insensitive to population variance.<o:p></o:p></p><p class=MsoNormal><a href="http://www.cogsci.ucsd.edu/~dgroppe/PUBLICATIONS/mass_uni_preprint2.pdf">http://www.cogsci.ucsd.edu/~dgroppe/PUBLICATIONS/mass_uni_preprint2.pdf</a><o:p></o:p></p><p class=MsoNormal><a href="https://mailman.science.ru.nl/pipermail/fieldtrip/2015-March/021934.html">https://mailman.science.ru.nl/pipermail/fieldtrip/2015-March/021934.html</a><o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Thank you.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>