Snijders, T.M. (Tineke)
tineke.snijders at donders.ru.nl
Mon May 16 22:26:57 CEST 2016
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.
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Alex Sel [alex.sel at psy.ox.ac.uk]
Sent: Monday, May 16, 2016 8:55 PM
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] depsamplesF
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?
Any insight on this would be much appreciated.
Alex Sel, PhD
Department of Experimental Psychology,
University of Oxford,
9 South Parks Road,
Tel: 01865 271 340
Email: Alex.sel at psy.ox.ac.uk
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