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Hi Karina, Adding the main effects and interactions in the flexible factorial module only adds these effects to the design matrix, it doesn't create the contrasts for those effects. I'll discuss creating the contrasts separately below, but in terms of your design being a 2 x 2 fully within-subject, you will need multiple models to calculate the F-statistics using the correct error term. For instance, your effects are: Main effect of time: needs a model containing Time and Subject after averaging over Self Main effect of self: needs a model containing Self and Subject after averaging over Time Time x Self: needs a model containing Time, Self, Time x Self, Subject, Time x Subject and Self x Subject The contrasts are another matter because of the necessity of creating estimable functions of the parameters in overparameterised designs. In unbalanced designs this is particularly tricky given that most people are after the standard Type III sums-of-squares. Because this is such a common issue on the list, I have actually written a paper going over the how and the why of both of these issues, with an example in SPM. I submitted it to NeuroImage, but the reviewers came back stating that none of it was new and no one would find it useful. Not that I'm bitter, but it'd be nice to actually know that some people would find it useful! I'm planning to put it up as a preprint on arXiv, but I'll send you the current draft separately. I hope it will help answer your questions and help you understand what you need to do. Best wishes Martyn ------------------------------------------------- Martyn McFarquhar, PhD Lecturer in Neuroimaging G30 Zochonis Building The University of Manchester Brunswick Street Manchester M13 9GB +44 (0)161 306 0450 -------------------------------------------------