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Hi, I am wondering if it might be possible to use a three level mixed-effects GLM to analyse my single-subject repeated-measure fMRI data which looks like this: First-level: - blockdesign (106 scans) - three conditions repeated three times each + 7 confounds (incl. headmovement estimates) Second-level: - the measurement was repeated twice resulting in three sessions - a covariate of no interest at this level could be "adaption" (1 0 -1) Third-level: - the three sessions were repeated six times seperated by a week each - after the first week we introduced a treatment which stopped right before the fifth week - a covariate of no interest at this level could be again "adaption" (5 3 1 -1 -3 -5) - I want to test for positive or negative BOLD responses which change with treatment, i.e. either look at differences between all of the weeks or use a covariate which resembles our hypothesis: 1-1-2-3-4-2 Does this make sense while all data is coming from a single subject? How do I calculate the effective degrees of freedom (which are hopefully not 6 weeks minus 2 covariates = 4 as in "random effects" analysis)? Unfortunately, the control condition turned out to change with treatment too, therefore I am not able to use the contrast "(A or B) > C" at the first-level, but only "(A or B) > 0" or "(A or B) < 0". Apart from introducing the problem of intra-subject variability of activation (which would have been controlled by the control condition), does this complicate anything? I would be grateful for any advice. All the best, Thomas ------------------------------- Thomas Mierdorf, Dipl. Psych. Institute of Experimental Psychology Heinrich-Heine-University, D-40225 Duesseldorf, Germany voice: ++492118112010; fax: ++492118114522 email: [log in to unmask]