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Dear Karl and/or others, Now that we're on the subject, how much smaller would the minimum recommended n be in PET for doing a random effects analysis in order to compare across groups or generalize to the population at large? Thanks for your help, Leann Kinnunen University of Chicago Department of Psychology ---------- Forwarded message ---------- Date: Tue, 20 Mar 2001 14:13:41 GMT From: Karl Friston <[log in to unmask]> To: [log in to unmask] Subject: Re: group x task interactions in clinical fMRI Dear Eraldo, > When using fMRI for clinical purposes (eg; mapping hemispheric > dominance for language function) one needs to compare the activations > in a patient with the activations in a group of controls to test the > reliability of any apparent difference in the patient > > This can be done as group x task interaction effect (one group has > only one subject, the patient) > > My understanding is that fixed effects models would not be good here > and a random effect analysis is needed I think the usual qualifications apply here. If you want to infer that the patient activates abnormally in relation to a specific group of control subjects than a fixed-effects analysis is appropriate. If you want to say that the abnormality is in relation to the population from which the normals were selected, then a random-effects analysis is called for. Both are valid. The special caveat here is that the fixed effects analysis may be more sensitive, which has implications in a clinical setting. The key question here is which has the greatest predictive validity about intervention outcomes. > My understanding is also that a random effect analysis would come at > the cost of the residual degrees of freedom with an issue on the > magnitude of the controls sample size to achieve a sufficiently > sensitive analysis > Is there any estimate on how big should be the size of the control group? Indeed - I would recommend at least 16 for a random effects analysis and ideally 32. With very best wishes, Karl