Hi,
This question is about validity of cluster-level inference in random
effects analyses of fMRI data.
In a previous message it was stated that height-based inference should
generally be more powerful than cluster-based inference when degrees of
freedom are low (<16) and smoothness relatively high (>8mm3). In my 2nd
level analysis d.f. was 8 (we plan to add about 3 more subjects) and final
smoothness estimate was 13 13 19. Random effects was chosen given the total
number of images to be processed.
Cluster level inference yielded a number of activations far above the
correction threshold while at voxel-level inference only a single focus
survived the threshold. Interestingly, all activations obtained using
cluster level inference were consistent with our a priori knowledge about
what this task should activate.
I understand there may potentially be theoretical problems using a
cluster-level inference in this context (cfr previous email by G Aguirre
(16 june 99)). Do these problems render the cluster-level inference
statistically invalid?
Thank you very much for your help
Rik Vandenberghe, M.D., Ph.D.
Visiting research associate
Cognitive Neurology and Alzheimer's Disease Center
Northwestern University Medical School
320 East Superior Street
Suite 11-461
Chicago, Illinois 60611
phone: (312) 908-8571
fax: (312) 908-8789
http://www.brain.nwu.edu
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