I’ve got a question about the repeated measures ANOVA cluster test with regards to what kind of repeated measures it supports. My study design is a cross-over study with 4 different conditions, all tested on the same 10 subjects, each with multiple repeated trials (68 after bad epoch rejection and equalizing counts among them).
I understand the basic data structure needed for the test as passing a list of
[condition1array, condition2array, … ], where conditionNarray has shape (samples(subjects), time, space)
However, I’m a little confused about the samples(subjects) dimension. Is it proper to use all the samples from all the subjects (i.e. conditionNarray has shape (10*68, time, space))? Part of me thinks that I could do that and then use an f-threshold of
mne.stats.f_threshold_mway_rm(n_subjects = 10)
But part of me is also a little confused with how the permutations would work, since, as far as I can tell, the permutations do not keep track of which data are originally from which subjects. Does this test support repeated measures across multiple subjects, or just repeated measures across one subject at a time?
I really appreciate any insight you can provide. Thank you!
You would generally average across the 68 trials, so you would have for each subject a total of 4 Evoked objects (one for each condition). Then, condition1array would be created from the 10 Evoked objects belonging to the first condition, condition2array from the 10 Evoked objects belonging to the second condition, and so on.
Dear @Kosnoff ,
I was following this tutorial by @Denis et al. and was wondering along the same line. My goal was to perform a permutation test rmANOVA to check for the effect of a repeated Factor (condition with 3 levels) in X subjects measured in S sampling time points. I seem to have adopted the tutorial code successfully and the output looks plausible. However, I would like to understand how the permutation was conducted. I tried looking into the code of the cluster_permutation_test() function, but I have difficulty understanding it. I would like to understand whether and how this function in the case of rmANOVAs restricts the permutations within subjects.
Do you by any chance know the answer to your question by now? Thanks in advance
