I have an EEG dataset with participant ids and averaged signal to noise ratios for different different conditions and regions. Can I use a mixed effect model for this dataset (e.g., lmm(SNR ~ condition * ROI (1|subject))? I am trying to understand the benefits of mixed effect models over Repeated measure anovas. Any answer/reading/discussion post will be helpful. Thanks!
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