Statistically comparing EEG / MEG waveforms through successive significant univariate tests: How bad can it be?
Vitória Piai; Kristoffer Dahlslätt; Eric Maris · 2014 · Psychophysiology
WASTE classifies this as Failed Experiment Report · AI classification, approximate
An experimental approach did not work as intended — learn what to avoid before investing the same effort.
Abstract (excerpt)
Abstract When making statistical comparisons, the temporal dimension of the EEG signal introduces problems. Guthrie and Buchwald (1991) proposed a formally correct statistical approach that deals with these problems: comparing waveforms by…
Excerpt shown for reference under fair use — read the full paper at the publisher.
Hosted by the publisher — may require access.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
The Two-pore channel (TPC) interactome unmasks isoform-specific roles for TPCs in endolysosomal morphology and cell pigmentation
Failed Experiment ReportA Markov-Middleton Model for Bursty Impulsive Noise: Modeling and Receiver Design
Failed Experiment ReportThe Reference of Proper Names: Testing Usage and Intuitions
Failed Experiment ReportAn investigation of self‐efficacy crossover between mentors and protégés within mentoring dyads
Failed Experiment ReportLymphatic endothelial cells are a replicative niche for Mycobacterium tuberculosis
Failed Experiment ReportNeoadjuvant chemotherapy and Avelumab in early stage resectable nonsmall cell lung cancer
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: Crossref · DOI 10.1111/psyp.12335