Bowman, H;
Brooks, JL;
Hajilou, O;
Zoumpoulaki, A;
Litvak, V;
(2020)
Breaking the circularity in circular analyses: Simulations and formal treatment of the flattened average approach.
PLOS Computational Biology
, 16
(11)
, Article e1008286. 10.1371/journal.pcbi.1008286.
(In press).
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Abstract
There has been considerable debate and concern as to whether there is a replication crisis in the scientific literature. A likely cause of poor replication is the multiple comparisons problem. An important way in which this problem can manifest in the M/EEG context is through post hoc tailoring of analysis windows (a.k.a. regions-of-interest, ROIs) to landmarks in the collected data. Post hoc tailoring of ROIs is used because it allows researchers to adapt to inter-experiment variability and discover novel differences that fall outside of windows defined by prior precedent, thereby reducing Type II errors. However, this approach can dramatically inflate Type I error rates. One way to avoid this problem is to tailor windows according to a contrast that is orthogonal (strictly parametrically orthogonal) to the contrast being tested. A key approach of this kind is to identify windows on a fully flattened average. On the basis of simulations, this approach has been argued to be safe for post hoc tailoring of analysis windows under many conditions. Here, we present further simulations and mathematical proofs to show exactly why the Fully Flattened Average approach is unbiased, providing a formal grounding to the approach, clarifying the limits of its applicability and resolving published misconceptions about the method. We also provide a statistical power analysis, which shows that, in specific contexts, the fully flattened average approach provides higher statistical power than Fieldtrip cluster inference. This suggests that the Fully Flattened Average approach will enable researchers to identify more effects from their data without incurring an inflation of the false positive rate.
| Type: | Article |
|---|---|
| Title: | Breaking the circularity in circular analyses: Simulations and formal treatment of the flattened average approach |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1371/journal.pcbi.1008286 |
| Publisher version: | https://doi.org/10.1371/journal.pcbi.1008286 |
| Language: | English |
| Additional information: | Copyright © 2020 Bowman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| Keywords: | Simulation and modeling, Research errors, Power grids, Statistical data, Electroencephalography, Experimental design, Scalp, Event-related potentials |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10116655 |
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