Journal article

Publication year: 2018

Journal: Frontiers in Human Neuroscience

Volume number: 12

ISSN: 1662-5161

Open access status: Gold

DOI Link: https://doi.org/10.3389/fnhum.2018.00421

Publisher: Frontiers Media

Abstract: 
Neuroscience has been diagnosed with a pervasive lack of statistical power and, in turn, reliability. One remedy proposed is a massive increase of typical sample sizes. Parts of the neuroimaging community have embraced this recommendation and actively push for a reallocation of resources toward fewer but larger studies. This is especially true for neuroimaging studies focusing on individual differences to test brain-behavior correlations. Here, I argue for a more efficient solution. Ad hoc simulations show that statistical power crucially depends on the choice of behavioral and neural measures, as well as on sampling strategy. Specifically, behavioral prescreening and the selection of extreme groups can ascertain a high degree of robust in-sample variance. Due to the low cost of behavioral testing compared to neuroimaging, this is a more efficient way of increasing power. For example, prescreening can achieve the power boost afforded by an increase of sample sizes from n = 30 to n = 100 at similar to 5% of the cost. This perspective article briefly presents simulations yielding these results, discusses the strengths and limitations of prescreening and addresses some potential counter-arguments. Researchers can use the accompanying online code to simulate the expected power boost of prescreening for their own studies.

Harvard Citation style: de Haas, B. (2018) How to Enhance the Power to Detect Brain–Behavior Correlations With Limited Resources, Frontiers in Human Neuroscience, 12, Article 421. https://doi.org/10.3389/fnhum.2018.00421

APA Citation style: de Haas, B. (2018). How to Enhance the Power to Detect Brain–Behavior Correlations With Limited Resources. Frontiers in Human Neuroscience. 12, Article 421. https://doi.org/10.3389/fnhum.2018.00421