Finding the right power balance: Better study design and collaboration can reduce dependence on statistical power

Shinichi Nakagawa, Malgorzata Lagisz, Yefeng Yang and Szymon M Drobniak

PLOS Biology, 2024, vol. 22, issue 1, 1-17

Abstract: Power analysis currently dominates sample size determination for experiments, particularly in grant and ethics applications. Yet, this focus could paradoxically result in suboptimal study design because publication biases towards studies with the largest effects can lead to the overestimation of effect sizes. In this Essay, we propose a paradigm shift towards better study designs that focus less on statistical power. We also advocate for (pre)registration and obligatory reporting of all results (regardless of statistical significance), better facilitation of team science and multi-institutional collaboration that incorporates heterogenization, and the use of prospective and living meta-analyses to generate generalizable results. Such changes could make science more effective and, potentially, more equitable, helping to cultivate better collaborations.Statistical power analysis currently dominates experimental design. In this Essay, the authors argue that we should move away from the current focus on power analysis and instead encourage smaller scale studies and collaborative projects.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pbio00:3002423

DOI: 10.1371/journal.pbio.3002423

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