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Sample Size Justifications and Open Science Practices in Human Factors (2020–2024)
Journal article

Sample Size Justifications and Open Science Practices in Human Factors (2020–2024)

Jannah R. Moussaoui, Jackson Marra-Dotts, Bochen Li, Samuel Groetsch, Kieran A. Lichter, Andrew Do, Alina Hyk, Sarah Baker, Jeremy Johnson, Briana Hoxha, …
Proceedings of the Human Factors and Ergonomics Society Annual Meeting, v 69(1), pp 1913-1918
Sep 2025

Abstract

Low rates of replicability in behavioral and cognitive sciences have prompted large-scale efforts to increase transparency and openness in reporting. Such practices directly impact researchers’ ability to evaluate studies, replicate procedures, and reproduce empirical findings. This study evaluated the prevalence of research transparency practices (e.g., disclosure of sample size determination, preregistration) and research openness (e.g., share of data, code, and stimuli) across all articles published in Human Factors over the years 2020 to 2024. Most articles made no mention of transparency and openness practices. Future initiatives to improve transparency and openness in Human Factors (e.g., adopting formal policies at the journal level) may be worthwhile.

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