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Statistical Perspectives on Reproducibility: Definitions and Challenges

Simkus, Andrea; Coolen-Maturi, Tahani; Coolen, Frank P.A.; Bendtsen, Claus

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Authors

Profile image of Andrea Simkus

Andrea Simkus andrea.simkus@durham.ac.uk
PGR Student Doctor of Philosophy

Claus Bendtsen



Abstract

Reproducibility is a widely discussed topic, yet many experimental results cannot be confirmed due to factors such as publication bias, poor documentation, and inappropriate statistical methods. A lack of standard definitions for reproducibility and related terms further complicates the matter. This paper reviews the literature on reproducibility, clarifies key terminology by defining five types of reproducibility, and addresses variations in published definitions by considering changes in datasets, labs, and experimental conditions. We explore the causes of low reproducibility in scientific studies and discuss statistical perspectives on quantifying and improving reproducibility. In particular, we propose framing statistical reproducibility as a predictive problem, providing a framework to evaluate and address reproducibility challenges.

Citation

Simkus, A., Coolen-Maturi, T., Coolen, F. P., & Bendtsen, C. (2025). Statistical Perspectives on Reproducibility: Definitions and Challenges. Journal of statistical theory and practice, 19(3), Article 40. https://doi.org/10.1007/s42519-025-00459-x

Journal Article Type Article
Acceptance Date May 14, 2025
Online Publication Date May 27, 2025
Publication Date Sep 1, 2025
Deposit Date May 15, 2025
Publicly Available Date Jun 2, 2025
Journal Journal of Statistical Theory and Practice
Electronic ISSN 1559-8616
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 19
Issue 3
Article Number 40
DOI https://doi.org/10.1007/s42519-025-00459-x
Keywords Preclinical research, Replicability, Nonparametric predictive inference, Reproducibility, Statistical reproducibility
Public URL https://durham-repository.worktribe.com/output/3948469

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