Better statistical reporting does not lead to statistical rigour: lessons from two decades of pseudoreplication in mouse-model studies of neurological disorders

These observations identify an urgent need for better standards in experimental design and increased vigilance for this type of error during peer review. While reporting standards have significantly improved over the past two decades, this alone has not been enough to curb the prevalence of pseudoreplication. We offer suggestions for how this can be remedied as well as quantifying the severity of this particular type of statistical error. Although the examined literature concerns a specific neuroscience-related area of research, the implications of pseudoreplication apply to all fields of empirical research.

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Publication Details

Journal
Molecular Autism
Published
2025-05-25
DOI
https://doi.org/10.1186/s13229-025-00663-3
Citations
1
Primary Topic
Meta-analysis and systematic reviews
Type
article
Field-Weighted Citation Impact
1.40

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article

Better statistical reporting does not lead to statistical rigour: lessons from two decades of pseudoreplication in mouse-model studies of neurological disorders

Emma Wilson, Peter C. Kind, Na Won Kim, Manuela Rizzi et al.
1 citations
Molecular Autism
Meta-analysis and systematic reviews
1.40
article

Better statistical reporting does not lead to statistical rigour: lessons from two decades of pseudoreplication in mouse-model studies of neurological disorders

Emma Wilson, Peter C. Kind, Na Won Kim, Manuela Rizzi, Lasani S. Wijetunge, Adam D. Jackson, Catherine M. Abbott, Antti Aaltonen, Antonis Asiminas, Sally M. Till, Eleni Tsoukala, Saurav Basu, Jingjing Ye, Sam A. Booker, Anjanette Harris, Karolina Mazur, Timothy O’Leary, Natasha Anstey, David J. A. Wyllie, Aoife McMahon, John C. Pierce, Nina G Petrović, Vanesa Salazar-Sanchez, C. M. Henley, Hugh Woods, C. C. Erdem, Constantinos Eleftheriou, Beatriz Maio, Lucia Landa-Navarro, Sarah Bendova, Sarah Giachetti, Sam Heyes, Raven Hickson, Alex Crocker-Buque, Laura Kamnioti-Dumont, Robert Templaar, Lysandra Fryer-Petridis
article en
1 citations

Abstract

These observations identify an urgent need for better standards in experimental design and increased vigilance for this type of error during peer review. While reporting standards have significantly improved over the past two decades, this alone has not been enough to curb the prevalence of pseudoreplication. We offer suggestions for how this can be remedied as well as quantifying the severity of this particular type of statistical error. Although the examined literature concerns a specific neuroscience-related area of research, the implications of pseudoreplication apply to all fields of empirical research.

Molecular AutismVol. 16(1)
University of Copenhagen (DK), European Bioinformatics Institute (GB), University of Cambridge (GB), Karolinska Institutet (SE), The Queen's Medical Research Institute (GB), University of Edinburgh (GB)
University of Edinburgh, Simons Initiative for the Developing Brain
Openalex Percentile: Top 16%
Meta-analysis and systematic reviews
1.40
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