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dc.contributor.authorEckhartt, Greg
dc.contributor.authorRuxton, Graeme Douglas
dc.identifier.citationEckhartt , G & Ruxton , G D 2023 , ' Investigating and preventing scientific misconduct using Benford’s Law ' , Research Integrity and Peer Review , vol. 8 , 1 .
dc.identifier.otherPURE: 282630331
dc.identifier.otherPURE UUID: 820e40a1-4401-4172-90d7-baa169371797
dc.identifier.otherORCID: /0000-0001-8943-6609/work/133187355
dc.description.abstractIntegrity and trust in that integrity are fundamental to academic research. However, procedures for monitoring the trustworthiness of research, and for investigating cases where concern about possible data fraud have been raised are not well established. Here we suggest a practical approach for the investigation of work suspected of fraudulent data manipulation using Benford’s Law. This should be of value to both individual peer-reviewers and academic institutions and journals. In this, we draw inspiration from well-established practices of financial auditing. We provide synthesis of the literature on tests of adherence to Benford’s Law, culminating in advice of a single initial test for digits in each position of numerical strings within a dataset. We also recommend further tests which may prove useful in the event that specific hypotheses regarding the nature of data manipulation can be justified. Importantly, our advice differs from the most common current implementations of tests of Benford’s Law. Furthermore, we apply the approach to previously-published data, highlighting the efficacy of these tests in detecting known irregularities. Finally, we discuss the results of these tests, with reference to their strengths and limitations.
dc.relation.ispartofResearch Integrity and Peer Reviewen
dc.rightsCopyright © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.en
dc.subjectBenford’s Law testsen
dc.subjectAnimal behaviouren
dc.subjectScientific misconducten
dc.subjectPeer reviewen
dc.subjectBenford’s Lawen
dc.subjectRetracted article testingen
dc.subjectQ Science (General)en
dc.titleInvestigating and preventing scientific misconduct using Benford’s Lawen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen
dc.contributor.institutionUniversity of St Andrews. Institute of Behavioural and Neural Sciencesen
dc.description.statusPeer revieweden

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