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dc.contributor.authorPembury Smith, Matilda
dc.contributor.authorRuxton, Graeme D.
dc.date.accessioned2020-10-12T10:30:06Z
dc.date.available2020-10-12T10:30:06Z
dc.date.issued2020-10-10
dc.identifier.citationPembury Smith , M & Ruxton , G D 2020 , ' Effective use of the McNemar test ' , Behavioral Ecology and Sociobiology , vol. 74 , 133 . https://doi.org/10.1007/s00265-020-02916-yen
dc.identifier.issn0340-5443
dc.identifier.otherPURE: 270484608
dc.identifier.otherPURE UUID: 62bf1099-98aa-43db-8b97-88de7158387d
dc.identifier.otherORCID: /0000-0001-8943-6609/work/82179566
dc.identifier.otherWOS: 000576567900001
dc.identifier.otherScopus: 85092380479
dc.identifier.urihttps://hdl.handle.net/10023/20769
dc.description.abstractIt is not uncommon for researchers to want to interrogate paired binomial data. For example, researchers may want to compare an organism’s response (positive or negative) to two different stimuli. If they apply both stimuli to a sample of individuals, it would be natural to present the data in a 2 × 2 table. There would be two cells with concordant results (the frequency of individuals which responded positively or negatively to both stimuli) and two cells with discordant results (the frequency of individuals who responded positively to one stimulus, but negatively to the other). The key issue is whether the totals in the two discordant cells are sufficiently different to suggest that the stimuli trigger different reactions. In terms of the null hypothesis testing paradigm, this would translate as a P value which is the probability of seeing the observed difference in these two values or a more extreme difference if the two stimuli produced an identical reaction. The statistical test designed to provide this P value is the McNemar test. Here, we seek to promote greater and better use of the McNemar test. To achieve this, we fully describe a range of circumstances within biological research where it can be effectively applied, describe the different variants of the test that exist, explain how these variants can be accessed in R, and offer guidance on which of these variants to adopt. To support our arguments, we highlight key recent methodological advances and compare these with a novel survey of current usage of the test.
dc.format.extent9
dc.language.isoeng
dc.relation.ispartofBehavioral Ecology and Sociobiologyen
dc.rightsCopyright © The Author(s) 2020. Open Access. 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. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en
dc.subjectMcNemar testen
dc.subjectBinomial dataen
dc.subjectP valueen
dc.subjectSignificance testingen
dc.subjectMeta-analysisen
dc.subjectQH301 Biologyen
dc.subjectT-DASen
dc.subject.lccQH301en
dc.titleEffective use of the McNemar testen
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.identifier.doihttps://doi.org/10.1007/s00265-020-02916-y
dc.description.statusPeer revieweden


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