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dc.contributor.authorFagerland, Morten
dc.contributor.authorLydersen, Stian
dc.contributor.authorLaake, Petter
dc.date.accessioned2019-10-24T12:40:18Z
dc.date.available2019-10-24T12:40:18Z
dc.date.created2013-09-24T10:53:18Z
dc.date.issued2013
dc.identifier.citationBMC Medical Research Methodology. 2013, 13 .nb_NO
dc.identifier.issn1471-2288
dc.identifier.urihttp://hdl.handle.net/11250/2624186
dc.description.abstractBackground Statistical methods that use the mid-p approach are useful tools to analyze categorical data, particularly for small and moderate sample sizes. Mid-p tests strike a balance between overly conservative exact methods and asymptotic methods that frequently violate the nominal level. Here, we examine a mid-p version of the McNemar exact conditional test for the analysis of paired binomial proportions. Methods We compare the type I error rates and power of the mid-p test with those of the asymptotic McNemar test (with and without continuity correction), the McNemar exact conditional test, and an exact unconditional test using complete enumeration. We show how the mid-p test can be calculated using eight standard software packages, including Excel. Results The mid-p test performs well compared with the asymptotic, asymptotic with continuity correction, and exact conditional tests, and almost as good as the vastly more complex exact unconditional test. Even though the mid-p test does not guarantee preservation of the significance level, it did not violate the nominal level in any of the 9595 scenarios considered in this article. It was almost as powerful as the asymptotic test. The exact conditional test and the asymptotic test with continuity correction did not perform well for any of the considered scenarios. Conclusions The easy-to-calculate mid-p test is an excellent alternative to the complex exact unconditional test. Both can be recommended for use in any situation. We also recommend the asymptotic test if small but frequent violations of the nominal level is acceptable.nb_NO
dc.language.isoengnb_NO
dc.publisherBMC (part of Springer Nature)nb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleThe McNemar test for binary matched-pairs data: mid-p and asymptotic are better than exact conditionalnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber8nb_NO
dc.source.volume13nb_NO
dc.source.journalBMC Medical Research Methodologynb_NO
dc.identifier.doi10.1186/1471-2288-13-91
dc.identifier.cristin1051620
dc.description.localcode© 2013 Fagerland et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.nb_NO
cristin.unitcode194,65,35,5
cristin.unitnameRKBU Midt-Norge - Regionalt kunnskapssenter for barn og unge - psykisk helse og barnevern
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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