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dc.contributor.authorRönkkö, Mikko
dc.contributor.authorAguirre-Urreta, Miguel
dc.date.accessioned2020-05-12T05:26:59Z
dc.date.available2020-05-12T05:26:59Z
dc.date.issued2020
dc.identifier.citationRönkkö, M., & Aguirre-Urreta, M. (2020). Cautionary note on the two-step transformation to normality. <i>Journal of Information Systems</i>, <i>34</i>(1), 151-166. <a href="https://doi.org/10.2308/isys-52255" target="_blank">https://doi.org/10.2308/isys-52255</a>
dc.identifier.otherCONVID_28266508
dc.identifier.otherTUTKAID_78856
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/68924
dc.description.abstractTempleton and Burney (2017) proposed a two-step normality transformation as a remedy for non-normally distributed data, which are commonly found in AIS research. We argue that, rather than transforming the data toward normality, researchers should first seek to analyze and understand the sources of non-normality. Using simulated datasets, we demonstrate three sources of non-normality and their consequences for regression estimation. We then demonstrate that the two-step transformation cannot solve any of these problems and that each source of non-normality can be handled with alternative, existing techniques. We further present two empirical examples to demonstrate these issues with real datasets.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherAmerican Accounting Association
dc.relation.ispartofseriesJournal of Information Systems
dc.rightsIn Copyright
dc.subject.othertwo-step transformation
dc.titleCautionary note on the two-step transformation to normality
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202005113126
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietojärjestelmätiedefi
dc.contributor.oppiaineInformation Systems Scienceen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2020-05-11T09:15:06Z
dc.description.reviewstatuspeerReviewed
dc.format.pagerange151-166
dc.relation.issn0888-7985
dc.relation.numberinseries1
dc.relation.volume34
dc.type.versionacceptedVersion
dc.rights.copyright© American Accounting Association, 2020
dc.rights.accesslevelopenAccessfi
dc.subject.ysonormaalijakauma
dc.subject.ysoregressioanalyysi
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p9478
jyx.subject.urihttp://www.yso.fi/onto/yso/p2130
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.2308/isys-52255


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