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dc.contributor.authorAguirre-Urreta, Miguel I.
dc.contributor.authorRönkkö, Mikko
dc.contributor.authorHu, Jiang
dc.date.accessioned2020-12-30T08:40:45Z
dc.date.available2020-12-30T08:40:45Z
dc.date.issued2020
dc.identifier.citationAguirre-Urreta, M. I., Rönkkö, M., & Hu, J. (2020). Polynomial Regression and Measurement Error : Implications for Information Systems Research. <i>Data Base for Advances in Information Systems</i>, <i>51</i>(3), 55-80. <a href="https://doi.org/10.1145/3410977.3410981" target="_blank">https://doi.org/10.1145/3410977.3410981</a>
dc.identifier.otherCONVID_41625638
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/73511
dc.description.abstractMany of the phenomena of interest in information systems (IS) research are nonlinear, and it has consequently been recognized that by applying linear statistical models (e.g., linear regression), we may ignore important aspects of these phenomena. To address this issue, IS researchers are increasingly applying nonlinear models to their datasets. One popular analytical technique for the modeling and analysis of nonlinear relationships is polynomial regression, which in its simplest form fits a "U-shaped" curve to the data. However, the use of polynomial regression can be problematic when the independent variables are contaminated with measurement error, and the implications of error can be more severe than in linear models. In this research, we discuss a number of techniques that can be used for modeling polynomial relationships while simultaneously taking measurement error into account and examine their performance by using a simulation study. In addition, we discuss the use of marginal and response surface plots as interpretational aides when evaluating the results of polynomial models and showcase their use through a practical example using a well-known dataset. Our results clearly indicate that the use of a linear regression analysis for this kind of model is problematic, and we provide a set of recommendations for future IS research practice.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherAssociation for Computing Machinery (ACM)
dc.relation.ispartofseriesData Base for Advances in Information Systems
dc.rightsIn Copyright
dc.subject.otherepälineaariset mallit
dc.subject.otherpiilevät muuttujat
dc.subject.otherpolynomial regression
dc.subject.othermeasurement
dc.subject.othererror
dc.subject.otherattenuation
dc.subject.othernonlinear SEM
dc.subject.otherlatent variables
dc.titlePolynomial Regression and Measurement Error : Implications for Information Systems Research
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202012307439
dc.contributor.laitosKauppakorkeakoulufi
dc.contributor.laitosSchool of Business and Economicsen
dc.contributor.oppiaineStrategia ja yrittäjyysfi
dc.contributor.oppiaineBasic or discovery scholarshipfi
dc.contributor.oppiaineStrategy and Entrepreneurshipen
dc.contributor.oppiaineBasic or discovery scholarshipen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.description.reviewstatuspeerReviewed
dc.format.pagerange55-80
dc.relation.issn1532-0936
dc.relation.numberinseries3
dc.relation.volume51
dc.type.versionacceptedVersion
dc.rights.copyright© Association for Computing Machinery (ACM), 2020
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber311309
dc.subject.ysomittaus
dc.subject.ysomittausvirheet
dc.subject.ysotietojärjestelmät
dc.subject.ysomuuttujat
dc.subject.ysolineaariset mallit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p4794
jyx.subject.urihttp://www.yso.fi/onto/yso/p22424
jyx.subject.urihttp://www.yso.fi/onto/yso/p3927
jyx.subject.urihttp://www.yso.fi/onto/yso/p16708
jyx.subject.urihttp://www.yso.fi/onto/yso/p25748
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1145/3410977.3410981
dc.relation.funderSuomen Akatemiafi
dc.relation.funderAcademy of Finlanden
jyx.fundingprogramTutkijatohtori, SAfi
jyx.fundingprogramPostdoctoral Researcher, AoFen
jyx.fundinginformationThe work by Mikko Rönkkö was supported by a grant from the Academy of Finland (grant 311309).


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