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dc.contributor.authorRönkkö, Mikko
dc.contributor.authorCho, Eunseong
dc.date.accessioned2020-12-30T08:35:20Z
dc.date.available2020-12-30T08:35:20Z
dc.date.issued2022
dc.identifier.citationRönkkö, M., & Cho, E. (2022). An Updated Guideline for Assessing Discriminant Validity. <i>Organizational Research Methods</i>, <i>25</i>(1), 6-14. <a href="https://doi.org/10.1177/1094428120968614" target="_blank">https://doi.org/10.1177/1094428120968614</a>
dc.identifier.otherCONVID_47113610
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/73510
dc.description.abstractDiscriminant validity was originally presented as a set of empirical criteria that can be assessed from multitrait-multimethod (MTMM) matrices. Because datasets used by applied researchers rarely lend themselves to MTMM analysis, the need to assess discriminant validity in empirical research has led to the introduction of numerous techniques, some of which have been introduced in an ad hoc manner and without rigorous methodological support. We review various definitions of and techniques for assessing discriminant validity and provide a generalized definition of discriminant validity based on the correlation between two measures after measurement error has been considered. We then review techniques that have been proposed for discriminant validity assessment, demonstrating some problems and equivalencies of these techniques that have gone unnoticed by prior research. After conducting Monte Carlo simulations that compare the techniques, we present techniques called CICFA(sys) and χ2(sys) that applied researchers can use to assess discriminant validity.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherSAGE Publications
dc.relation.ispartofseriesOrganizational Research Methods
dc.rightsCC BY-NC 4.0
dc.subject.otherdiscriminant validity
dc.subject.otherMonte Carlo simulation
dc.subject.othermeasurement
dc.subject.otherconfirmatory factor analysis
dc.subject.othervalidation
dc.subject.otheraverage variance extracted
dc.subject.otherheterotrait-monotrait ratio
dc.subject.othercross-loadings
dc.titleAn Updated Guideline for Assessing Discriminant Validity
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202012307438
dc.contributor.laitosKauppakorkeakoulufi
dc.contributor.laitosSchool of Business and Economicsen
dc.contributor.oppiaineBasic or discovery scholarshipfi
dc.contributor.oppiaineStrategia ja yrittäjyysfi
dc.contributor.oppiaineBasic or discovery scholarshipen
dc.contributor.oppiaineStrategy and Entrepreneurshipen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange6-14
dc.relation.issn1094-4281
dc.relation.numberinseries1
dc.relation.volume25
dc.type.versionpublishedVersion
dc.rights.copyright© The Author(s) 2020
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber311309
dc.subject.ysovalidointi
dc.subject.ysoMonte Carlo -menetelmät
dc.subject.ysokvantitatiivinen tutkimus
dc.subject.ysotilastomenetelmät
dc.subject.ysofaktorianalyysi
dc.subject.ysomittaus
dc.subject.ysoorganisaatiotutkimus
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p20652
jyx.subject.urihttp://www.yso.fi/onto/yso/p6361
jyx.subject.urihttp://www.yso.fi/onto/yso/p18834
jyx.subject.urihttp://www.yso.fi/onto/yso/p3127
jyx.subject.urihttp://www.yso.fi/onto/yso/p6540
jyx.subject.urihttp://www.yso.fi/onto/yso/p4794
jyx.subject.urihttp://www.yso.fi/onto/yso/p7816
dc.rights.urlhttps://creativecommons.org/licenses/by-nc/4.0/
dc.relation.doi10.1177/1094428120968614
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramPostdoctoral Researcher, AoFen
jyx.fundingprogramTutkijatohtori, SAfi
jyx.fundinginformationThis research was supported in part by a grant from the Academy of Finland (Grant 311309) and the Research Grant of Kwangwoon University in 2019.
dc.type.okmA1


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