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dc.contributor.authorSchuberth, Florian
dc.contributor.authorRosseel, Yves
dc.contributor.authorRönkkö, Mikko
dc.contributor.authorTrinchera, Laura
dc.contributor.authorKline, Rex B.
dc.contributor.authorHenseler, Jörg
dc.date.accessioned2022-12-13T08:43:44Z
dc.date.available2022-12-13T08:43:44Z
dc.date.issued2023
dc.identifier.citationSchuberth, F., Rosseel, Y., Rönkkö, M., Trinchera, L., Kline, R. B., & Henseler, J. (2023). Structural Parameters under Partial Least Squares and Covariance-Based Structural Equation Modeling : A Comment on Yuan and Deng (2021). <i>Structural Equation Modeling : A Multidisciplinary Journal</i>, <i>30</i>(3), 339-345. <a href="https://doi.org/10.1080/10705511.2022.2134140" target="_blank">https://doi.org/10.1080/10705511.2022.2134140</a>
dc.identifier.otherCONVID_160162249
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/84322
dc.description.abstractIn their article, Yuan and Deng argue that a structural parameter under partial least squares structural equation modeling (PLS-SEM) is zero if and only if the same structural parameter is zero under covariance-based structural equation modeling (CB-SEM). Yuan and Deng then conclude that statistical tests on individual structural parameters assessing the null hypothesis of no effect can achieve the same purpose in CB-SEM and PLS-SEM. Our response to their article highlights that the relationship they find between PLS-SEM and CB-SEM structural parameters is not universally valid, and that consequently, tests on individual parameters in CB-SEM and PLS-SEM generally do not fulfill the same purpose.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherRoutledge
dc.relation.ispartofseriesStructural Equation Modeling : A Multidisciplinary Journal
dc.rightsCC BY 4.0
dc.subject.otherbias correction
dc.subject.otherfactor score regression
dc.subject.othermeasurement error
dc.subject.otherpartial least squares structural equation modeling (PLS-SEM)
dc.titleStructural Parameters under Partial Least Squares and Covariance-Based Structural Equation Modeling : A Comment on Yuan and Deng (2021)
dc.typeresearch article
dc.identifier.urnURN:NBN:fi:jyu-202212135579
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange339-345
dc.relation.issn1070-5511
dc.relation.numberinseries3
dc.relation.volume30
dc.type.versionpublishedVersion
dc.rights.copyright© 2022 The Author(s). Published with license by Taylor & Francis Group, LLC
dc.rights.accesslevelopenAccessfi
dc.type.publicationarticle
dc.subject.ysomittausvirheet
dc.subject.ysorakenneyhtälömallit
dc.subject.ysovirheanalyysi
dc.subject.ysotilastolliset mallit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p22424
jyx.subject.urihttp://www.yso.fi/onto/yso/p28201
jyx.subject.urihttp://www.yso.fi/onto/yso/p9865
jyx.subject.urihttp://www.yso.fi/onto/yso/p26278
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1080/10705511.2022.2134140
jyx.fundinginformationJörg Henseler gratefully acknowledges financial support from FCT Fundação para a Cincia e a Tecnologia (Portugal), national funding through a research grant from the Information Management Research Center—MagIC/NOVA IMS (UIDB/04152/2020).
dc.type.okmA1


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