Improvements to PLSc: Remaining problems and simple solutions

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorRönkkö, Mikko
dc.contributor.authorMcIntosh, Cameron N.fi
dc.contributor.authorAguirre-Urreta, Miguel I.fi
dc.contributor.departmentTuotantotalouden laitosfi
dc.contributor.departmentDepartment of Industrial Engineering and Managementen
dc.contributor.labInstitute of Strategy and Venturingen
dc.contributor.schoolPerustieteiden korkeakoulufi
dc.contributor.schoolSchool of Scienceen
dc.date.accessioned2016-03-21T10:00:59Z
dc.date.available2016-03-21T10:00:59Z
dc.date.issued2016
dc.description.abstractThe recent article by Dijkstra and Henseler (2015b) presents a consistent partial least squares (PLSc) estimator that corrects for measurement error attenuation and provides evidence showing that, generally, PLSc performs comparably to a wide variety of more conventional estimators for structural equation models (SEM) with latent variables. However, PLSc does not adjust for other limitations of conventional PLS, namely: (1) bias in estimates of regression coefficients due to capitalization on chance; and (2) overestimation of composite reliability due to the proportionality relation between factor loadings and indicator weights. In this article, we illustrate these problems and then propose a simple solution: the use of unit-weighted composites, rather than those constructed from PLS results, combined with errors-in-variables regression (EIV) by using reliabilities obtained from factor analysis. Our simulations show that these two improvements perform as well as or better than PLSc. We also provide examples of how our proposed estimator can be easily implemented in various proprietary and open source software packages.en
dc.format.extent102
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRönkkö, Mikko & McIntosh, Cameron N. & Aguirre-Urreta, Miguel I. 2016. Improvements to PLSc: Remaining problems and simple solutions. Unpublished working paper. 102 pages.en
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/19844
dc.identifier.urnURN:NBN:fi:aalto-201603051463
dc.language.isoenen
dc.publisherAalto Universityen
dc.publisherAalto-yliopistofi
dc.subject.keywordpartial least squaresen
dc.subject.keywordstructural equation modelingen
dc.subject.keywordcomposite variablesen
dc.subject.keywordlatent variablesen
dc.subject.keywordmeasurement erroren
dc.subject.keywordreliabilityen
dc.subject.keywordcorrection for attenuationen
dc.subject.keywordcapitalization on chanceen
dc.subject.keyworderrors-in-variables regressionen
dc.subject.otherMathematicsen
dc.titleImprovements to PLSc: Remaining problems and simple solutionsen
dc.typeJ Muu elektroninen julkaisufi
dc.type.dcmitypetexten
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