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Bayesian evaluation of inequality-constrained hypotheses in SEM Models using Mplus

dc.contributor.authorVan de Schoot, Rens
dc.contributor.authorHoijtink, Herbert
dc.contributor.authorHallquist, Machael N.
dc.contributor.authorBoelen, Paul A.
dc.contributor.researchID25959565 - Van de Schoot, Adrianus Gerardus Joanes
dc.date.accessioned2015-03-19T09:30:12Z
dc.date.available2015-03-19T09:30:12Z
dc.date.issued2012
dc.description.abstractResearchers in the behavioral and social sciences often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model resulting in an informative hypothesis. The questions they would like an answer to are "Is the hypothesis Correct" or "Is the hypothesis incorrect?" We demonstrate a Bayesian approach to compare an inequality-constrained hypothesis with its complement in an SEM framework. The method is introduced and its utility is illustrated by means of an example. Furthermore, the influence of the specification of the prior distribution is examined. Finally, it is shown how the approach proposed can be implemented using Mplus.en_US
dc.description.urihttp://dx.doi.org/10.1080/10705511.2012.713267
dc.description.urihttp://www.tandfonline.com/doi/full/10.1080/10705511.2012.713267#abstract
dc.identifier.citationVan de Schoor, R. & Hoijtink, H., et al. 2012.Bayesian evaluation of inequality-constrained hypotheses in SEM Models using Mplus. Structural Equation Modeling–a Multidisciplinary Journal, 19:593-609. [http://www.tandfonline.com/toc/hsem20/current#.VQqCgeG2qJU]en_US
dc.identifier.issn1070-5511
dc.identifier.issn1532-8007
dc.identifier.urihttp://hdl.handle.net/10394/13590
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectBayes factoren_US
dc.subjectInformative hypothesisen_US
dc.subjectMplusen_US
dc.subjectOrder restricted inferenceen_US
dc.subjectStructural equation modelingen_US
dc.titleBayesian evaluation of inequality-constrained hypotheses in SEM Models using Mplusen_US
dc.typeArticleen_US

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