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dc.contributor.authorKern, Christoph
dc.contributor.authorStein, Petra
dc.date.accessioned2017-01-24T08:40:03Z
dc.date.available2017-01-24T08:40:03Z
dc.date.issued2016
dc.identifier.urihttp://www.ssoar.info/ssoar/handle/document/50108
dc.description.abstractThis study discusses difficulties of effect comparisons in multilevel structural equation models with non-metric outcomes, such as nonlinear dyadic mixed-effects regression. In these models, the fixation of the level-1 error variances induces substantial drawbacks in the context of effect comparisons which align with the well-known problems of standard single- and multilevel nonlinear models. Specifically, the level-1 and level-2 coefficients as well as the level-2 variance components are implicitly rescaled by the amount of unobserved level-1 residual variation and thus may apparently differ across (and within) equations despite of true effect equality. Against this background, the present study discusses a multilevel extension of the method proposed by Sobel and Arminger (1992) with which potential differences in level-1 residual variation can be taken into account through the specification of non-linear parameter constraints. The problems of effect comparisons in multilevel probit SEM's and the proposed correction method are exemplified with a simulation study.en
dc.languageen
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.othermultilevel probit SEM; effect comparison; non-linear constraints; structural equation model
dc.titleEffect Comparison in Multilevel Structural Equation Models with Non-Metric Outcomes
dc.description.reviewbegutachtetde
dc.description.reviewrevieweden
dc.source.collectionJSM 2016 Proceedings, Social Statistics Section
dc.publisher.countryUSA
dc.publisher.cityAlexandria, VA
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozstatistical analysisen
dc.subject.thesozsimulationen
dc.subject.thesozstatistische Analysede
dc.subject.thesozstatistische Methodede
dc.subject.thesozstatistical methoden
dc.subject.thesozSimulationde
dc.subject.thesozMehrebenenanalysede
dc.subject.thesozempirical social researchen
dc.subject.thesozmulti-level analysisen
dc.subject.thesozmultivariate Analysede
dc.subject.thesozModellvergleichde
dc.subject.thesozmodel comparisonen
dc.subject.thesozmultivariate analysisen
dc.subject.thesozempirische Sozialforschungde
dc.identifier.urnurn:nbn:de:0168-ssoar-50108-5
dc.rights.licenceDeposit Licence - Keine Weiterverbreitung, keine Bearbeitungde
dc.rights.licenceDeposit Licence - No Redistribution, No Modificationsen
ssoar.contributor.institutionUniversität Duisburg-Essen
internal.statusnoch nicht fertig erschlossen
internal.identifier.thesoz10035472
internal.identifier.thesoz10035497
internal.identifier.thesoz10049678
internal.identifier.thesoz10052601
internal.identifier.thesoz10037865
internal.identifier.thesoz10052184
internal.identifier.thesoz10042035
dc.type.stockincollection
dc.type.documentSammelwerksbeitragde
dc.type.documentcollection articleen
dc.source.pageinfo3892-3901
internal.identifier.classoz10105
internal.identifier.document25
dc.contributor.corporateeditorAmerican Statistical Association
internal.identifier.ddc300
dc.description.pubstatusPublished Versionen
dc.description.pubstatusVeröffentlichungsversionde
internal.identifier.licence3
internal.identifier.pubstatus1
internal.identifier.review2
dc.subject.classhort10100
internal.pdf.version1.5
internal.pdf.validtrue
internal.pdf.wellformedtrue
internal.check.abstractlanguageharmonizerCERTAIN
internal.check.languageharmonizerCERTAIN_CHANGED


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