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  • Testing for invariance of measurements across groups (such as countries o r time points) is essential before meaningful comparisons may be conducted. However, when tested, invariance is often absent. As a result, comparisons across groups are potentially problematic and may be biased. In the current study, we propose utilizing a multilevel structural equation modeling (SEM) approach to provide a framework to explain item bias. We show how variation in a contextual variable may explain non invariance. For the illustration of the method, we use data from the second round of the European Social Survey (ESS). (author's abstract) (xsd:string)
?:contributor
?:dateModified
  • 2012 (xsd:gyear)
?:datePublished
  • 2012 (xsd:gyear)
?:doi
  • 10.1177/0022022112438397 ()
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  • true (xsd:boolean)
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  • en (xsd:string)
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?:issn
  • 0022-0221 ()
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  • 4 (xsd:string)
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?:name
  • Using a multilevel structural equation modeling approach to explain cross-cultural measurement noninvariance (xsd:string)
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?:publicationType
  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
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?:sourceInfo
  • GESIS-SSOAR (xsd:string)
  • In: Journal of Cross-Cultural Psychology, 43, 2012, 4, 558-575 (xsd:string)
rdf:type
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?:urn
  • urn:nbn:de:0168-ssoar-444854 ()
?:volumeNumber
  • 43 (xsd:string)