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Multidimensional Measurement Invariance in an International Context

Fit Measure Performance With Many Groups

Bibliographic Data

ID7842869
AuthorsDubravka Svetina (0000-0003-3286-3540, Indiana University Bloomington, IN, USA, corresponding author), Leslie Rutkowski (0000-0003-2868-2202, University of Oslo)
Year2017
Volume48
Issue7
Pages991-1008
Publication date2017-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Cross-Cultural Psychology (JOURNAL)
Journal identifiersISSN: 0022-0221 • E-ISSN: 1552-5422
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/0022022117717028
OpenAlexW2728114399
LanguageEN
Citations received15
References cited32

Growing interest in measurement invariance (MI)/equivalence for nonachievement measures across heterogeneous populations in an international context also demands an examination of current criteria for establishing scale score comparability. Namely, in international large-scale assessments (ILSAs) operationally, establishing MI using multiple-groups analyses typically relies on the criteria proposed by research that was limited in scope to few groups and relatively small sample sizes. Recent studies that examined situations resembling those of ILSAs found mixed results with respect to the evaluation criteria for testing MI. The current article extended this line of research by first illustrating the current practices in applied research using empirical examples, and second, by evaluating the performance of several fit measures in two simulation studies when the data were assumed to be ordered categorical and multidimensional in nature. Our simulation study results suggested that in some cases, typical or newly proposed recommendations were not suitable in large-group, varied sample size, multidimensional contexts. Thus, we call for a new measure that more appropriately accounts for complex data characteristics on assessments such as ILSAs

Categorical variable · Comparability · Confirmatory factor analysis · Context (archaeology · Data mining · Econometrics · Equivalence (formal languages · Geography · Level of measurement · Measure (data warehouse · Measurement invariance · Sample (material · Sample size determination · Scale (ratio · Scope (computer science · Statistics · Structural equation modeling · Advanced Causal Inference Techniques · Computer Science · Mathematics · Psychometric Methodologies and Testing · Reliability and Agreement in Measurement

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Unique citing works15
Citations per year2,14
Citation span2019 - 2026 (8)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 15

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