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| Multilevel Differential Item Functioning (Multilevel DIF)× | Mehrstufige konfirmatorische Faktorenanalyse (MCFA)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 2001 | 1994 |
| Urheber≠ | Kamata (2001) and subsequent multilevel IRT/DIF literature | Bengt O. Muthen |
| Typ≠ | Bias detection / multilevel measurement model | Latent variable model / measurement model |
| Wegweisende Quelle≠ | French, B. F., & Finch, W. H. (2008). Multigroup confirmatory factor analysis: Locating the invariant referent sets. Structural Equation Modeling: A Multidisciplinary Journal, 15(1), 96–113. DOI ↗ | Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗ |
| Aliasnamen | multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF | MCFA, multilevel measurement model, two-level CFA, hierarchical CFA |
| Verwandt≠ | 5 | 6 |
| Zusammenfassung≠ | Multilevel DIF analysis detects whether individual test or survey items function differently across groups when respondents are clustered within higher-level units — such as students nested in schools, employees in organizations, or patients in clinics. By accounting for hierarchical data structure, it separates genuine item bias from artificial DIF signals caused by ignoring clustering. | Multilevel confirmatory factor analysis tests a pre-specified factor structure while simultaneously accounting for the non-independence of observations caused by clustered data. It decomposes item variance into within-group and between-group components, fitting a separate measurement model at each level, making it the standard tool for validating psychometric scales administered within natural groups such as classrooms, clinics, or organisations. |
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