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| Multi-group Content Validity× | Bestätigende Faktorenanalyse (CFA)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1986–2006 | 1969 |
| Urheber≠ | Lynn (1986); extended by Polit & Beck (2006) | Karl Gustav Jöreskog |
| Typ≠ | Validity assessment / expert judgment aggregation | Hypothesis-testing latent variable model |
| Wegweisende Quelle≠ | Polit, D. F. & Beck, C. T. (2006). The content validity index: Are you sure you know what's being reported? Critique and recommendations. Research in Nursing & Health, 29(5), 489–497. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Aliasnamen | multi-group CVI, cross-group content validity, subgroup content validity index, multi-panel content validity | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | Multi-group content validity extends the standard content validity index (CVI) procedure by computing and comparing item- and scale-level validity indices across two or more distinct expert panels or subgroups. It ensures that a scale's items are judged as relevant and representative not only overall but also within each subgroup of interest, supporting cross-group generalizability of the instrument. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
| ScholarGateDatensatz ↗ |
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