Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Gareniskā vienumu analīze× | Apstiprinošā faktoru analīze (AFA)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1990s–2000s | 1969 |
| Autors≠ | Vandenberg, Lance, Meade and colleagues in organizational/educational measurement | Karl Gustav Jöreskog |
| Tips≠ | Item-level longitudinal diagnostic | Hypothesis-testing latent variable model |
| Pirmavots≠ | Meade, A. W., Johnson, E. C. & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. Journal of Applied Psychology, 93(3), 568–592. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Citi nosaukumi | LIA, repeated-measures item analysis, longitudinal item calibration, item parameter stability analysis | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Saistītās≠ | 6 | 4 |
| Kopsavilkums≠ | Longitudinal item analysis examines how the statistical properties of individual scale items — difficulty, discrimination, factor loadings, and fit — remain stable or change systematically across repeated measurement occasions. It is the item-level foundation of longitudinal measurement validity. | 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. |
| ScholarGateDatu kopa ↗ |
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