Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Ordinārais Raša modelis (vērtēšanas skalas un daļējā kredīta modeļi)× | Apstiprinošā faktoru analīze (AFA)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1978–1982 | 1969 |
| Autors≠ | David Andrich (RSM, 1978); Geoff Masters (PCM, 1982) | Karl Gustav Jöreskog |
| Tips≠ | Item response model for ordered categories | Hypothesis-testing latent variable model |
| Pirmavots≠ | Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43(4), 561–573. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Citi nosaukumi | Rating Scale Model, Partial Credit Model, RSM, PCM | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Saistītās≠ | 6 | 4 |
| Kopsavilkums≠ | The ordinal Rasch model extends the dichotomous Rasch framework to items with ordered response categories such as Likert-type scales. It places both persons and items on a shared interval-level metric, enabling principled measurement from ordinal data while checking whether items function consistently across all response thresholds. | 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. |
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