Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Latent Growth Curve Model (LGC)× | Apstiprinošā faktoru analīze (AFA)× | |
|---|---|---|
| Nozare≠ | Statistika | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1990 | 1969 |
| Autors≠ | Meredith & Tisak | Karl Gustav Jöreskog |
| Tips≠ | Latent variable / longitudinal growth model | Hypothesis-testing latent variable model |
| Pirmavots≠ | Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Citi nosaukumi | latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | The latent growth curve model is a structural equation modelling approach introduced by Meredith and Tisak (1990) for analysing change over time. It treats each individual's starting point (intercept) and rate of change (slope) as latent variables, simultaneously estimating the average trajectory across the sample and the extent to which individuals differ in their own trajectories. | 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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