Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Latent Growth Curve Model (LGC)× | ANOVA ar atkārtotiem mērījumiem× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime≠ | Latent structure | Hypothesis test |
| Izcelsmes gads≠ | 1990 | 1992 |
| Autors≠ | Meredith & Tisak | Girden (textbook treatment); Field (2013) |
| Tips≠ | Latent variable / longitudinal growth model | Parametric within-subjects mean comparison |
| Pirmavots≠ | Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122. DOI ↗ | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 |
| Citi nosaukumi | latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA |
| 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. | Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013). |
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