Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель латентных кривых роста (LGC)× | Эксплораторный факторный анализ (ЭФА)× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1990 | — |
| Автор метода≠ | Meredith & Tisak | — |
| Тип≠ | Latent variable / longitudinal growth model | Latent variable / dimension reduction |
| Основополагающий источник≠ | Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122. DOI ↗ | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ |
| Другие названия≠ | latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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. | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. |
| ScholarGateНабор данных ↗ |
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