Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Многоуровневый конфирматорный факторный анализ (MCFA)× | Латентно-профильный анализ (LPA)× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1994 | 2010 |
| Автор метода≠ | Bengt O. Muthen | Lazarsfeld & Henry; Collins & Lanza |
| Тип≠ | Latent variable model / measurement model | Person-centered finite mixture model |
| Основополагающий источник≠ | Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗ | Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis. Wiley. ISBN: 978-0-470-22839-7 |
| Другие названия | MCFA, multilevel measurement model, two-level CFA, hierarchical CFA | Continuous Latent Class Analysis, Gaussian Profile Mixture Model, Person-Centered Cluster Analysis, Gizil Profil Analizi |
| Связанные≠ | 6 | 2 |
| Сводка≠ | Multilevel confirmatory factor analysis tests a pre-specified factor structure while simultaneously accounting for the non-independence of observations caused by clustered data. It decomposes item variance into within-group and between-group components, fitting a separate measurement model at each level, making it the standard tool for validating psychometric scales administered within natural groups such as classrooms, clinics, or organisations. | Latent Profile Analysis (LPA) is a person-centered finite mixture modeling technique that identifies unobserved subgroups — called profiles — within a population based on patterns of scores across multiple continuous indicators. Rooted in Lazarsfeld and Henry's latent structure tradition and formally synthesized for applied behavioral research by Collins and Lanza (2010), LPA assumes that observed heterogeneity in continuous data arises from a discrete number of latent classes, each characterized by a unique multivariate mean profile. |
| ScholarGateНабор данных ↗ |
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