Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Многомерное шкалирование (MDS)× | Латентно-классовый анализ (LCA)× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1952–1964 | 1950s–1968 |
| Автор метода≠ | Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964) | Paul F. Lazarsfeld |
| Тип≠ | Dimensionality reduction / visualization | Latent variable / person-centered classification |
| Основополагающий источник≠ | Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27. DOI ↗ | Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231. DOI ↗ |
| Другие названия | MDS, metric MDS, non-metric MDS, proximity scaling | LCA, latent class model, latent categorical analysis, finite mixture of multinomials |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Multidimensional scaling maps objects described only by pairwise similarities or dissimilarities into a low-dimensional geometric space so that distances in that space reflect the original proximity structure as faithfully as possible. It is widely used to visualize the hidden structure of psychological, social, and behavioral data. | Latent class analysis identifies unobserved subgroups — latent classes — within a population by finding patterns of responses across a set of categorical observed indicators. It is the categorical-variable counterpart of cluster analysis, but grounded in an explicit probabilistic model, and is widely used in social, health, and behavioral sciences to discover typologies in survey or diagnostic data. |
| ScholarGateНабор данных ↗ |
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