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| Scaling multidimensionale (MDS)× | Analisi delle classi latenti (LCA)× | |
|---|---|---|
| Campo | Statistica | Statistica |
| Famiglia | Latent structure | Latent structure |
| Anno di origine≠ | 1952–1964 | 1950s–1968 |
| Ideatore≠ | Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964) | Paul F. Lazarsfeld |
| Tipo≠ | Dimensionality reduction / visualization | Latent variable / person-centered classification |
| Fonte seminale≠ | 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 ↗ |
| Alias | MDS, metric MDS, non-metric MDS, proximity scaling | LCA, latent class model, latent categorical analysis, finite mixture of multinomials |
| Correlati≠ | 5 | 6 |
| Sintesi≠ | 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. |
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