方法对比
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| 潜在类别分析 (Latent Class Analysis, LCA)× | 探索性因子分析（EFA）× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1950s–1968 | — |
| 提出者≠ | Paul F. Lazarsfeld | — |
| 类型≠ | Latent variable / person-centered classification | Latent variable / dimension reduction |
| 开创性文献≠ | Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231. 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 ↗ |
| 别名≠ | LCA, latent class model, latent categorical analysis, finite mixture of multinomials | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| 相关≠ | 6 | 4 |
| 摘要≠ | 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. | 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. |
| ScholarGate数据集 ↗ |
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