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| Group-Based Trajectory Model× | Анализ на латентните класове (LCA)× | |
|---|---|---|
| Област≠ | Criminology | Статистика |
| Семейство≠ | Regression model | Latent structure |
| Година на възникване≠ | 1993 | 1950s–1968 |
| Създател≠ | Daniel S. Nagin & Kenneth C. Land | Paul F. Lazarsfeld |
| Тип≠ | Finite-mixture model of longitudinal developmental trajectories | Latent variable / person-centered classification |
| Основополагащ източник≠ | Nagin, D. S., & Land, K. C. (1993). Age, criminal careers, and population heterogeneity: Specification and estimation of a nonparametric, mixed Poisson model. Criminology, 31(3), 327–362. DOI ↗ | Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231. DOI ↗ |
| Други названия≠ | GBTM, Group-Based Modeling of Development, Nagin Trajectory Model, Semiparametric Group-Based Modeling | LCA, latent class model, latent categorical analysis, finite mixture of multinomials |
| Свързани≠ | 4 | 6 |
| Резюме≠ | Group-based trajectory modeling (GBTM) is a finite-mixture method that identifies clusters of individuals who follow similar developmental paths of a behavior — most famously offending — over age or time. Introduced to criminology by Daniel Nagin and Kenneth Land in 1993, it replaces the assumption of a single average trajectory with a small number of distinct latent groups, each described by its own polynomial curve and its share of the population. | 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 от данни ↗ |
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