Regression modelLongitudinal clustering and latent class growth methods
Criminal Trajectory Clustering
Criminal trajectory clustering is the broad family of methods that group individuals by the shape of their longitudinal offending curves. Rather than committing to a single statistical model, it spans algorithmic approaches — k-means for longitudinal data, distance-based clustering of trajectory shapes, and likelihood-based latent class growth — and treats the choice of clustering method itself as a modeling decision validated by fit and stability criteria.
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来源
- Nagin, D. S. (2005). Group-Based Modeling of Development. Harvard University Press. ISBN: 9780674016866
- Genolini, C., & Falissard, B. (2010). KmL: k-means for longitudinal data. Computational Statistics, 25(2), 317–328. DOI: 10.1007/s00180-009-0178-4 ↗
如何引用本页
ScholarGate. (2026, June 22). Clustering of Criminal Offending Trajectories. ScholarGate. https://scholargate.app/zh/criminology/criminal-trajectory-clustering
选用哪种方法?
将本方法与其最相近的同类并置,并排研读——本馆将书籍铺陈于案上,取舍则由您定夺。
- Age-Crime Curve ModelingCriminology↔ 比较
- Criminal Career ParadigmCriminology↔ 比较
- Group-Based Trajectory ModelCriminology↔ 比较
- Life-Course Criminology AnalysisCriminology↔ 比较