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Group-Based Trajectory Model×Criminal Career Paradigm×
DziedzinaCriminologyCriminology
RodzinaRegression modelProcess / pipeline
Rok powstania19931986
TwórcaDaniel S. Nagin & Kenneth C. LandAlfred Blumstein, Jacqueline Cohen, Jeffrey Roth & Christy Visher
TypFinite-mixture model of longitudinal developmental trajectoriesConceptual framework for decomposing offending over the life course
Źródło pierwotneNagin, 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 ↗Blumstein, A., Cohen, J., Roth, J. A., & Visher, C. A. (Eds.). (1986). Criminal Careers and 'Career Criminals' (Vols. 1–2). National Academy Press. ISBN: 9780309036887
Inne nazwyGBTM, Group-Based Modeling of Development, Nagin Trajectory Model, Semiparametric Group-Based ModelingCriminal Careers Framework, Career Criminal Paradigm, Offending Career Approach, Blumstein Criminal Career Model
Pokrewne44
PodsumowanieGroup-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.The criminal career paradigm is a framework for studying offending as a longitudinal sequence in an individual's life rather than as undifferentiated aggregate crime. Codified by Blumstein, Cohen, Roth, and Visher in the 1986 National Academy of Sciences report, it decomposes crime into distinct dimensions — whether someone offends (participation), how often active offenders offend (frequency, λ), and the onset, seriousness, and duration of the career — each potentially with different causes.
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ScholarGatePorównaj metody: Group-Based Trajectory Model · Criminal Career Paradigm. Pobrano 2026-06-24 z https://scholargate.app/pl/compare