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Repeat Victimization Analysis×Near-Repeat Analysis×
FachgebietCriminologyCriminology
FamilieRegression modelProcess / pipeline
Entstehungsjahr19932003
UrheberKen Pease, Graham Farrell & colleaguesMichael Townsley, Shane Johnson & Kate Bowers
TypTime-to-event analysis of elevated short-term re-victimization riskSpace-time clustering test for crime contagion
Wegweisende QuelleTseloni, A., & Pease, K. (2003). Repeat personal victimization: 'Boosts' or 'flags'? British Journal of Criminology, 43(1), 196–212. DOI ↗Townsley, M., Homel, R., & Chaseling, J. (2003). Infectious burglaries: A test of the near repeat hypothesis. British Journal of Criminology, 43(3), 615–633. DOI ↗
AliasnamenRepeat Victimisation Analysis, Re-Victimization Risk Analysis, Multiple Victimization Analysis, Time-Course of Repeat VictimizationNear Repeat Calculator Method, Space-Time Near-Repeat Analysis, Near-Repeat Victimization, Contagion Crime Pattern Analysis
Verwandt44
ZusammenfassungRepeat victimization analysis studies the sharply elevated short-term risk that the same target — a household, person, or business — is victimized again soon after an initial offense. Established as a crime-prevention priority by Ken Pease, Graham Farrell, and colleagues in the early 1990s, it models the time-course of re-victimization, quantifies how the hazard of a repeat decays as time passes since the first event, and asks whether repeats arise because an event 'boosts' future risk or because stable target features 'flag' that risk.Near-repeat analysis tests whether crimes cluster in space and time beyond chance: after a crime occurs, are nearby locations at elevated risk for a short period? Developed in the early 2000s by Townsley, Johnson, Bowers and colleagues for burglary, it formalizes the 'contagion' or 'communicable disease' pattern of crime using a Knox space-time test against a Monte Carlo reference distribution.
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ScholarGateMethoden vergleichen: Repeat Victimization Analysis · Near-Repeat Analysis. Abgerufen am 2026-06-24 von https://scholargate.app/de/compare