Salīdzināt metodes

	Repeat Victimization Analysis	Near-Repeat Analysis
Nozare	Criminology	Criminology
Saime	Regression model	Process / pipeline
Izcelsmes gads	1993	2003
Autors	Ken Pease, Graham Farrell & colleagues	Michael Townsley, Shane Johnson & Kate Bowers
Tips	Time-to-event analysis of elevated short-term re-victimization risk	Space-time clustering test for crime contagion
Pirmavots	Tseloni, A., & Pease, K. (2003). Repeat personal victimization: 'Boosts' or 'flags'? British Journal of Criminology, 43(1), 196–212.	Townsley, M., Homel, R., & Chaseling, J. (2003). Infectious burglaries: A test of the near repeat hypothesis. British Journal of Criminology, 43(3), 615–633.
Citi nosaukumi	Repeat Victimisation Analysis, Re-Victimization Risk Analysis, Multiple Victimization Analysis, Time-Course of Repeat Victimization	Near Repeat Calculator Method, Space-Time Near-Repeat Analysis, Near-Repeat Victimization, Contagion Crime Pattern Analysis
Saistītās	4	4
Kopsavilkums	Repeat 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.