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| Repeat Victimization Analysis× | Near-Repeat Analysis× | |
|---|---|---|
| Obor | Criminology | Criminology |
| Rodina≠ | Regression model | Process / pipeline |
| Rok vzniku≠ | 1993 | 2003 |
| Tvůrce≠ | Ken Pease, Graham Farrell & colleagues | Michael Townsley, Shane Johnson & Kate Bowers |
| Typ≠ | Time-to-event analysis of elevated short-term re-victimization risk | Space-time clustering test for crime contagion |
| Původní zdroj≠ | Tseloni, 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 ↗ |
| Další názvy | 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 |
| Příbuzné | 4 | 4 |
| Shrnutí≠ | 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. |
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