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Review your selected methods side by side; rows that differ are highlighted.
| Desistance Analysis× | Recidivism Survival Analysis× | |
|---|---|---|
| Field | Criminology | Criminology |
| Family≠ | Regression model | Survival analysis |
| Year of origin≠ | 2001 | 1988 |
| Originator≠ | John H. Laub & Robert J. Sampson; Shawn D. Bushway et al. | David R. Cox (method); Peter Schmidt & Ann Dryden Witte (criminological application) |
| Type≠ | Time-to-event and trajectory modeling of ceasing offending | Time-to-event regression for reoffending |
| Seminal source≠ | Laub, J. H., & Sampson, R. J. (2001). Understanding desistance from crime. Crime and Justice, 28, 1–69. DOI ↗ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| Aliases | Desistance Modeling, Time-to-Desistance Analysis, Cessation-of-Offending Analysis, Criminal Career Termination Analysis | Time-to-Recidivism Modeling, Recidivism Hazard Modeling, Failure-Time Analysis of Reoffending, Survival Analysis of Reoffending |
| Related | 4 | 4 |
| Summary≠ | Desistance analysis models the process by which offenders cease offending — estimating the timing of the last offense, the hazard of termination, and the decline of offending toward zero. Sharpened by Laub and Sampson and by Bushway and colleagues around 2001, it treats desistance not as a single event but as a process, and confronts the deep measurement problem of telling true termination apart from a long gap or a gradual slowing of crime. | Recidivism survival analysis models the time from a release or index event until an individual reoffends, treating reoffending as a time-to-event ('failure') outcome with censoring for those not observed to fail. It applies survival methods — Kaplan-Meier curves, Cox proportional-hazards regression, and split-population models — to answer not just whether someone recidivates but how quickly and what raises or lowers that risk over time. |
| ScholarGateDataset ↗ |
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