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| Recidivism Survival Analysis× | Cox proportional hazards× | |
|---|---|---|
| Field≠ | Criminology | Epidemiology |
| Family≠ | Survival analysis | Process / pipeline |
| Year of origin≠ | 1988 | 1972 |
| Originator≠ | David R. Cox (method); Peter Schmidt & Ann Dryden Witte (criminological application) | Sir David Roxbee Cox |
| Type≠ | Time-to-event regression for reoffending | Semi-parametric regression model |
| Seminal source≠ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗ |
| Aliases | Time-to-Recidivism Modeling, Recidivism Hazard Modeling, Failure-Time Analysis of Reoffending, Survival Analysis of Reoffending | Cox regression, Cox PH model, proportional hazards model, CPH |
| Related≠ | 4 | 5 |
| Summary≠ | 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. | The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research. |
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