Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Propensity Weighting in Criminology× | Recidivism Survival Analysis× | |
|---|---|---|
| Domeniu | Criminology | Criminology |
| Familie≠ | Process / pipeline | Survival analysis |
| Anul apariției≠ | 1983 | 1988 |
| Autorul original≠ | Paul R. Rosenbaum & Donald B. Rubin (propensity score); Robert Apel & Gary Sweeten (criminological adaptation) | David R. Cox (method); Peter Schmidt & Ann Dryden Witte (criminological application) |
| Tip≠ | Observational causal estimator for justice exposures | Time-to-event regression for reoffending |
| Sursa seminală≠ | Apel, R. J., & Sweeten, G. (2010). Propensity score matching in criminology and criminal justice. In A. R. Piquero & D. Weisburd (Eds.), Handbook of Quantitative Criminology (pp. 543–562). Springer. DOI ↗ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| Denumiri alternative | IPTW for Justice Exposures, Inverse-Probability Weighting in Criminology, Propensity-Weighted Crime Effects, Observational Treatment-Effect Weighting | Time-to-Recidivism Modeling, Recidivism Hazard Modeling, Failure-Time Analysis of Reoffending, Survival Analysis of Reoffending |
| Înrudite | 4 | 4 |
| Rezumat≠ | Propensity weighting estimates the causal effect of a justice exposure — incarceration, gang membership, a program, or a sanction — from observational data when randomization was impossible. It models each unit's probability of receiving the exposure given measured confounders (the propensity score) and then weights units by the inverse of that probability, creating a pseudo-population in which the exposure is unrelated to those confounders. Rosenbaum and Rubin introduced the propensity score in 1983, and Apel and Sweeten adapted it for criminology, where ethical and practical barriers make experiments rare. | 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. |
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