Compare methods

	Regression Discontinuity in Sentencing	Propensity Weighting in Criminology
Field	Criminology	Criminology
Family	Process / pipeline	Process / pipeline
Year of origin	1983	1983
Originator	Richard A. Berk & David Rauma (criminological application); Donald L. Thistlethwaite & Donald T. Campbell (design origin)	Paul R. Rosenbaum & Donald B. Rubin (propensity score); Robert Apel & Gary Sweeten (criminological adaptation)
Type	Quasi-experimental causal design at a policy threshold	Observational causal estimator for justice exposures
Seminal source	Berk, R. A., & Rauma, D. (1983). Capitalizing on nonrandom assignment to treatments: A regression-discontinuity evaluation of a crime-control program. Journal of the American Statistical Association, 78(381), 21–27.	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.
Aliases	Sentencing Threshold RDD, Cutoff-Based Justice Evaluation, Risk-Score Discontinuity Design, Age-of-Majority Discontinuity	IPTW for Justice Exposures, Inverse-Probability Weighting in Criminology, Propensity-Weighted Crime Effects, Observational Treatment-Effect Weighting
Related	4	4
Summary	Regression discontinuity (RD) in sentencing exploits the sharp thresholds built into justice policy — sentencing-guideline cutoffs, the age of majority, risk-score thresholds that trigger detention or diversion — to estimate causal effects without a randomized trial. Units just above the cutoff receive a different treatment from units just below it, yet they are otherwise nearly identical, so comparing their outcomes isolates the effect of crossing the line. Berk and Rauma's 1983 evaluation of a crime-control program showed how criminologists can 'capitalize on nonrandom assignment' created by such rules.	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.