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Desenho de Regressão por Descontinuidade (RDD)×Propensity Score Matching×
ÁreaEconometriaEstatística para pesquisa
FamíliaRegression modelProcess / pipeline
Ano de origem20081983
Autor originalImbens & Lemieux; Lee & Lemieux (modern practice); Cattaneo, Idrobo & TitiunikPaul Rosenbaum and Donald Rubin
TipoQuasi-experimental causal designMethod
Fonte seminalImbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗
Outros nomesRDD, regression discontinuity, sharp regression discontinuity, Regresyon Süreksizliği Tasarımı (RDD)PSM, propensity score weighting, covariate balance
Relacionados53
ResumoRegression Discontinuity Design is a quasi-experimental method that estimates a local causal effect around a threshold (cutoff) value, comparing units just below and just above the cutoff as if they were almost randomly assigned. It is the design developed for applied practice by Imbens and Lemieux (2008) and by Lee and Lemieux (2010).Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.
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ScholarGateComparar métodos: Regression Discontinuity Design · Propensity Score Matching. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare