Сравнение на методи

	Неясен регресионен разривен дизайн в изследванията на образованието	Съгласуване по показател на склонност
Област	Причинно-следствено заключение	Статистика за изследвания
Семейство	Regression model	Process / pipeline
Година на възникване	Late 1990s–2000s	1983
Създател	Imbens & Lemieux (2008); applied in education by Jacob & Lefgren (2004) and Angrist & Lavy (1999)	Paul Rosenbaum and Donald Rubin
Тип	Quasi-experimental / causal inference	Method
Основополагащ източник	Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635.	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.
Други названия	Fuzzy RDD, Fuzzy RD, Imperfect RDD, Non-sharp RD	PSM, propensity score weighting, covariate balance
Свързани	4	3
Резюме	Fuzzy Regression Discontinuity Design (Fuzzy RDD) is a quasi-experimental causal method that exploits a known score threshold — such as a test cutoff — to estimate the effect of a program or intervention when assignment is imperfect. Widely used in education research to evaluate summer school, remedial programs, scholarships, and class-size rules, it uses two-stage least squares to recover a local average treatment effect for students near the threshold.	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.