Compară metode

	Potrivirea scorului de propensitate în cercetarea educațională	Estimator de potrivire
Domeniu	Inferență cauzală	Inferență cauzală
Familie	Regression model	Regression model
Anul apariției	1983 (foundational); education adoption widespread from late 1990s	1973
Autorul original	Rosenbaum & Rubin (1983); widely adopted in education research via Shadish, Cook & Campbell (2002)	Rubin (1973); large-sample theory by Abadie & Imbens (2006)
Tip	Quasi-experimental / matching-based causal inference	Nonparametric matching / causal inference
Sursa seminală	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.	Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267.
Denumiri alternative	PSM in education, educational PSM, PSM for program evaluation in schools, propensity matching education	nearest-neighbor matching, NNM, matching on covariates, covariate matching
Înrudite	5	6
Rezumat	Propensity Score Matching (PSM) in education research is a quasi-experimental technique that creates comparable treatment and control groups from observational student, teacher, or school data. By balancing groups on observed background characteristics, it enables credible causal estimates of educational interventions — such as tutoring programs, school choice policies, or teacher professional development — when random assignment is infeasible.	The matching estimator identifies the causal effect of a treatment by pairing each treated unit with one or more untreated units that have similar observed characteristics. Formalised by Rubin (1973) and given rigorous large-sample theory by Abadie and Imbens (2006), it constructs a credible control group from observational data without requiring a parametric model for the outcome.