Módszerek összehasonlítása

	Propensity Score Matching in Education Research	Propensity Score Weighting (PSW / IPW)
Tudományterület	Oksági következtetés	Oksági következtetés
Módszercsalád	Regression model	Regression model
Keletkezés éve	1983 (foundational); education adoption widespread from late 1990s	1983 (propensity score); 2003 (efficient IPW estimator)
Megalkotó	Rosenbaum & Rubin (1983); widely adopted in education research via Shadish, Cook & Campbell (2002)	Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
Típus	Quasi-experimental / matching-based causal inference	Causal inference / reweighting
Alapmű	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.	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.
Alternatív nevek	PSM in education, educational PSM, PSM for program evaluation in schools, propensity matching education	PSW, inverse probability weighting, IPW, propensity-based weighting
Kapcsolódó	5	6
Összefoglaló	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.	Propensity score weighting is a causal-inference method that reweights observations so that the covariate distributions of treated and untreated units look exchangeable, enabling unbiased estimation of average treatment effects from observational data. Each unit receives a weight that is the inverse of its probability of receiving the treatment it actually received — a strategy formalised by Rosenbaum and Rubin (1983) and given its efficient semiparametric form by Hirano, Imbens and Ridder (2003).