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Vekting med propensitets-skårer i utdanningsforskning×Propensity Score Matching×
FagfeltKausal inferensForskningsstatistikk
FamilieRegression modelProcess / pipeline
Opprinnelsesår1983 (theory); widely adopted in education research from 2000s1983
OpphavspersonRosenbaum & Rubin (foundational theory, 1983); Thoemmes & Kim (education-focused review, 2011)Paul Rosenbaum and Donald Rubin
TypeQuasi-experimental causal inferenceMethod
Opprinnelig kildeRosenbaum, 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 ↗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 ↗
AliasPSW in education, inverse probability weighting in education, IPW education, propensity weighting educationPSM, propensity score weighting, covariate balance
Relaterte53
SammendragPropensity score weighting (PSW) is a quasi-experimental technique that reweights observational samples so that treated and comparison students look similar on measured background characteristics, allowing credible causal estimates of educational interventions — such as program participation, instructional method, or school type — without random assignment.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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ScholarGateSammenlign metoder: Propensity Score Weighting in Education Research · Propensity Score Matching. Hentet 2026-06-20 fra https://scholargate.app/no/compare