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Váženie skóre propensity pre hodnotenie politík×Vážená inverzná pravdepodobnosť liečby (IPW / IPTW)×
OdborKauzálna inferenciaKauzálna inferencia
RodinaRegression modelRegression model
Rok vzniku1983/20032000
TvorcaRosenbaum & Rubin (1983); extended to policy evaluation by Hirano, Imbens & Ridder (2003)Robins, Hernán & Brumback
TypQuasi-experimental causal inferenceCausal inference weighting estimator
Pôvodný zdrojHirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. Econometrica, 71(4), 1161-1189. DOI ↗Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗
Ďalšie názvyPSW policy evaluation, inverse probability weighting for policy, IPW policy evaluation, policy PSWIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Príbuzné65
ZhrnutiePolicy evaluation propensity score weighting applies inverse-probability weighting to observational data to estimate the causal effect of a policy program. By reweighting participants and non-participants so they resemble a target population, it removes selection bias from voluntary or administratively allocated program assignment without requiring randomization.Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.
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ScholarGatePorovnať metódy: Policy Evaluation Propensity Score Weighting · Inverse Probability Weighting. Získané 2026-06-19 z https://scholargate.app/sk/compare