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OdborKauzálna inferenciaŠtatistika vo výskume
RodinaRegression modelProcess / pipeline
Rok vzniku1997-19981983
TvorcaHeckman, Ichimura & ToddPaul Rosenbaum and Donald Rubin
TypMatching / causal inferenceMethod
Pôvodný zdrojHeckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an Econometric Evaluation Estimator. Review of Economic Studies, 65(2), 261-294. 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 ↗
Ďalšie názvyPSM with panel data, longitudinal PSM, panel PSM, difference-in-differences PSMPSM, propensity score weighting, covariate balance
Príbuzné63
ZhrnutiePanel data propensity score matching combines the bias-reduction of PSM with the longitudinal structure of panel data, enabling causal estimation of treatment effects by matching treated and control units on observable pre-treatment characteristics and then differencing within matched pairs over time. Developed in the framework of Heckman, Ichimura, and Todd (1998), it is especially valuable when randomisation is infeasible and both selection on observables and time-varying confounding must be addressed simultaneously.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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ScholarGatePorovnať metódy: Panel Data Propensity Score Matching · Propensity Score Matching. Získané 2026-06-18 z https://scholargate.app/sk/compare