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Podatkovno-panelno podudaranje po funkciji sklonosti×Uparivanje prema ocjeni sklonosti×
PodručjeUzročno zaključivanjeIstraživačka statistika
ObiteljRegression modelProcess / pipeline
Godina nastanka1997-19981983
TvoracHeckman, Ichimura & ToddPaul Rosenbaum and Donald Rubin
VrstaMatching / causal inferenceMethod
Temeljni izvorHeckman, 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 ↗
Drugi naziviPSM with panel data, longitudinal PSM, panel PSM, difference-in-differences PSMPSM, propensity score weighting, covariate balance
Srodne63
SažetakPanel 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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ScholarGateUsporedite metode: Panel Data Propensity Score Matching · Propensity Score Matching. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare