Regression modelQuasi-experimental / causal inference

Robusna metoda sintetičke kontrole

Robusna metoda sintetičke kontrole proširuje klasični sintetički kontrolni procjenitelj pružajući statistički valjanu kvantifikaciju nesigurnosti i zaključivanje. Razvijena od strane Cattanea, Fenga i Titiunik (2021.), ona rješava temeljno ograničenje izvornog pristupa – nedostatak formalnih intervala predviđanja – čineći uzročne zaključke obranjivijima kada se promatra samo jedna tretirana jedinica.

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Izvori

  1. Cattaneo, M. D., Feng, Y., & Titiunik, R. (2021). Prediction Intervals for Synthetic Control Methods. Journal of the American Statistical Association, 116(536), 1865-1880. DOI: 10.1080/01621459.2021.1979561
  2. Abadie, A., Diamond, A., & Hainmueller, J. (2015). Comparative Politics and the Synthetic Control Method. American Journal of Political Science, 59(2), 495-510. DOI: 10.1111/ajps.12116

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Robust Synthetic Control Method with Uncertainty Quantification. ScholarGate. https://scholargate.app/hr/causal-inference/robust-synthetic-control-method

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ScholarGateRobust Synthetic Control Method (Robust Synthetic Control Method with Uncertainty Quantification). Preuzeto 2026-06-15 s https://scholargate.app/hr/causal-inference/robust-synthetic-control-method · Skup podataka: https://doi.org/10.5281/zenodo.20539026