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Analýza citlivosti pro kauzalitu ve výzkumu vzdělávání×Rozdíl v rozdílech (Diff-in-Diff)×
OborKauzální inferenceEkonometrie
RodinaRegression modelRegression model
Rok vzniku1983–20021994
TvůrcePaul R. Rosenbaum (formal framework); applied in education research by Briggs and othersCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypCausal robustness / bias assessmentCausal inference / panel regression
Původní zdrojRosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Další názvyRosenbaum sensitivity analysis, hidden-bias sensitivity analysis, causal sensitivity analysis, SA for causal education studiesdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Příbuzné65
ShrnutíSensitivity analysis for causality in education research tests how robust a quasi-experimental finding is to unmeasured confounding. Rather than assuming all bias has been removed, it quantifies how large a hidden bias would need to be to overturn a causal conclusion — a critical safeguard when randomisation is impossible, which is common in educational settings.Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.
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ScholarGatePorovnat metody: Sensitivity analysis for causality in education research · Difference-in-Differences. Získáno 2026-06-17 z https://scholargate.app/cs/compare