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Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Analýza přerušených časových řad ve výzkumu vzdělávání×Rozdíl v rozdílech (Diff-in-Diff)×
OborKauzální inferenceEkonometrie
RodinaRegression modelRegression model
Rok vzniku1979-20021994
TvůrceShadish, Cook & Campbell (quasi-experimental design); Wagner et al. (segmented regression formalization)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypQuasi-experimental causal inferenceCausal inference / panel regression
Původní zdrojShadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Další názvyITS in education, educational ITS, segmented regression in education, policy interrupted time seriesdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Příbuzné45
ShrnutíInterrupted time series (ITS) analysis is a quasi-experimental design that estimates the causal effect of an education policy or intervention by examining whether an outcome trend changes abruptly at the point of implementation. Applied to education, it is used to evaluate reforms, curriculum changes, testing policies, and school interventions using routinely collected longitudinal data without a randomised control group.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: Interrupted Time Series in Education Research · Difference-in-Differences. Získáno 2026-06-18 z https://scholargate.app/cs/compare