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Regression discontinuity design in education research×Diferenças em Diferenças (DiD)×
ÁreaInferência causalEconometria
FamíliaRegression modelRegression model
Ano de origem1960 (origination); 1999-2010 (education economics canon)1994
Autor originalThistlethwaite & Campbell (1960); popularized in education economics by Angrist & Lavy (1999), Lee & Lemieux (2010)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipoQuasi-experimental causal inferenceCausal inference / panel regression
Fonte seminalLee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Outros nomesRDD in education, education RD design, sharp RDD education, score-cutoff designdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionados55
ResumoRegression discontinuity design (RDD) in education research exploits a score-based eligibility cutoff — such as a test score threshold, GPA requirement, or age cutoff — to estimate the causal effect of a program, intervention, or policy on student or school outcomes. Units just below and just above the cutoff are treated as near-randomly assigned, enabling credible causal inference without a randomized trial.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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ScholarGateComparar métodos: Regression discontinuity design in education research · Difference-in-Differences. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare