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Ensaio Clínico Randomizado por Conglomerados em Degrau×Diferenças em Diferenças (DiD)×
ÁreaInferência causalEconometria
FamíliaRegression modelRegression model
Ano de origem20071994
Autor originalHussey and HughesCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipoPhased implementation trial designCausal inference / panel regression
Fonte seminalHemming, K., Haines, T. P., Chilton, P. J., Girling, A. J., & Lilford, R. J. (2015). The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting. British Medical Journal, 350, h391. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Outros nomesSWCRT, SW-CRT, Stepped Wedge Designdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionados35
ResumoA stepped wedge cluster randomized trial is an experimental design where clusters (e.g., schools, hospitals, communities) are randomized to receive an intervention in a phased, staggered manner over time. First formally described by Hussey and Hughes in 2007, this design combines the benefits of cluster randomization with a time-stepped implementation strategy. It is particularly useful for evaluating the effectiveness of interventions in real-world healthcare and public health 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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ScholarGateComparar métodos: Stepped Wedge Cluster Randomized Trial · Difference-in-Differences. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare