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| Gestuftes Keil-Cluster-Randomisierungsverfahren× | Differenz-in-Differenzen (DiD)× | |
|---|---|---|
| Fachgebiet≠ | Kausale Inferenz | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2007 | 1994 |
| Urheber≠ | Hussey and Hughes | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Typ≠ | Phased implementation trial design | Causal inference / panel regression |
| Wegweisende Quelle≠ | Hemming, 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 |
| Aliasnamen | SWCRT, SW-CRT, Stepped Wedge Design | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Verwandt≠ | 3 | 5 |
| Zusammenfassung≠ | A 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. |
| ScholarGateDatensatz ↗ |
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