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| Sensitivitätsanalyse für Kausalität in der Bildungsforschung× | Differenz-in-Differenzen (DiD)× | |
|---|---|---|
| Fachgebiet≠ | Kausale Inferenz | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1983–2002 | 1994 |
| Urheber≠ | Paul R. Rosenbaum (formal framework); applied in education research by Briggs and others | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Typ≠ | Causal robustness / bias assessment | Causal inference / panel regression |
| Wegweisende Quelle≠ | Rosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679 | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Aliasnamen≠ | Rosenbaum sensitivity analysis, hidden-bias sensitivity analysis, causal sensitivity analysis, SA for causal education studies | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | Sensitivity 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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