विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| छिपे हुए पूर्वाग्रह के लिए संवेदनशीलता विश्लेषण (रोजनबाम बाउंड्स / ई-वैल्यू)× | कारण अनुमान के लिए प्लेसबो परीक्षण× | |
|---|---|---|
| क्षेत्र | कारणात्मक अनुमान | कारणात्मक अनुमान |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2002 | 2010 |
| प्रवर्तक≠ | Paul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value) | Abadie, Diamond & Hainmueller (synthetic control placebos); Imbens & Lemieux (RDD validity) |
| प्रकार≠ | Sensitivity analysis for causal inference | Falsification / robustness test family for causal inference |
| मौलिक स्रोत≠ | Rosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679 | Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗ |
| उपनाम≠ | Rosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivity | falsification tests, placebo checks, refutation tests, Plasebo Testleri — Nedensel Çıkarım Doğrulama |
| संबंधित | 5 | 5 |
| सारांश≠ | Sensitivity analysis for hidden bias is a family of methods that quantify how strongly an unmeasured confounder would have to operate before it could overturn a causal conclusion drawn from observational data. It was crystallised by Paul Rosenbaum's sensitivity bounds (2002) and extended by VanderWeele and Ding's E-value (2017). | Placebo tests are a family of falsification checks that probe the credibility of a causal claim by re-running the analysis on a fake treatment, a false intervention date, or an outcome that should not have been affected. The approach was popularised through the synthetic control work of Abadie, Diamond and Hainmueller (2010) and the regression-discontinuity validity checks of Imbens and Lemieux (2008). |
| ScholarGateडेटासेट ↗ |
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