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)× | साधनात्मक चर द्विपदीय न्यूनतम वर्ग (IV/2SLS) के माध्यम से× | |
|---|---|---|
| क्षेत्र | कारणात्मक अनुमान | कारणात्मक अनुमान |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2002 | 2009 |
| प्रवर्तक≠ | Paul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value) | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| प्रकार≠ | Sensitivity analysis for causal inference | Instrumental-variables regression |
| मौलिक स्रोत≠ | 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 |
| उपनाम | Rosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivity | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| 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). | IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009). |
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