ScholarGate
सहायक

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)×स्थानीय औसत उपचार प्रभाव (LATE / CACE)×
क्षेत्रकारणात्मक अनुमानकारणात्मक अनुमान
परिवारRegression modelRegression model
उद्भव वर्ष20021994
प्रवर्तकPaul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value)Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
प्रकारSensitivity analysis for causal inferenceInstrumental-variable causal estimand
मौलिक स्रोतRosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗
उपनामRosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivityLATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
संबंधित55
सारांशSensitivity 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).The Local Average Treatment Effect is an instrumental-variable estimand, introduced by Imbens and Angrist (1994) and formalised with Rubin (1996), that recovers the average treatment effect for the subpopulation of compliers — units whose treatment status is actually moved by the instrument. It is closely tied to compliance analysis.
ScholarGateडेटासेट
  1. v1
  2. 2 स्रोत
  3. PUBLISHED
  1. v1
  2. 2 स्रोत
  3. PUBLISHED

खोज पर जाएँ स्लाइड डाउनलोड करें

ScholarGateविधियों की तुलना करें: Sensitivity Analysis for Unmeasured Confounding · Local Average Treatment Effect. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare