手法を比較

	隠れたバイアスに対する感度分析（ローゼンバウム限界値 / E値）	局所的平均処置効果（LATE / CACE）
分野	因果推論	因果推論
系統	Regression model	Regression model
提唱年	2002	1994
提唱者	Paul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value)	Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
種類	Sensitivity analysis for causal inference	Instrumental-variable causal estimand
原典	Rosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679	Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475.
別名	Rosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivity	LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
関連	5	5
概要	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).	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.