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| Analisis Sensitivitas untuk Bias Tersembunyi (Batas Rosenbaum / Nilai-E)× | Efek Perlakuan Rata-rata Lokal (LATE / CACE)× | |
|---|---|---|
| Bidang | Inferensi Kausal | Inferensi Kausal |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 2002 | 1994 |
| Pencetus≠ | Paul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value) | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) |
| Tipe≠ | Sensitivity analysis for causal inference | Instrumental-variable causal estimand |
| Sumber perintis≠ | 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. DOI ↗ |
| Alias≠ | Rosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivity | LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE) |
| Terkait | 5 | 5 |
| Ringkasan≠ | 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. |
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