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Placebotester för kausal inferens×Känslighetsanalys för dolt urvalsbias (Rosenbaum Bounds / E-value)×
ÄmnesområdeKausal inferensKausal inferens
FamiljRegression modelRegression model
Ursprungsår20102002
UpphovspersonAbadie, Diamond & Hainmueller (synthetic control placebos); Imbens & Lemieux (RDD validity)Paul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value)
TypFalsification / robustness test family for causal inferenceSensitivity analysis for causal inference
UrsprungskällaAbadie, 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 ↗Rosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679
Aliasfalsification tests, placebo checks, refutation tests, Plasebo Testleri — Nedensel Çıkarım DoğrulamaRosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivity
Närliggande55
SammanfattningPlacebo 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).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).
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ScholarGateJämför metoder: Placebo Tests · Sensitivity Analysis for Unmeasured Confounding. Hämtad 2026-06-18 från https://scholargate.app/sv/compare