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Analýza citlivosti na skryté skreslenie (Rosenbaumove hranice / E-hodnota)×Nástrojové premenné pomocou dvojstupňového metódy najmenších štvorcov (IV/2SLS)×
OdborKauzálna inferenciaKauzálna inferencia
RodinaRegression modelRegression model
Rok vzniku20022009
TvorcaPaul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value)Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)
TypSensitivity analysis for causal inferenceInstrumental-variables regression
Pôvodný zdrojRosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Ďalšie názvyRosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivityinstrumental variables, IV estimation, 2SLS, instrumental variable regression
Príbuzné55
ZhrnutieSensitivity 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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ScholarGatePorovnať metódy: Sensitivity Analysis for Unmeasured Confounding · Two-Stage Least Squares (2SLS). Získané 2026-06-18 z https://scholargate.app/sk/compare