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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Analiza e ndjeshmërisë ndaj ndikimit të fshehur (Kufijtë e Rosenbaum / Vlera E)×Përshtatja e Rezultatit të Tendencës×
FushaInferenca kauzaleStatistika e hulumtimit
FamiljaRegression modelProcess / pipeline
Viti i origjinës20021983
KrijuesiPaul R. Rosenbaum (bounds); Tyler J. VanderWeele & Peng Ding (E-value)Paul Rosenbaum and Donald Rubin
LlojiSensitivity analysis for causal inferenceMethod
Burimi themeluesRosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗
Emërtime të tjeraRosenbaum bounds, E-value, hidden bias sensitivity analysis, unmeasured confounding sensitivityPSM, propensity score weighting, covariate balance
Të lidhura53
PërmbledhjaSensitivity 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).Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.
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ScholarGateKrahasoni metodat: Sensitivity Analysis for Unmeasured Confounding · Propensity Score Matching. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare