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Sensitivity Analysis for Causality

Sensitivity analysis for causality assesses how robust a causal conclusion is to unobserved confounding. Rather than assuming all confounders are controlled, it asks: how strong would an unmeasured variable need to be to overturn the estimated effect? It is an indispensable robustness check after any quasi-experimental or observational causal analysis.

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Sensitivity Analysis for Hidden Bias in Causal Inference

Taksonomisk metoderegistrering · regression-model / causal-inference

Rosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. · ISBN 978-0387989679
Cinelli, C., & Hazlett, C. (2020). Making sense of sensitivity: Extending omitted variable bias. Journal of the Royal Statistical Society: Series B, 82(1), 39-67. · DOI 10.1111/rssb.12348

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