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Robust Causal Impact Analysis/Evidence
Method evidence record

Robust Causal Impact Analysis

Robust Causal Impact Analysis extends the Bayesian structural time-series CausalImpact framework (Brodersen et al., 2015) by embedding systematic robustness checks — in-time placebo tests, in-space placebo controls, covariate sensitivity analysis, and prior sensitivity assessments — to verify that a detected intervention effect is genuine and not an artifact of model choices or coincidental data patterns.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Robust Causal Impact Analysis with Sensitivity and Placebo Checks
Taxonomic method record · regression-model / causal-inference
  • Brodersen, K. H., Gallusser, F., Koehler, J., Remy, N., & Scott, S. L. (2015). Inferring causal impact using Bayesian structural time-series models. Annals of Applied Statistics, 9(1), 247-274. · DOI 10.1214/14-AOAS788
  • Cunningham, S. (2021). Causal Inference: The Mixtape. Yale University Press. · ISBN 978-0300251685
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Curated claims

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketBayesian Causal Impact Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketCausal Impact Analysismachine-suggested · Relational suggestion, not evidence.Same method familyInterrupted Time Seriesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSensitivity Analysis for Causalitymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSynthetic Control Methodmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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