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Causal Impact Analysis/Evidence
Method evidence record

Causal Impact Analysis

Causal Impact Analysis, introduced by Brodersen et al. (2015) at Google, uses Bayesian structural time-series models to estimate what would have happened to an outcome had an intervention never occurred. By constructing a probabilistic counterfactual from pre-treatment data and control covariates, it quantifies point-in-time and cumulative treatment effects with full posterior uncertainty intervals.

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Source record

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

Bayesian Structural Time-Series Causal Impact Analysis
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
  • CausalImpact. Wikipedia. · URL
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Related methods

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

See alsoBayesian Structural Time Seriesmachine-suggested · Relational suggestion, not evidence.Same method familyDifference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Same method familyInterrupted Time Seriesmachine-suggested · Relational suggestion, not evidence.See alsoPropensity Score Matchingmachine-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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