mlsanityData to 7 Oct 2026

Bayesian Causal Inference: A Critical Review

arXiv 2206.15460 ↗First posted 30 Jun 2022stat.ME stat.APcited by 21

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Abstract (arXiv)

This paper provides a critical review of the Bayesian perspective of causal inference based on the potential outcomes framework. We review the causal estimands, identification assumptions, the general structure of Bayesian inference of causal effects, and sensitivity analysis. We highlight issues that are unique to Bayesian causal inference, including the role of the propensity score, definition of identifiability, the choice of priors in both low and high dimensional regimes. We point out the central role of covariate overlap and more generally the design stage in Bayesian causal inference. We extend the discussion to two complex assignment mechanisms: instrumental variable and time-varying treatments. Throughout, we illustrate the key concepts via examples.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jun 2022.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 2; 2025: 8; 2026: 6.

21 papers.

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  1. 2025CausalPFN: Amortized Causal Effect Estimation via In-Context Learningcited by 43
  2. 2023Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confoundingcited by 7
  3. 2025An AI-powered Bayesian generative modeling approach for causal inference in observational studiescited by 6
  4. 2023Bayesian Safe Policy Learning with Chance Constrained Optimization: Application to Military Security Assessment during the Vietnam Warcited by 4
  5. 2023Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Modelcited by 4
  6. 2026Causal Foundation Models with Continuous Treatmentscited by 4
  7. 2025Causal-EPIG: A Prediction-Oriented Active Learning Framework for CATE Estimationcited by 2
  8. 2023A Forecaster's Review of Judea Pearl's Causality: Models, Reasoning and Inference, Second Edition, 2009cited by 1
  9. 2024A flexible Bayesian g-formula for causal survival analyses with time-dependent confoundingcited by 1
  10. 2025Bayesian Estimation of Causal Effects Using Proxies of a Latent Interference Networkcited by 1
  11. 2025Horseshoe Forests for High-Dimensional Causal Survival Analysiscited by 1
  12. 2025ActiveCQ: Active Estimation of Causal Quantitiescited by 1
9 more
  1. 2025Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effectscited by 1
  2. 2026Retrospective Counterfactual Prediction by Conditioning on the Factual Outcome: A Cross-World Approachcited by 1
  3. 2023Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlapcited by 0
  4. 2024Individualized Multi-Treatment Response Curves Estimation using RBF-net with Shared Neuronscited by 0
  5. 2025Improving Generative Methods for Causal Evaluation via Simulation-Based Inferencecited by 0
  6. 2026Bayesian Supervised Causal Clusteringcited by 0
  7. 2026Bayesian Sensitivity of Causal Inference Estimators under Evidence-Based Priorscited by 0
  8. 2026Some cautionary tales about Bayesian predictive inferencecited by 0
  9. 2026AI Deployment Accountability Engineering: A Vision for Accountable AI in Safety-Critical Socio-Technical Systemscited by 0