Comment on "Blessings of Multiple Causes"
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Abstract (arXiv)
(This comment has been updated to respond to Wang and Blei's rejoinder [arXiv:1910.07320].) The premise of the deconfounder method proposed in "Blessings of Multiple Causes" by Wang and Blei [arXiv:1805.06826], namely that a variable that renders multiple causes conditionally independent also controls for unmeasured multi-cause confounding, is incorrect. This can be seen by noting that no fact about the observed data alone can be informative about ignorability, since ignorability is compatible with any observed data distribution. Methods to control for unmeasured confounding may be valid with additional assumptions in specific settings, but they cannot, in general, provide a checkable approach to causal inference, and they do not, in general, require weaker assumptions than the assumptions that are commonly used for causal inference. While this is outside the scope of this comment, we note that much recent work on applying ideas from latent variable modeling to causal inference problems suffers from similar issues.
Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Oct 2019.
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Citing papers per year: 2021: 5; 2022: 2; 2023: 3; 2024: 4; 2025: 0; 2026: 2.
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- 2021Sequential Deconfounding for Causal Inference with Unobserved Confounderscited by 24
- 2023Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounderscited by 17
- 2021Causal Inference Despite Limited Global Confounding via Mixture Modelscited by 9
- 2022Estimating Social Influence from Observational Datacited by 5
- 2023Scalable Computation of Causal Boundscited by 5
- 2024What is Fair? Defining Fairness in Machine Learning for Healthcited by 5
- 2024Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learningcited by 5
- 2021Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxiescited by 4
- 2021Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implicationcited by 3
- 2024Synthetic Potential Outcomes and Causal Mixture Identifiabilitycited by 3
- 2024Automating the Selection of Proxy Variables of Unmeasured Confounderscited by 2
- 2021What can the millions of random treatments in nonexperimental data reveal about causes?cited by 1
4 more
- 2022Deep Causal Reasoning for Recommendationscited by 1
- 2023Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Datacited by 1
- 2026Shrinkage priors for Bayesian Substitute Confounderscited by 0
- 2026Spatiotemporal Proximal Causal Inference under Hidden Confounding and Interferencecited by 0
- 2026Spatiotemporal Proximal Causal Inference under Hidden Confounding and Interference2 Aug 2026
- 2026Shrinkage priors for Bayesian Substitute Confounders16 Jun 2026
- 2024Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning8 Dec 2024
- 2024What is Fair? Defining Fairness in Machine Learning for Health13 Jun 2024
- 2024Synthetic Potential Outcomes and Causal Mixture Identifiability29 May 2024
- 2024Automating the Selection of Proxy Variables of Unmeasured Confounders25 May 2024
- 2023Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data16 Oct 2023
- 2023Scalable Computation of Causal Bounds4 Aug 2023
- 2023Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders4 Mar 2023
- 2022Estimating Social Influence from Observational Data24 Mar 2022
- 2022Deep Causal Reasoning for Recommendations6 Jan 2022
- 2021Causal Inference Despite Limited Global Confounding via Mixture Models22 Dec 2021
4 more
- 2021Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies19 Dec 2021
- 2021Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication4 Oct 2021
- 2021What can the millions of random treatments in nonexperimental data reveal about causes?3 May 2021
- 2021Sequential Deconfounding for Causal Inference with Unobserved Confounders16 Apr 2021
- 2022Deep Causal Reasoning for Recommendationscited by 1
- 2022Deep Causal Reasoning for Recommendations6 Jan 2022
- 2021Sequential Deconfounding for Causal Inference with Unobserved Confounderscited by 24
- 2023Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounderscited by 17
- 2021Causal Inference Despite Limited Global Confounding via Mixture Modelscited by 9
- 2022Estimating Social Influence from Observational Datacited by 5
- 2023Scalable Computation of Causal Boundscited by 5
- 2024What is Fair? Defining Fairness in Machine Learning for Healthcited by 5
- 2021Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxiescited by 4
- 2021Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implicationcited by 3
- 2024Synthetic Potential Outcomes and Causal Mixture Identifiabilitycited by 3
- 2024Automating the Selection of Proxy Variables of Unmeasured Confounderscited by 2
- 2021What can the millions of random treatments in nonexperimental data reveal about causes?cited by 1
- 2023Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Datacited by 1
12 most cited of 14 All 14 (JSON)
- 2026Spatiotemporal Proximal Causal Inference under Hidden Confounding and Interference2 Aug 2026
- 2026Shrinkage priors for Bayesian Substitute Confounders16 Jun 2026
- 2024What is Fair? Defining Fairness in Machine Learning for Health13 Jun 2024
- 2024Synthetic Potential Outcomes and Causal Mixture Identifiability29 May 2024
- 2024Automating the Selection of Proxy Variables of Unmeasured Confounders25 May 2024
- 2023Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data16 Oct 2023
- 2023Scalable Computation of Causal Bounds4 Aug 2023
- 2023Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders4 Mar 2023
- 2022Estimating Social Influence from Observational Data24 Mar 2022
- 2021Causal Inference Despite Limited Global Confounding via Mixture Models22 Dec 2021
- 2021Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies19 Dec 2021
- 2021Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication4 Oct 2021
12 newest of 14 All 14 (JSON)