Comment: Reflections on the Deconfounder

DOI10.1080/01621459.2019.1689138zbMath1428.62056arXiv1910.08042OpenAlexW2998143050WikidataQ126395856 ScholiaQ126395856MaRDI QIDQ5208063

Alexander D'Amour

Publication date: 15 January 2020

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.08042

zbMATH Keywords

causal inferenceunobserved confoundingunconfoundedness

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Causal inference from observational studies (62D20)

Related Items (1)

Identifying Effects of Multiple Treatments in the Presence of Unmeasured Confounding

Uses Software

• GeneralisedCovarianceMeasure

Cites Work

• Unnamed Item
• The Hardness of Conditional Independence Testing and the Generalised Covariance Measure
• Bayesian robust inference of sample selection using selection-\(t\) models
• When is a sensitivity parameter exactly that?
• Split-door criterion: identification of causal effects through auxiliary outcomes
• Bayesian approaches for missing not at random outcome data: the role of identifying restrictions
• Sample Selection Bias as a Specification Error
• Identifying causal effects with proxy variables of an unmeasured confounder
• Making Sense of Sensitivity: Extending Omitted Variable Bias
• Flexible Sensitivity Analysis for Observational Studies Without Observable Implications
• Bias attenuation results for nondifferentially mismeasured ordinal and coarsened confounders

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