The role of exchangeability in causal inference
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Publication:6181740
DOI10.1214/22-sts879arXiv2006.01799OpenAlexW3033114400WikidataQ130416003 ScholiaQ130416003MaRDI QIDQ6181740
David A. Stephens, Olli Saarela, Erica E. M. Moodie
Publication date: 23 January 2024
Published in: Statistical Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.01799
Cites Work
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- Standardization and control for confounding in observational studies: a historical perspective
- The stochastic system approach for estimating dynamic treatments effect
- Analysis of treatment response data without the joint distribution of potential outcomes
- From statistical evidence to evidence of causality
- A martingale approach to continuous-time marginal structural models
- Some models and methods for the analysis of observational data
- The role of exchangeability in inference
- Bayesian inference for causal effects: The role of randomization
- Confounding and collapsibility in causal inference
- Identifying the consequences of dynamic treatment strategies: a decision-theoretic overview
- Invariance, causality and robustness
- Symmetric Measures on Cartesian Products
- On Bayesian estimation of marginal structural models
- The central role of the propensity score in observational studies for causal effects
- Statistics and Causal Inference
- Asymptotic Statistics
- Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments
- Causal Inference Without Counterfactuals
- Causal Reasoning from Longitudinal Data*
- Seeing and Doing: the Concept of Causation
- On model selection and model misspecification in causal inference
- A Bayesian view of doubly robust causal inference: Table 1.
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