A New Criterion for Confounder Selection
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Publication:2893399
DOI10.1111/J.1541-0420.2011.01619.XzbMath1274.62890OpenAlexW2025309870WikidataQ38295854 ScholiaQ38295854MaRDI QIDQ2893399
Tyler J. Vanderweele, Ilya Shpitser
Publication date: 20 June 2012
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc3166439
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Cites Work
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- Bayesian inference for causal effects: The role of randomization
- Ancestral graph Markov models.
- The central role of the propensity score in observational studies for causal effects
- Causal diagrams for empirical research
- Some Surprising Results about Covariate Adjustment in Logistic Regression Models
- Independence properties of directed markov fields
- Influence Diagrams for Causal Modelling and Inference
- Identifying independence in bayesian networks
- Large Sample Properties of Matching Estimators for Average Treatment Effects
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