Adjustment for Missing Confounders Using External Validation Data and Propensity Scores

DOI10.1080/01621459.2011.643739zbMath1328.62031OpenAlexW1995878244WikidataQ60373070 ScholiaQ60373070MaRDI QIDQ4916437

Sylvia Richardson, Lawrence C. McCandless, Nicky G. Best

Publication date: 22 April 2013

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

Full work available at URL: https://doi.org/10.1080/01621459.2011.643739

zbMATH Keywords

biasobservational studiesBayesian inferencecausal inference

Mathematics Subject Classification ID

Bayesian inference (62F15)

Related Items (6)

The Central Role of Bayes’ Theorem for Joint Estimation of Causal Effects and Propensity Scores ⋮ Adjusting for unmeasured confounding in survival causal effect using validation data ⋮ Variational inference for cutting feedback in misspecified models ⋮ Combining Multiple Observational Data Sources to Estimate Causal Effects ⋮ Approximate Bayesian inference for doubly robust estimation ⋮ Model Feedback in Bayesian Propensity Score Estimation

Uses Software

• BayesDA

Cites Work

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• Multiple-Bias Modelling for Analysis of Observational Data
• The central role of the propensity score in observational studies for causal effects
• Matching Using Estimated Propensity Scores: Relating Theory to Practice
• A Pseudoscore Estimator for Regression Problems With Two-Phase Sampling
• Flexible Maximum Likelihood Methods for Assessing Joint Effects in Case- Control Studies with Complex Sampling
• Multiple imputation of discrete and continuous data by fully conditional specification

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