A practical introduction to Bayesian estimation of causal effects: parametric and nonparametric approaches

DOI10.1002/SIM.8761zbMATH Open1546.62567MaRDI QIDQ6627906

Jason A. Roy, [[Person:6047795|Author name not available (Why is that?)]]

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

BARTGaussian processDirichlet processBayesianconfoundingcausal inferenceBayesian nonparametricg-computation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Title not available (Why is that?)
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• BART: Bayesian additive regression trees
• Identification, inference and sensitivity analysis for causal mediation effects
• Bayesian inference for causal effects: The role of randomization
• An introduction to MCMC for machine learning
• Causal inference: a missing data perspective
• A semiparametric modeling approach using Bayesian additive regression trees with an application to evaluate heterogeneous treatment effects
• Estimating population average causal effects in the presence of non-overlap: the effect of natural gas compressor station exposure on cancer mortality
• Semiparametric Bayes hierarchical models with mean and variance constraints
• Bayesian inference in partially identified models: is the shape of the posterior distribution useful?
• An enriched conjugate prior for Bayesian nonparametric inference
• Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models
• Simplified Bayesian Sensitivity Analysis for Mismeasured and Unobserved Confounders
• Principal Stratification in Causal Inference
• The Estimation of Causal Effects by Difference-in-Difference MethodsEstimation of Spatial Panels
• A Bayesian Semiparametric Approach to Intermediate Variables in Causal Inference
• Estimating causal effects of air quality regulations using principal stratification for spatially correlated multivariate intermediate outcomes
• The horseshoe estimator for sparse signals
• Toward Causal Inference With Interference
• Estimating Optimal Transformations for Multiple Regression and Correlation
• A Bayesian Machine Learning Approach for Optimizing Dynamic Treatment Regimes
• A Bayesian nonparametric approach to causal inference on quantiles
• A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
• Penalized Spline of Propensity Methods for Treatment Comparison
• A framework for Bayesian nonparametric inference for causal effects of mediation

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