Estimating population average causal effects in the presence of non-overlap: the effect of natural gas compressor station exposure on cancer mortality

DOI10.1214/18-AOAS1231zbMath1423.62149arXiv1805.09736WikidataQ92187314 ScholiaQ92187314MaRDI QIDQ2318683

Fabrizia Mealli, Rachel C. Nethery, Francesca Dominici

Publication date: 15 August 2019

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1805.09736

zbMATH Keywords

overlapsplinesnatural gaspropensity scoreBayesian additive regression treescancer mortality

Mathematics Subject Classification ID

Numerical computation using splines (65D07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Applications of statistics in engineering and industry; control charts (62P30)

Related Items (2)

overlap ⋮ Estimating population average causal effects in the presence of non-overlap: the effect of natural gas compressor station exposure on cancer mortality

Uses Software

• BayesTree
• GitHub
• BartPy
• Unnamed Item

Cites Work

• Unnamed Item
• BART: Bayesian additive regression trees
• Assessing lack of common support in causal inference using Bayesian nonparametrics: Implications for evaluating the effect of breastfeeding on children's cognitive outcomes
• Bayesian regression tree models for causal inference: regularization, confounding, and heterogeneous effects (with discussion)
• Estimating population average causal effects in the presence of non-overlap: the effect of natural gas compressor station exposure on cancer mortality
• Overlap in observational studies with high-dimensional covariates
• Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models
• Dealing with limited overlap in estimation of average treatment effects
• The central role of the propensity score in observational studies for causal effects
• Bayesian Effect Estimation Accounting for Adjustment Uncertainty
• Balancing Covariates via Propensity Score Weighting
• Bayesian Regression Trees for High-Dimensional Prediction and Variable Selection
• Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores

This page was built for publication: Estimating population average causal effects in the presence of non-overlap: the effect of natural gas compressor station exposure on cancer mortality