Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods

DOI10.1080/10618600.2017.1356325OpenAlexW2582129089WikidataQ55261456 ScholiaQ55261456MaRDI QIDQ3391146

Daniel J. Feaster, Hemant Ishwaran, Saad Sadiq, Min Lu

Publication date: 28 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://europepmc.org/articles/pmc5920646

zbMATH Keywords

propensity scoretreatment heterogeneitycounterfactual modelindividual treatment effect (ITE)synthetic forests

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (9)

A Semiparametric Approach to Model Effect Modification ⋮ Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation ⋮ Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data ⋮ Optimal dynamic treatment regime estimation using information extraction from unstructured clinical text ⋮ Assessing the Most Vulnerable Subgroup to Type II Diabetes Associated with Statin Usage: Evidence from Electronic Health Record Data ⋮ A General Framework for Subgroup Detection via One-Step Value Difference Estimation ⋮ Efficient screening of predictive biomarkers for individual treatment selection ⋮ THE METHODS OF REGRESSION APPLIED TO THE STOCK PRICE FORECASTING ⋮ The designed bootstrap for causal inference in big observational data

Uses Software

• BayesTree
• randomSurvivalForest
• randomForestSRC
• BartPy

Cites Work

• BART: Bayesian additive regression trees
• Random survival forests
• Subsampling
• On the application of probability theory to agricultural experiments. Essay on principles. Section 9. Translated from the Polish and edited by D. M. Dąbrowska and T. P. Speed
• The central role of the propensity score in observational studies for causal effects
• Estimation of the Causal Effect of a Time-Varying Exposure on the Marginal Mean of a Repeated Binary Outcome
• Random forest missing data algorithms
• Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
• Random forests

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