Incorporating external data into the analysis of clinical trials via Bayesian additive regression trees

DOI10.1002/sim.9191zbMATH Open1546.62929MaRDI QIDQ6628191

Tianjian Zhou, Yuan Ji

Publication date: 29 October 2024

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

zbMATH Keywords

Bayesian methodtreatment effectreal-world datahistorical controlborrow information

Mathematics Subject Classification ID

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

Cites Work

• Unnamed Item
• BART: Bayesian additive regression trees
• Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy
• Bayesian regression tree models for causal inference: regularization, confounding, and heterogeneous effects (with discussion)
• Posterior concentration for Bayesian regression trees and forests
• Commensurate priors for incorporating historical information in clinical trials using general and generalized linear models
• Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials
• Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods
• A Semiparametric Bayesian Approach to Dropout in Longitudinal Studies With Auxiliary Covariates
• Robust meta‐analytic‐predictive priors in clinical trials with historical control information
• On Optimality Properties of the Power Prior
• Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
• Bayesian Regression Tree Ensembles that Adapt to Smoothness and Sparsity
• Bayesian Regression Trees for High-Dimensional Prediction and Variable Selection
• Random forests
• The relationship between the power prior and hierarchical models

This page was built for publication: Incorporating external data into the analysis of clinical trials via Bayesian additive regression trees