3 papers
stat.ME2026
Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world data
Tijn Jacobs, Stéphanie L. van der Pas, Wessel N. van Wieringen
We develop the Bayesian fusion forest, a nonparametric framework to estimate heterogeneous treatment effects on survival outcomes by combining a randomised controlled trial and rea…
stat.ME2026
ShrinkageTrees: An R Package for Bayesian Tree Ensembles for Survival Analysis and Causal Inference
Tijn Jacobs
ShrinkageTrees is an R package for Bayesian tree ensembles in survival analysis and causal inference. The package implements Bayesian additive regression tree models for right- and…
stat.ME2026
Horseshoe Forests for High-Dimensional Causal Survival Analysis
Tijn Jacobs, Wessel N. van Wieringen, Stéphanie L. van der Pas
We develop a Bayesian tree ensemble model to estimate heterogeneous treatment effects in censored survival data with high-dimensional covariates. Instead of imposing sparsity throu…