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riAFTBART

A Flexible Approach for Causal Inference with Multiple Treatments and Clustered Survival Outcomes

v0.3.3 · May 29, 2024 · MIT + file LICENSE

Description

Random-intercept accelerated failure time (AFT) model utilizing Bayesian additive regression trees (BART) for drawing causal inferences about multiple treatments while accounting for the multilevel survival data structure. It also includes an interpretable sensitivity analysis approach to evaluate how the drawn causal conclusions might be altered in response to the potential magnitude of departure from the no unmeasured confounding assumption.This package implements the methods described by Hu et al. (2022) <doi:10.1002/sim.9548>.

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r-devel-macos-arm64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies MCMCpack msm dbarts magrittr foreach doParallel dplyr BART stringr tidyr survival cowplot ggplot2 twang nnet +2 more dependencies riAFTBART

Version History

new 0.3.3 Mar 10, 2026
updated 0.3.3 ← 0.3.2 diff May 29, 2024
updated 0.3.2 ← 0.3.1 diff May 16, 2022
updated 0.3.1 ← 0.3.0 diff May 15, 2022
updated 0.3.0 ← 0.2.0 diff Apr 9, 2022
updated 0.2.0 ← 0.1.0 diff Feb 14, 2022
new 0.1.0 Feb 8, 2022