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

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.

Getting started

Package details

AuthorLiangyuan Hu [aut], Jiayi Ji [aut, cre]
MaintainerJiayi Ji <jj869@sph.rutgers.edu>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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riAFTBART documentation built on May 17, 2022, 1:07 a.m.