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riAFTBART  

A Flexible Approach for Causal Inference with Multiple Treatments and Clustered Survival Outcomes
View on CRAN: Click here


Download and install riAFTBART package within the R console
Install from CRAN:
install.packages("riAFTBART")

Install from Github:
library("remotes")
install_github("cran/riAFTBART")

Install by package version:
library("remotes")
install_version("riAFTBART", "0.3.3")



Attach the package and use:
library("riAFTBART")
Maintained by
Fengrui Zhang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-09
Latest Update: 2022-05-16
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.
How to cite:
Fengrui Zhang (2022). riAFTBART: A Flexible Approach for Causal Inference with Multiple Treatments and Clustered Survival Outcomes. R package version 0.3.3, https://cran.r-project.org/web/packages/riAFTBART. Accessed 06 Nov. 2024.
Previous versions and publish date:
0.1.0 (2022-02-09 11:00), 0.2.0 (2022-02-15 17:10), 0.3.0 (2022-04-10 22:10), 0.3.1 (2022-05-16 09:20), 0.3.2 (2022-05-17 01:20)
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