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BayesPocket
View on CRAN: Click
here
Download and install BayesPocket package within the R console
Install from CRAN:
install.packages("BayesPocket")
Install from Github:
library("remotes")
install_github("cran/BayesPocket") Install by package version:
library("remotes")
install_version("BayesPocket", "0.1.0") Attach the package and use:
library("BayesPocket")
Maintained by
Qingyang Liu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-13
Latest Update: 2026-05-13
Description:
Implements the Mixed Treatment-State Causal Model (MTSCM), a Bayesian framework for estimating causal effects of clinical interventions on bounded continuous outcomes in longitudinal observational studies with irregular visits. The methodology is specifically designed for periodontal disease research, where discrete treatments and continuous disease states (e.g., proportion of periodontal pockets exceeding 3 mm) reciprocally influence one another under dynamic feedback. The package integrates a double-censored Tobit likelihood to handle boundary mass at zero and one, subject-specific random effects to capture within-subject correlation, and flexible tree-based ensemble priors (standard BART and Soft BART) to model complex nonlinear interactions without parametric restrictions. Causal identification is established under the potential outcomes framework via the G-computation formula, with key estimands including the Mixed Average Potential Outcome (MAPO) and the Mixed Probability of Disease Resolution (MPDR). The package provides functions for model fitting, posterior inference, and causal estimand estimation.
How to cite:
Qingyang Liu (2026). BayesPocket: Bayesian Causal Inference for Periodontal Diseases in Longitudinal Studies. R package version 0.1.0, https://cran.r-project.org/web/packages/BayesPocket. Accessed 24 Oct. 2026.
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