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BayesPocket

0.1.0

Bayesian Causal Inference for Periodontal Diseases in Longitudinal Studies

0packages depend
1.2Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Qingyang LiuFirst published 2026-05-131 releasesCRAN page ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 3.1 min · r-release-macos-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
8
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-05-14
    7 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

1.2K
CRAN downloads in the past year
Rank #9,552 · ~3/day · ~98/mo
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23330 days
97690 days
1.2K1 year
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Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (4)
Maintainer (1)
Author, Maintainer
Authors (4)
Author, Maintainer
Author
Package Timeline

1 release. R releases are shown for context.

  • 0.1.0Latest
    2026-05-13 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-05-13
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.5
Download size
17 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("BayesPocket")
Liu, Q., Bandyopadhyay, D., Ni, Y., & Pati, D. (2026). BayesPocket: Bayesian Causal Inference for Periodontal Diseases in Longitudinal Studies (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.BayesPocket

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for BayesPocket version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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