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BayesPET

0.1.0

Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials

0packages depend
1.7Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Xinyi HeFirst published 2026-02-121 releasesCRAN page ↗

Bayesian methods for predicting the calendar time at which a target number of events is reached in clinical trials. The methodology applies to both blinded and unblinded settings and jointly models enrollment, event-time, and censoring processes. The package provides tools for trial data simulation, model fitting using 'Stan' via the 'rstan' interface, and event time prediction under a wide range of trial designs, including varying sample sizes, enrollment patterns, treatment effects, and event or censoring time distributions. The package is intended to support interim monitoring, operational planning, and decision-making in clinical trial development. Methods are described in Fu et al. (2025) doi:10.1002/sim.70310.

Install

Health

CRAN checks
13OK
Slowest check: 22.0 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
13
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
  • OK2026-07-29
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-07-27
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-04-25
    12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 3 earlier snapshots
  • NOTE2026-04-22
    11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-18
    10 OK · 3 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • NOTE2026-03-10
    11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
88%
Return-value docs
100%
References docs
6%

Downloads

1.7K
CRAN downloads in the past year
Rank #12,280 · ~5/day · ~140/mo
Daily download trend is not available in this view yet.
23730 days
81190 days
1.7K1 year
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Dependencies

Declared dependencies
17 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (3)
Maintainer (1)
Maintainer, Author
Authors (3)
Maintainer, Author
Author, Copyright holder
Copyright holders (1)
Author, Copyright holder
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-02-12
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.1.0
Bundled data
6.0 KB / 1 file
Download size
93 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("BayesPET")
He, X., Fu, J., & Yuan, Y. (2026). BayesPET: Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.BayesPET

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 BayesPET 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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