Package: BayesPET 0.1.0

Xinyi He

BayesPET: Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials

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>.

Authors:Xinyi He [cre, aut], Jingyan Fu [aut], Ying Yuan [aut, cph]

BayesPET_0.1.0.tar.gz
BayesPET_0.1.0.tar.gz(r-4.7-arm64)BayesPET_0.1.0.tar.gz(r-4.7-x86_64)BayesPET_0.1.0.tar.gz(r-4.6-arm64)BayesPET_0.1.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
BayesPET/json (API)

# Install 'BayesPET' in R:

install.packages('BayesPET', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

data_example - Example trial datasets for fitting Stan models and predicting event times

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.00 score 239 downloads 9 exports 73 dependencies

Last updated from:45fb8b3491. Checks:5 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	489
linux-devel-x86_64	OK	575
source / vignettes	OK	472
linux-release-arm64	OK	487
linux-release-x86_64	OK	438
wasm-release	FAIL	189

Exports:convert_median fit_censor fit_enroll fit_event_blind fit_event_unblind fit_models generate_data get_oc predict_eventtime

Dependencies:abind backports BH bit bit64 callr checkmate cli clipr codetools cpp11 crayon desc digest distributional dplyr farver furrr future generics ggplot2 globals glue gridExtra gtable hms inline isoband labeling lifecycle listenv loo magrittr matrixStats numDeriv otel parallelly pillar pkgbuild pkgconfig plyr posterior prettyunits processx progress ps purrr QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel readr reshape2 rlang rstan rstantools S7 scales StanHeaders stringi stringr tensorA tibble tidyr tidyselect tzdb utf8 vctrs viridisLite vroom withr

Help page	Topics
BayesPET: Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials	BayesPET-package BayesPET
Solve baseline survival parameters by matching the marginal median survival time	convert_median
Example trial datasets for fitting Stan models and predicting event times	data_example
Fit a Weibull model for random censoring times	fit_censor
Fit enrollment model	fit_enroll
Fit a Weibull event-time model with unknown treatment assignments	fit_event_blind
Fit a Weibull event-time model with known treatment assignments	fit_event_unblind
Fit enrollment, event-time, and censoring models to clinical trial data and return posterior draws model parameters	fit_models
Generate two-arm trial data with enrollment, event, and censoring processes, and return data formatted for event-time prediction.	generate_data
Generate operating characteristics for event prediction	get_oc
Plot method for BayesPET prediction objects	plot.BayesPET_predtime
Predict the calendar time at which a target number of events is reached from interim analysis data	predict_eventtime
Print method for BayesPET model fitting objects	print.BayesPET_fit
Print method for BayesPET prediction objects	print.BayesPET_predtime
Summary method for BayesPET operating characteristics object	print.summary.BayesPET_oc summary.BayesPET_oc
Summary method for BayesPET prediction objects	print.summary.BayesPET_predtime summary.BayesPET_predtime

Package: BayesPET 0.1.0

BayesPET: Bayesian Prediction of Event Times for Blinded Randomized Controlled Trials

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)