Package: basksim 2.2.0

basksim: Simulation-Based Calculation of Basket Trial Operating Characteristics

Provides a unified syntax for the simulation-based comparison of different single-stage basket trial designs with a binary endpoint and equal sample sizes in all baskets. Methods include the designs by Baumann et al. (2025) <doi:10.1080/19466315.2024.2402275>, Schmitt and Baumann (2025) <doi:10.1080/19466315.2025.2486231>, Fujikawa et al. (2020) <doi:10.1002/bimj.201800404>, Berry et al. (2020) <doi:10.1177/1740774513497539>, and Neuenschwander et al. (2016) <doi:10.1002/pst.1730>. For the latter two designs, the functions are mostly wrappers for functions provided by the package 'bhmbasket'.

Authors:Lukas Baumann [aut, cre], Lukas D Sauer [aut], Sabrina Schmitt [aut]

basksim_2.2.0.tar.gz
basksim_2.2.0.zip(r-4.7)basksim_2.2.0.zip(r-4.6)basksim_2.2.0.zip(r-4.5)
basksim_2.2.0.tgz(r-4.6-any)basksim_2.2.0.tgz(r-4.5-any)
basksim_2.2.0.tar.gz(r-4.7-any)basksim_2.2.0.tar.gz(r-4.6-any)
basksim_2.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
basksim/json (API)

# Install 'basksim' in R:
install.packages('basksim', repos = c('https://lbau7.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lbau7/basksim/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

jagscpp

5.58 score 2 stars 2 packages 21 scripts 342 downloads 23 exports 33 dependencies

Last updated from:9598693c43. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK259
source / vignettesOK178
linux-release-x86_64OK227
macos-release-arm64OK212
macos-oldrel-arm64OK274
windows-develOK288
windows-releaseOK257
windows-oldrelOK291
wasm-releaseOK117

Exports:adjust_lambdaecdgeom_borrowgeom_posteriorgeom_priorget_dataget_detailsget_evaluationget_resultsget_scenariosopt_designsetup_appsetup_bhmsetup_binomialsetup_cppsetup_cppglobalsetup_cpplimsetup_exnexsetup_fujikawasetup_jsdglobalsetup_mmlsetup_mmlglobaltoer

Dependencies:arrangementsbackportsbhmbasketcheckmateclicodacodetoolsdigestdoFuturedoRNGextraDistrforeachfuturefuture.applyglobalsgluegmpHDIntervaliteratorslatticelifecyclelistenvmagrittrparallellyprogressrpurrrR6RcppRcppArmadillorjagsrlangrngtoolsvctrs

Readme and manuals

Help Manual

Help pageTopics
Adjust Lambdaadjust_lambda
Adjust Lambda for the BHM Designadjust_lambda.bhm
Adjust Lambdaadjust_lambda.default
Adjust Lambda for the EXNEX Designadjust_lambda.exnex
Calculate the Expected Number of Correct Decisions for a Basket Trial Designecd
Plot a Bayesian basket trial's posterior distribution after borrowinggeom_borrow
Plot a Fujikawa basket trial's posterior distribution after borrowinggeom_borrow.fujikawa
Plot a Bayesian basket trial's posterior distributiongeom_posterior
Plot a Fujikawa basket trial's posterior distributiongeom_posterior.fujikawa
Plot a Bayesian basket trial's prior distributiongeom_prior
Plot a Fujikawa basket trial's prior distributiongeom_prior.fujikawa
Simulate Data Based on a Binomial Distributionget_data
Get Details of a Basket Trial Simulationget_details
Get Details of a Basket Trial Simulation with the Adaptive Power Prior Design for sequential clinical trialsget_details.app
Get Details of a BHM Basket Trial Simulationget_details.bhm
Get Details of a Basket Trial with the Frequentist Binomial Designget_details.binomial
Get Details of a Basket Trial Simulation with the Calibrated Power Prior Designget_details.cpp
Get Details of a Basket Trial Simulation with the Global Calibrated Power Prior Designget_details.cppglobal
Get Details of a Basket Trial Simulation with the Limited Calibrated Power Prior Designget_details.cpplim
Get Details of a Basket Trial Simulation with the EXNEX Designget_details.exnex
Get Details of a Basket Trial Simulation with Fujikawa's Designget_details.fujikawa
Get Details of a Basket Trial Simulation with the Power Prior Design Based on Global JSD Weightsget_details.jsdglobal
Get Details of a Basket Trial Simulation with the MML Designget_details.mml
Get Details of a Basket Trial Simulation with the Global MML Designget_details.mmlglobal
Evaluate a Basket Trialget_evaluation
Evaluate a Basket Trial with the Adaptive Power Prior Design for sequential clinical trialsget_evaluation.app
Evaluate a BHM Basket Trialget_evaluation.bhm
Evaluate a Basket Trial with the Calibrated Power Prior Designget_evaluation.cpp
Evaluate a Basket Trial with the Limited Calibrated Power Prior Designget_evaluation.cpplim
Evaluate a Basket Trial with the EXNEX Designget_evaluation.exnex
Evaluate a Basket Trial with Fujikawa's Designget_evaluation.fujikawa
Get Results for Simulation of Basket Trial Designsget_results
Get Results for Simulation of a Basket Trial with Adaptive Power Prior Designget_results.app
Get Results for Simulation of a Basket Trial with the BHM Designget_results.bhm
Get Results for Simulation of a Basket Trial with a Calibrated Power Prior Designget_results.cpp
Get Results for Simulation of a Basket Trial with a Global Calibrated Power Prior Designget_results.cppglobal
Get Results for Simulation of a Basket Trial with a Limited Calibrated Power Prior Designget_results.cpplim
Get Results for Simulation of a Basket Trial with the EXNEX Designget_results.exnex
Get Results for Simulation of a Basket Trial with Fujikawa's Designget_results.fujikawa
Get Results for Simulation of a Basket Trial with the Power Prior Design Based on Global JSD Weightsget_results.jsdglobal
Get Results for Simulation of a Basket Trial with the MML Designget_results.mml
Get Results for Simulation of a Basket Trial with the Global MML Designget_results.mmlglobal
Create a Scenario Matrixget_scenarios
Optimize a Basket Trial Designopt_design
Set Up Adaptive Power Prior Design Objectsetup_app
Set Up BHM Design Objectsetup_bhm
Set Up Frequentist Binomial Design Objectsetup_binomial
Set Up Calibrated Power Prior Design Objectsetup_cpp
Set Up Global Calibrated Power Prior Design Objectsetup_cppglobal
Set Up Limited Calibrated Power Prior Design Objectsetup_cpplim
Set Up EXNEX Design Objectsetup_exnex
Set Up Fujikawa Design Objectsetup_fujikawa
Set Up Global JSD Design Objectsetup_jsdglobal
Set Up mml Design Objectsetup_mml
Set Up mmlglobal Design Objectsetup_mmlglobal
Calculate the Type 1 Error Rate for a Basket Trial Designtoer