Package: bayesCT 0.99.3

Thevaa Chandereng

bayesCT: Simulation and Analysis of Adaptive Bayesian Clinical Trials

Simulation and analysis of Bayesian adaptive clinical trials for binomial, Gaussian, and time-to-event data types, incorporates historical data and allows early stopping for futility or early success. The package uses novel and efficient Monte Carlo methods for estimating Bayesian posterior probabilities, evaluation of loss to follow up, and imputation of incomplete data. The package has the functionality for dynamically incorporating historical data into the analysis via the power prior or non-informative priors.

Authors:Thevaa Chandereng [aut, cre, cph], Donald Musgrove [aut, cph], Tarek Haddad [aut, cph], Graeme Hickey [aut, cph], Timothy Hanson [aut, cph], Theodore Lystig [aut, cph]

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bayesCT.pdf |bayesCT.html✨
bayesCT/json (API)

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

Bug tracker:https://github.com/thevaachandereng/bayesct/issues

Datasets:
  • binomialdata - Binomial dataset for analyzing adaptive Bayesian trials
  • normaldata - Gaussian dataset for analyzing adaptive Bayesian trials
  • survivaldata - Time-to-event dataset for analyzing adaptive Bayesian trials

On CRAN:

Conda:

archivedpackagesr-universe

4.00 score 5 stars 270 downloads 29 exports 42 dependencies

Last updated 1 days agofrom:e9d2726795 (on package/bayesCT). Checks:6 OK, 3 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-winNOTEApr 01 2025
R-4.5-macNOTEApr 01 2025
R-4.5-linuxNOTEApr 01 2025
R-4.4-winOKApr 01 2025
R-4.4-macOKApr 01 2025
R-4.4-linuxOKApr 01 2025
R-4.3-winOKApr 01 2025
R-4.3-macOKApr 01 2025

Exports:%>%analysisbeta_priorbinomial_analysisbinomial_outcomebinomialBACTdata_binomialdata_normaldata_survivalenrollmentenrollment_rategamma_priorhistorical_binomialhistorical_normalhistorical_survivalhypothesisimputenormal_analysisnormal_outcomenormalBACTpw_exp_imputepw_exp_simrandomizationrandomizesimulatestudy_detailssurvival_analysissurvival_outcomesurvivalBACT

Dependencies:bayesDPclicodacolorspacedplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmgcvmunsellnlmepillarpkgconfigpurrrquantregR6RColorBrewerRcppRcppArmadillorlangscalesSparseMsurvivaltibbletidyselectutf8vctrsviridisLitewithr

Binomial Outcome

Thevaa Chandereng, Donald Musgrove, Tarek Haddad, Graeme Hickey, Timothy Hanson, Theodore Lystig

Rendered frombinomial.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2025-04-01
Started: 2025-04-01

Normal Outcome

Thevaa Chandereng, Donald Musgrove, Tarek Haddad, Graeme Hickey, Timothy Hanson, Theodore Lystig

Rendered fromnormal.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2025-04-01
Started: 2025-04-01

Time-to-Event Outcome

Thevaa Chandereng, Donald Musgrove, Tarek Haddad, Graeme Hickey, Timothy Hanson, Theodore Lystig

Rendered fromtime-to-event.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2025-04-01
Started: 2025-04-01

bayesCT: An R package for Simulation in Adaptive Bayesian Clinical Trials

Thevaa Chandereng, Donald Musgrove, Tarek Haddad, Graeme Hickey, Timothy Hanson, Theodore Lystig

Rendered frombayesCT.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2025-04-01
Started: 2025-04-01

Readme and manuals

Help Manual

Help pageTopics
Analysis wrapper functionanalysis
Beta prior for for control and treatment groupbeta_prior
Analyzing Bayesian trial for binomial countsbinomial_analysis
Proportion of an event in control and treatmentbinomial_outcome
Binomial counts for Bayesian Adaptive TrialsbinomialBACT
Binomial dataset for analyzing adaptive Bayesian trialsbinomialdata
Data file for binomial analysisdata_binomial
Data file for normal analysisdata_normal
Data file for survival analysisdata_survival
Simulating enrollment datesenrollment
Enrollment rate wrapperenrollment_rate
Gamma prior for for control and treatment groupgamma_prior
Historical data for binomial distributionhistorical_binomial
Historical data for normal distributionhistorical_normal
Historical data for survival analysishistorical_survival
Hypothesis wrapperhypothesis
Imputation wrapperimpute
Analyzing Bayesian trial for normal mean datanormal_analysis
Parameters for treatment and control in normal casenormal_outcome
Normal distribution for Bayesian Adaptive TrialsnormalBACT
Gaussian dataset for analyzing adaptive Bayesian trialsnormaldata
Imputes time-to-event outcomes.pw_exp_impute
Simulates time-to-event outcomes.pw_exp_sim
Randomization allocationrandomization
Randomization scheme wrapperrandomize
Simulation wrapper for binomial and normal.simulate
Details of the clinical studystudy_details
Analyzing Bayesian trial for time-to-event datasurvival_analysis
Piecewise constant hazard rates and the cutpoint for control and treatment groupsurvival_outcome
Time-to-event outcome for Bayesian Adaptive TrialssurvivalBACT
Time-to-event dataset for analyzing adaptive Bayesian trialssurvivaldata