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bayesCT
View on CRAN: Click
here
Download and install bayesCT package within the R console
Install from CRAN:
install.packages("bayesCT")
Install from Github:
library("remotes")
install_github("cran/bayesCT")
Install by package version:
library("remotes")
install_version("bayesCT", "0.99.3")
Attach the package and use:
library("bayesCT")
Maintained by
Thevaa Chandereng
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-01-30
Latest Update: 2020-07-01
Description:
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.
How to cite:
Thevaa Chandereng (2019). bayesCT: Simulation and Analysis of Adaptive Bayesian Clinical Trials. R package version 0.99.3, https://cran.r-project.org/web/packages/bayesCT. Accessed 22 Dec. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for bayesCT
Functions, R codes and Examples using
the bayesCT R package
Some associated functions: analysis . beta_prior . binomialBACT . binomial_analysis . binomial_outcome . binomialdata . data_binomial . data_normal . data_survival . enrollment . enrollment_rate . gamma_prior . historical_binomial . historical_normal . historical_survival . hypothesis . impute . normalBACT . normal_analysis . normal_outcome . normaldata . pipe . pw_exp_impute . pw_exp_sim . randomization . randomize . simulate . study_details . survivalBACT . survival_analysis . survival_outcome . survivaldata .
Some associated R codes: analysis.R . binomial.R . binomialdata.R . enrollment.R . normal.R . normaldata.R . pw_exp.R . randomization.R . simulate.R . survival.R . survivaldata.R . utils.R . wrapper.R . Full bayesCT package functions and examples
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