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BayesOrdDesign
View on CRAN: Click
here
Download and install BayesOrdDesign package within the R console
Install from CRAN:
install.packages("BayesOrdDesign")
Install from Github:
library("remotes")
install_github("cran/BayesOrdDesign") Install by package version:
library("remotes")
install_version("BayesOrdDesign", "0.1.2") Attach the package and use:
library("BayesOrdDesign")
Maintained by
Chengxue Zhong
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-21
Latest Update:
Description:
The proposed group-sequential trial design is based on Bayesian methods for ordinal endpoints,
including three methods, the proportional-odds-model (PO)-based, non-proportional-odds-model (NPO)-based,
and PO/NPO switch-model-based designs, which makes our proposed methods generic to be able to deal with
various scenarios.
Richard J. Barker, William A. Link (2013) .
Thomas A. Murray, Ying Yuan, Peter F. Thall, Joan H. Elizondo, Wayne L.Hofstetter (2018) .
Chengxue Zhong, Haitao Pan, Hongyu Miao (2021) .
How to cite:
Chengxue Zhong (2021). BayesOrdDesign: Bayesian Group Sequential Design for Ordinal Data. R package version 0.1.2, https://cran.r-project.org/web/packages/BayesOrdDesign. Accessed 05 Aug. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for BayesOrdDesign
Functions, R codes and Examples using
the BayesOrdDesign R package
Some associated functions: Bayes_ord . example.data . get_oc_NPO . get_oc_PO . get_oc_Switch . rjmcmc_func . ss_npo . ss_po . ss_switch .
Some associated R codes: Bayes_Ord_Design_NPO.R . Bayes_Ord_Design_PO.R . Bayes_Ord_Design_Switch.R . Bayes_ord.R . OC_func_NPO.R . OC_func_PO.R . OC_func_Switch.R . data.R . data_generator_npo.R . data_simulator.R . funcs.R . jags_npo.R . jags_po.R . packages.R . rjmcmc.R . rjmcmc_internal.R . utility_function.R . Full BayesOrdDesign package functions and examples
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