Package: bayesDP 1.3.7

bayesDP: Implementation of the Bayesian Discount Prior Approach for Clinical Trials

Functions for data augmentation using the Bayesian discount prior method for single arm and two-arm clinical trials, as described in Haddad et al. (2017) <doi:10.1080/10543406.2017.1300907>. The discount power prior methodology was developed in collaboration with the The Medical Device Innovation Consortium (MDIC) Computer Modeling & Simulation Working Group.

Authors:Shawn Balcome [aut], Donnie Musgrove [aut], Tarek Haddad [aut], Graeme L. Hickey [cre, aut], Christopher Jackson [ctb]

bayesDP_1.3.7.tar.gz
bayesDP_1.3.7.zip(r-4.7)bayesDP_1.3.7.zip(r-4.6)bayesDP_1.3.7.zip(r-4.5)
bayesDP_1.3.7.tgz(r-4.6-x86_64)bayesDP_1.3.7.tgz(r-4.6-arm64)bayesDP_1.3.7.tgz(r-4.5-x86_64)bayesDP_1.3.7.tgz(r-4.5-arm64)
bayesDP_1.3.7.tar.gz(r-4.7-arm64)bayesDP_1.3.7.tar.gz(r-4.7-x86_64)bayesDP_1.3.7.tar.gz(r-4.6-arm64)bayesDP_1.3.7.tar.gz(r-4.6-x86_64)
bayesDP_1.3.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
bayesDP/json (API)
NEWS

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

Bug tracker:https://github.com/graemeleehickey/bayesdp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

bayesianbayesian-inferencebayesian-statisticsclinical-trialsmdicposterior-predictiveposterior-probabilityprior-distributionopenblascpp

5.19 score 26 scripts 408 downloads 1 mentions 11 exports 29 dependencies

Last updated from:4592804d86. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK166
linux-devel-x86_64OK179
source / vignettesOK216
linux-release-arm64OK198
linux-release-x86_64OK169
macos-release-arm64OK119
macos-release-x86_64OK234
macos-oldrel-arm64OK112
macos-oldrel-x86_64OK337
windows-develOK117
windows-releaseOK154
windows-oldrelOK177
wasm-releaseOK131

Exports:alpha_discountbdpbinomialbdplmbdplogitbdpnormalbdpsurvivalplotppexpprintprobability_discountsummary

Dependencies:clicodacpp11farverggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixMatrixModelsmcmcMCMCpackquantregR6RColorBrewerRcppRcppArmadillorlangS7scalesSparseMsurvivalvctrsviridisLitewithr

BayesDP

Rendered frombdpbinomial-vignette.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2018-04-10
Started: 2017-04-14

BayesDP

Rendered frombdplm-vignette.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2018-07-09
Started: 2017-08-23

BayesDP

Rendered frombdpnormal-vignette.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2018-04-10
Started: 2017-04-14

BayesDP

Rendered frombdpsurvival-vignette.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2018-04-10
Started: 2017-04-14

Readme and manuals

Help Manual

Help pageTopics
Bayesian Discount Prior: Historical Data Weight (alpha)alpha_discount alpha_discount,ANY-method
Bayesian Discount Prior: Binomial countsbdpbinomial bdpbinomial,ANY-method bdpbinomial-method
Bayesian Discount Prior: Two-Arm Linear Regressionbdplm bdplm,ANY-method bdplm-method
Bayesian Discount Prior: Two-Arm Logistic Regressionbdplogit bdplogit,ANY-method bdplogit-method
Bayesian Discount Prior: Gaussian mean valuesbdpnormal bdpnormal,ANY-method bdpnormal-method
Bayesian Discount Prior: Survival Analysisbdpsurvival bdpsurvival,ANY-method bdpsurvival-method
bdpbinomial Object Plotplot,bdpbinomial-method
bdpnormal Object Plotplot,bdpnormal-method
bdpsurvival Object Plotplot,bdpsurvival-method
Compute cdf of the piecewise exponential distributionppexp
bdpbinomial Object Printprint,bdpbinomial-method
bdplm Object Printprint,bdplm-method
bdpnormal Object Printprint,bdpnormal-method
bdpsurvival Object Printprint,bdpsurvival-method
Bayesian Discount Prior: Comparison Between Current and Historical Dataprobability_discount probability_discount,ANY-method
bdpbinomial Object Summarysummary,bdpbinomial-method
bdplm Object Summarysummary,bdplm-method
bdpnormal Object Summarysummary,bdpnormal-method
bdpsurvival Object Summarysummary,bdpsurvival-method