Package: bayprior 0.2.12

Ndoh Penn

bayprior: Bayesian Prior Elicitation and Diagnostics for Clinical Trials

A toolkit for constructing, validating, and justifying Bayesian priors in clinical trial settings. Implements expert elicitation via quantile matching, the roulette method, and moment matching across six distribution families, linear and logarithmic expert pooling, prior-data conflict diagnostics including the Box p-value, surprise index, information divergence, and Mahalanobis distance, sensitivity analyses with tornado and influence heatmap plots, sceptical, robust, and power priors, and automated prior justification reports. Includes a fully modular 'Shiny' application for interactive use. Methods based on O'Hagan et al. (2006, ISBN:9780470029886), Box (1980) <doi:10.2307/2982063>, Oakley and O'Hagan (2010) <https://tonyohagan.co.uk/shelf/>, Schmidli et al. (2014) <doi:10.1111/biom.12242>, Ibrahim and Chen (2000) <doi:10.1214/ss/1009212673>, Spiegelhalter et al. (1994) <doi:10.2307/2983527>.

Authors:Ndoh Penn [aut, cre]

bayprior_0.2.12.tar.gz
bayprior_0.2.12.tar.gz(r-4.7-any)bayprior_0.2.12.tar.gz(r-4.6-any)
bayprior_0.2.12.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
bayprior/json (API)
NEWS

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

Bug tracker:https://github.com/ndohpenngit/bayprior/issues

On CRAN:

Conda:

3.48 score 22 exports 79 dependencies

Last updated from:ca3749ef57. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK161
source / vignettesOK236
linux-release-x86_64OK153
wasm-releaseOK137

Exports:aggregate_expertsas_priorcalibrate_power_priorconflict_mahalanobiselicit_betaelicit_exponentialelicit_gammaelicit_lognormalelicit_mixtureelicit_normalelicit_rouletteelicit_weibullplot_prior_likelihoodplot_sensitivityplot_tornadoprior_conflictprior_reportrobust_priorrun_appsceptical_priorsensitivity_crisensitivity_grid

Dependencies:askpassattemptbase64encbslibcachemclicommonmarkconfigcpp11crosstalkcurldata.tabledigestdplyrDTevaluatefarverfastmapfontawesomefsgenericsggplot2gluegolemgtableherehighrhtmltoolshtmlwidgetshttpuvhttrisobandjquerylibjsonliteknitrlabelinglaterlazyevallifecyclemagrittrmemoisemimeopensslotelpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownrprojrootS7sassscalesshinyshinycssloadersshinydashboardshinyjsshinyWidgetssourcetoolsstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxtableyaml

Introduction to bayprior

Rendered frombayprior-introduction.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2026-06-03
Started: 2026-06-03

Prior Elicitation Methods

Rendered fromprior-elicitation.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2026-06-03
Started: 2026-06-03

Prior-Data Conflict Diagnostics

Rendered fromconflict-diagnostics.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2026-06-03
Started: 2026-06-03

Regulatory Reporting

Rendered fromregulatory-reporting.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2026-06-03
Started: 2026-06-03

Robust, Sceptical, and Power Priors

Rendered fromrobust-priors.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2026-06-03
Started: 2026-06-03

Sensitivity Analysis

Rendered fromsensitivity-analysis.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2026-06-03
Started: 2026-06-03

Readme and manuals

Help Manual

Help pageTopics
Aggregate multiple expert priors into a consensus prioraggregate_experts
Constructor for bayprior from raw parametersas_prior
bayprior: Bayesian Prior Elicitation for Clinical Trialsbayprior-package bayprior
Calibrate power prior weight via Bayes Factorcalibrate_power_prior
Multivariate prior-data conflict via Mahalanobis distanceconflict_mahalanobis
Elicit a Beta prior via quantile matching or moment matchingelicit_beta
Elicit an Exponential prior via moments, rate, or quantile matchingelicit_exponential
Elicit a Gamma prior via quantile matching or moment matchingelicit_gamma
Elicit a Log-Normal prior via quantile matching or moment matchingelicit_lognormal
Elicit a mixture priorelicit_mixture
Elicit a Normal prior via quantile matching or moment matchingelicit_normal
Roulette-method elicitation (chip-allocation)elicit_roulette
Elicit a Weibull prior via moments, direct parameters, or quantile matchingelicit_weibull
Plot prior, likelihood, and posterior density overlaysplot_prior_likelihood
Plot sensitivity analysis resultsplot_sensitivity
Tornado plot of prior influence on posterior quantitiesplot_tornado
Plot calibration curve for power prior weight selectionplot.bayprior_power_prior
Print method for bayprior objectsprint.bayprior
Print method for bayprior_conflict objectsprint.bayprior_conflict
Print method for multivariate conflict objectsprint.bayprior_conflict_mv
Print method for bayprior_power_prior objectsprint.bayprior_power_prior
Compute prior-data conflict diagnosticsprior_conflict
Generate a Prior Justification Reportprior_report
Construct a robust (heavy-tailed mixture) priorrobust_prior
Run the bayprior Shiny Applicationrun_app
Construct a sceptical (penalised-enthusiasm) priorsceptical_prior
Sensitivity of posterior CrI to prior hyperparameterssensitivity_cri
Sensitivity grid over prior hyperparameterssensitivity_grid
Summary method for bayprior objectssummary.bayprior