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bayprior  

Bayesian Prior Elicitation and Diagnostics for Clinical Trials
View on CRAN: Click here


Download and install bayprior package within the R console
Install from CRAN:
install.packages("bayprior")

Install from Github:
library("remotes")
install_github("cran/bayprior")

Install by package version:
library("remotes")
install_version("bayprior", "0.2.12")



Attach the package and use:
library("bayprior")
Maintained by
Ndoh Penn
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-03
Latest Update: 2026-06-03
Description:
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>.
How to cite:
Ndoh Penn (2026). bayprior: Bayesian Prior Elicitation and Diagnostics for Clinical Trials. R package version 0.2.12, https://cran.r-project.org/web/packages/bayprior. Accessed 28 Aug. 2026.
Previous versions and publish date:
(2026-08-19 16:10), 0.2.12 (2026-06-03 15:00), 0.3.0 (2026-07-30 17:20)
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Complete documentation for bayprior
Functions, R codes and Examples using the bayprior R package
Full bayprior package functions and examples
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