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bayprior
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", "0.3.2") Attach the package and use:
library("bayprior")
Maintained by
Ndoh Penn
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
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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 0.3.2, https://cran.r-project.org/web/packages/bayprior. Accessed 30 Oct. 2026.
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