# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "BayesPPD" in publications use:' type: software license: GPL-3.0-or-later title: 'BayesPPD: Bayesian Power Prior Design' version: 1.1.3 identifiers: - type: doi value: 10.32614/CRAN.package.BayesPPD abstract: Bayesian power/type I error calculation and model fitting using the power prior and the normalized power prior for generalized linear models. Detailed examples of applying the package are available at . Models for time-to-event outcomes are implemented in the R package 'BayesPPDSurv'. The Bayesian clinical trial design methodology is described in Chen et al. (2011) , and Psioda and Ibrahim (2019) . The normalized power prior is described in Duan et al. (2006) and Ibrahim et al. (2015) . authors: - family-names: Shen given-names: Yueqi email: angieshen6@gmail.com - family-names: Psioda given-names: Matthew A. email: matt_psioda@unc.edu - family-names: Ibrahim given-names: Joseph G. email: ibrahim@bios.unc.edu preferred-citation: type: article title: 'BayesPPD: An R Package for Bayesian Sample Size Determination Using the Power and Normalized Power Prior for Generalized Linear Models' authors: - family-names: Shen given-names: Yueqi email: angieshen6@gmail.com - family-names: Psioda given-names: Matthew A. email: matt_psioda@unc.edu - family-names: Ibrahim given-names: Joseph G. email: ibrahim@bios.unc.edu journal: The R Journal year: '2023' volume: '14' issue: '4' repository: https://angieshen6.r-universe.dev commit: a105b5c74c009b19c541310f436d70714827e36b date-released: '2025-01-03' contact: - family-names: Shen given-names: Yueqi email: angieshen6@gmail.com