BayesianMCPMod 1.1.0 (07-Mar-2025)

• Fixed a bug in plot.modelFits() that would plot credible bands based on incorrectly selected bootstrapped quantiles
• Added getMED(), a function to assess the minimally efficacious dose (MED) and integrated getMED() into assessDesign() and performBayesianMCPMod
• Added parallel processing using the future framework
• Modified the handling of the fit of an average model: Now, getModelFits() has an argument to fit an average model and this will be carried forward for all subsequent functions
• Re-introduced getBootstrapSamples(), a separate function for bootstrapping samples from the posterior distributions of the dose levels
• Adapted the vignettes to new features

BayesianMCPMod 1.0.2 (06-Feb-2025)

• Addition of new vignette comparing frequentist and Bayesian MCPMod using vague priors
• Extension of getPosterior to allow the input of a fully populated variance-covariance matrix
• Added the non-monotonic model shapes beta and quadratic
• New argument in assessDesign() to optionally skip the Mod part of Bayesian MCPMod
• Additional tests

BayesianMCPMod 1.0.1 (03-Apr-2024)

• Re-submission of the ‘BayesianMCPMod’ package
• Removed a test that occasionally failed on the fedora CRAN test system
• Fixed a bug that would return wrong bootstrapped quantiles in getBootstrapQuantiles()
• Added getBootstrapSamples(), a separate function for bootstrapping samples

BayesianMCPMod 1.0.0 (31-Dec-2023)

• Initial release of the ‘BayesianMCPMod’ package
• Special thanks to Jana Gierse, Bjoern Bornkamp, Chen Yao, Marius Thomas & Mitchell Thomann for their review and valuable comments
• Thanks to Kevin Kunzmann for R infrastructure support and to Frank Fleischer for methodological support