NEWS

BayesianMCPMod 1.1.0 (2025-03-07)

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

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

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

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