All reference classes in the package have been replaced by R6 classes. This change brings significant advantages, including improved performance, more flexible and cleaner object-oriented programming, and enhanced encapsulation of methods and properties. The transition to R6 classes allows for more efficient memory management and faster execution, making the package more robust and scalable. Additionally, R6 classes provide a more intuitive and user-friendly interface for developers, facilitating the creation and maintenance of complex data structures and workflows.
Extension of the function getPerformanceScore() for sample size recalculation rules to the setting of binary endpoints according to Bokelmann et al. (2024)
The getSimulationMultiArmMeans(), getSimulationMultiArmRates(), and getSimulationMultiArmSurvival() functions now support an enhanced selectArmsFunction argument. Previously, only effectVector and stage were allowed as arguments. Now, users can optionally utilize additional arguments for more powerful custom function implementations, including conditionalPower, conditionalCriticalValue, plannedSubjects/plannedEvents, allocationRatioPlanned, selectedArms, thetaH1 (for means and survival), stDevH1 (for means), overallEffects, and for rates additionally: piTreatmentsH1, piControlH1, overallRates, and overallRatesControl.
Same as above forgetSimulationEnrichmentMeans(), getSimulationEnrichmentRates(), and getSimulationEnrichmentSurvival(). Specifically, support for population selection with selectPopulationsFunction argument based on predictive/posterior probabilities added (see #32)
New features
getPerformanceScore()for sample size recalculation rules to the setting of binary endpoints according to Bokelmann et al. (2024)getSimulationMultiArmMeans(),getSimulationMultiArmRates(), andgetSimulationMultiArmSurvival()functions now support an enhancedselectArmsFunctionargument. Previously, onlyeffectVectorandstagewere allowed as arguments. Now, users can optionally utilize additional arguments for more powerful custom function implementations, includingconditionalPower,conditionalCriticalValue,plannedSubjects/plannedEvents,allocationRatioPlanned,selectedArms,thetaH1(for means and survival),stDevH1(for means),overallEffects, and for rates additionally:piTreatmentsH1,piControlH1,overallRates, andoverallRatesControl.getSimulationEnrichmentMeans(),getSimulationEnrichmentRates(), andgetSimulationEnrichmentSurvival(). Specifically, support for population selection withselectPopulationsFunctionargument based on predictive/posterior probabilities added (see #32)Improvements, issues, and changes