rpact 2.06

Boundaries on effect scale for testing means now accounts for the unknown variance case
getAnalysisSurvival: calculation of stage wise results not more in getStageResults
getStageResults: the calculation of ‘effectSizes’ for survival data and thetaH0 != 1 was corrected
getDataset of survival data: issue with the internal storage of log ranks fixed
Sample size plot: issue for kMax = 1 fixed
getSampleSizeSurvival with piecewise survival time: issue with calculation of ‘maxNumberOfSubjects’ for given ‘followUpTime’ fixed
Internal Shiny app interface improved
Minor improvements

rpact 2.05

Assumed median survival time: get[SampleSize/Power/Simulation]Survival now support direct input of arguments ‘median1’ and ‘median2’
Output of generic function ‘summary’ improved
Plot type 5 of getPower[…] and getSimulation[…] objects improved
Output of getSampleSizeSurvival with given maxNumberOfSubjects improved
Output of get[SampleSize/Power]Survival for Kappa != 1 improved
Assert function for minNumberOfSubjectsPerStage corrected for undefined conditionalPower
Two-sided boundaries on effect scale in survival design improved
Error in ‘summary’ for getDesign[…] fixed
Other minor improvements

Incorrect output of function ‘summary’ fixed for getSampleSize[…] and getPower[…]
as.data.frame: default value of argument ‘niceColumnNamesEnabled’ changed from TRUE to FALSE

Plot function for Fisher design implemented
Generic function ‘summary’ implemented for getDesign[…], getSampleSize[…], getPower[…], and getSimulation[…] results: a simple boundary summary will be displayed

Generic function as.data.frame improved for getDesign[…], getSampleSize[…], getPower[…], and getSimulation[…] results
Ouput of getStageResults() improved
Improvements for Shiny app compatibility and better Shiny app performance
Repeated p-values are no longer calculated for typeOfDesign = “WToptimum”
Piecewise suvival time improved for numeric definition: median and pi will not be calculated and displayed any longer
Plot: legend title and tick mark positioning improved; optional arguments xlim and ylim implemented
Sample size/power: usage of argument ‘twoSidedPower’ optimized
Performance of function rpwexp/getPiecewiseExponentialRandomNumbers improved (special thanks to Marcel Wolbers for his example code)
For group sequential designs a warning will be displayed if information rates from design not according to data information
Format for output of standard deviation optimized

Minor corrections in the inline help
Labeling of lower and upper critical values (effect scale) reverted
Simulation for Fisher’s combination test corrected
Parameter minNumberOfAdditionalEventsPerStage renamed to minNumberOfEventsPerStage
Parameter maxNumberOfAdditionalEventsPerStage renamed to maxNumberOfEventsPerStage
Parameter minNumberOfAdditionalSubjectsPerStage renamed to minNumberOfSubjectsPerStage
Parameter maxNumberOfAdditionalSubjectsPerStage renamed to maxNumberOfSubjectsPerStage
Output of function getAccrualTime() improved
Validation of arguments maxNumberOfIterations, allocation1, and allocation2 added: check for positive integer
Function getSampleSizeSurvival improved: numeric search for accrualTime if followUpTime is given
Default value improved for analysis tools: if no effect was specified for conditional power calculation, the observed effect is selected
Fixed: function getDataset produced an error if only one log-rank value and one event was defined
Number of subjects per treatment arm are provided in output of simulation survival if allocation ratio != 1
Function getSimulationSurvival improved: first value of minNumberOfEventsPerStage and maxNumberOfEventsPerStage must be NA or equal to first value of plannedSubjects

Power calculation at given or adapted sample size for means, rates and survival data
Sample size and power calculation for survival trials with piecewise accrual time and intensity
Sample size and power calculation for survival trials with exponential survival time, piecewise exponential survival time and survival times that follow a Weibull distribution
Simulation tool for survival trials; our simulator is very fast because it was implemented with C++. Adaptive event number recalculations based on conditional power can be assessed
Simulation tool for designs with continuous and binary endpoints. Adaptive sample size recalculations based on conditional power can be assessed
Comprehensive and unified tool for performing sample size calculation for fixed sample size design
Enhanced plot functionalities

Fisher design, analysis of means or rates, conditional rejection probabilities (CRP): calculation issue fixed for stage > 2
Call of getSampleSize[Means/Rates/Survival] without design argument implemented
For all ‘set.seed’ calls ‘kind’ and ‘normal.kind’ were specified as follows: kind = “Mersenne-Twister”, normal.kind = “Inversion”
Minor code optimizations, e.g. ‘return()’ replaced by ‘return(invisible())’ if reasonable
Bug in ‘readDatasets’ fixed: variable names ‘group’ and ‘groups’ are now accepted
“Overall reject per stage” and “Overall futility per stage” renamed to “Overall reject” and “Overall futility”, respectively (also variable names).
Labels “events..” and “..patients..” consistently changed to “# events..” and “# patients…”, respectively.
Output format for ‘allocationRatioPlanned’ specified
Method ‘show’ of class ‘ParameterSet’ expanded: R Markdown output features implemented
getSampleSizeSurvival(): argument ‘maxNumberOfPatients’ was renamed in ‘maxNumberOfSubjects’
Result output, inline help and documentation: the word ‘patient’ was replaced by ‘subject’
Variables ‘numberOfSubjectsGroup1’ and ‘numberOfSubjectsGroup2’ were renamed to ‘numberOfSubjects1’ and ‘numberOfSubjects1’
Final p-values for two-sided test (group sequential, inverse normal, and Fisher combination test) available
Upper and lower boundaries on effect scale for testing rates in two samples