rpact 4.1.0

New features

The new function getSimulationCounts() can be used to perform power simulations for clinical trials with negative binomial distributed count data. The function returns the simulated power, stopping probabilities, conditional power, and expected sample size for testing mean rates for negative binomial distributed event numbers in the two treatment groups testing situation.
The functions getDesignGroupSequential(), getDesignInverseNormal(), and getDesignFisher() now support the argument directionUpper to specify the direction of the alternative for one-sided testing early at the design phase, see enhancement #26
getSampleSizeCounts() and getPowerCounts() output boundary values also on the treatment effect scale, see enhancement #40
The fetch() and obtain() functions can be used to extract multiple parameters from an rpact result object and support various output formats

Improvements, issues, and changes

Usage of pipe-operators improved
Analysis progress messages are only displayed when R is used interactively
Manual use of kable() for rpact result objects marked as deprecated, as the formatting and display will be handled automatically by rpact
The order of all summary entries has been revised and optimized
Minimum version of suggested package ggplot2 changed from 2.2.0 to 3.2.0
Issues #41, #44, #46, and #47 fixed
When analyzing with a two-sided test, an issue with the calculation of the conditional rejection probability was fixed
Bug is fixed: directionUpper = FALSE has no influence in simulation for testing rates in one-sample situation

rpact 4.0.0

New features

All reference classes in the package have been replaced by R6 classes.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 for getSimulationEnrichmentMeans(), getSimulationEnrichmentRates(), and getSimulationEnrichmentSurvival(). Specifically, support for population selection with selectPopulationsFunction argument based on predictive/posterior probabilities added (see #32)
The fetch() and obtain() functions can be used to extract a single parameter from an rpact result object, which is useful for writing pipe-operator linked commands

Improvements, issues, and changes

Issues #25, #35, and #36 fixed
Minor improvements

rpact 3.5.1

The internal fields .parameterNames and .parameterFormatFunctions were removed from all rpact result objects in favor of a more efficient solution
Issues #15, #16, #17, #19, and #23 fixed
Fixed inconsistent naming of variables and class fields (issue #21)
- getSampleSizeSurvival() / getPowerSurvival():
  - Field eventsPerStage replaced by cumulativeEventsPerStage
  - Field singleEventsPerStage added
- getSimulationSurvival():
  - Field eventsPerStage replaced by singleEventsPerStage
  - Field overallEventsPerStage replaced by cumulativeEventsPerStage
- getSimulationMultiArmSurvival():
  - Field eventsPerStage replaced by cumulativeEventsPerStage
  - Field singleNumberOfEventsPerStage replaced by singleEventsPerArmAndStage
  - Field singleEventsPerStage added
- getSimulationEnrichmentSurvival():
  - field singleNumberOfEventsPerStage replaced by singleEventsPerSubsetAndStage
Test coverage CI/CD pipeline activated with the assistance of GitHub Actions, which runs covr and uploads the results to codecov.io
Minor improvements

rpact 3.5.0

New features

The new functions getSampleSizeCounts() and getPowerCounts() can be used to perform sample size calculations and the assessment of test characteristics for clinical trials with negative binomial distributed count data. This is possible for fixed sample size and group sequential designs. For the latter, the methodology described in Muetze et al. (2019) is implemented. These functions can also be used to perform blinded sample size reassessments according to Friede and Schmidli (2010).

Improvements, issues, and changes

Original Fortran 77 code of AS 251 included into the package, see functions mvnprd, mvstud, as251Normal, and as251StudentT
R package mnormt dependency has been removed
Argument theta can be used for plotting of sample size and power results
Pipe operator usage improved
Shiny app link changed to https://rpact.shinyapps.io/cloud
Several minor improvements

rpact 3.4.0

New features

The new function getPerformanceScore() calculates the conditional performance score, its sub-scores and components according to Herrmann et al. (2020) for a given simulation result from a two-stage design
allocationRatioPlanned for simulating multi-arm and enrichment designs can be a vector of length kMax, the number of stages
getObjectRCode() (short: rcmd()): with the new arguments pipeOperator and output many new output variants can be specified, e.g., the native R pipe operator or the magrittr pipe operator can be used
Generic function knitr::knit_print for all result objects implemented and automatic code chunk option results = 'asis' activated

Improvements, issues, and changes

Improved speed of numerical computation of group sequential designs and test characteristics
Multivariate t distribution restricted to df <= 500 because of erroneous results in mnormt package otherwise. For df > 500, multivariate normal distribution is used
Performance of cumulative distribution function and survival function plot improved
Test coverage extended and improved
Descriptions for all class fields added
Renamed field omega to chi in class TrialDesignPlanSurvival
Several minor improvements

rpact 3.3.4

Rcpp sugar function sapply removed from C++ code to stop deprecated warnings on r-devel-linux-x86_64-fedora-clang
Minor improvements

rpact 3.3.3

allocationRatioPlanned for simulating means and rates for a two treatment groups design can be a vector of length kMax, the number of stages
calcSubjectsFunction can be used in C++ version for simulating means and rates
calcEventsFunction added in getSimulationSurvival()
getPerformanceScore() added: calculates the performance score for simulation means results (1 and 2 groups; 2 stages)
Performance of simulation rates improved for 1 and 2 groups (by translating from R to C++)
Performance of simulation means improved for 1 and 2 groups
Two-sided O’Brien and Fleming beta-spending function corrected
Issue in plot type 5 for sample size means and rates fixed
Added dependency on R >= 3.6.0
Minor improvements

rpact 3.3.2

Design objects can be piped into getDataset() to enable pipe syntax for analysis, e.g., getDesignGroupSequential() |> getDataset(dataMeans) |> getAnalysisResults()
Performance of simulation means improved for 1 and 2 groups (by translating from R to C++)
Total test time was cut in half by improving simulation performance and enabling parallel testing
SystemRequirements: C++11 added to DESCRIPTION to enable C++ 11 compilation on R 3.x
Minor improvements

rpact 3.3.1

Help pages improved
Parameter betaAdjustment can also be used in getDesignInverseNormal()
subsets removed from result of getWideFormat() for non-enrichment datasets
Summary of enrichment survival simulation results improved
Parameter populations in getSimulationEnrichmentMeans(), getSimulationEnrichmentRates(), and getSimulationEnrichmentSurvival() has been removed since it is always derived from effectList
Bug fixed in getSimulationEnrichmentRates() for calculated non-integer number of subjects
Futility probabilities and futility bounds corrected for two-sided beta-spending function approach
getRawData(): the resulting data.frame now contains the correct stopStage and lastObservationTime (formerly observationTime)
deltaWT is provided with three decimal points for typeOfDesign = “WToptimum”
Generic as.data.frame functions improved
testthat version changed to edition 3
The rpact source code has been published on GitHub and the bug report link has been changed to https://github.com/rpact-com/rpact/issues
Minor improvements

rpact 3.3.0

New features

Two-sided beta-spending approach with binding and non-binding futility bounds
Delayed response utility added in design specification

Improvements, issues, and changes

getSimulationMultiArmSurvival(): single stage treatment arm specific event numbers account for selection procedure
User defined selection function can be used in getSimulationEnrichmentRates() and getSimulationEnrichmentSurvival()
Design summary extended by information of getDesignCharacteristics()
getSimulationSurvival(): the result object now contains the new parameter overallEventsPerStage, which contains the values previously given in eventsPerStage (it was “cumulative” by mistake); eventsPerStage contains now the non-cumulative values as expected
Minor improvements

rpact 3.2.3

Performance of group sequential and Fisher’s combination test designs improved
‘register’ storage class specifier removed from C++ sources
Minor improvements

rpact 3.2.2

Performance of group sequential and Fisher’s combination test designs improved (by translating from R to C++)
Numerical issue in analysis time calculation for survival design in specific cases resolved
The internally used minimum quantile function value was changed from stats::qnorm(1e-323) to stats::qnorm(1e-100)
Unit tests extended
Minor improvements

rpact 3.2.1

C++ warning “using integer absolute value function ‘abs’ when argument is of floating point type” under r-devel-linux-x86_64-debian-clang removed
getDataset: support of emmeans result objects as input improved
getAnalysisResults(): issue with zero values in the argument ‘userAlphaSpending’ fixed
Minor improvements

rpact 3.2.0

New features

Simulation tools for enrichment design testing means, rates, and hazard ratios: function getSimulationEnrichmentMeans(), getSimulationEnrichmentRates(), getSimulationEnrichmentSurvival() available for simulation of enrichment designs; note that this is a novel implementation, hence experimental
getDesignGroupSequential() / getDesignInverseNormal(): new typeOfDesign = “noEarlyEfficacy” added

Improvements, issues, and changes

getSimulationSurvival(): bug fixed for accruallIntensity = 0 at some accrual intervals
For observed conditional power, standardized theta not truncated to 0 any more in getSimulationMultiArmMeans(), getSimulationMultiArmRates(), and getSimulationMultiArmSurvival()
Conditional power calculation for analysis rates takes into account differently the null value of condErrorRate
Function testPackage(): a problem with downloading full set of unit tests under Debian/Linux has been fixed
Generic function kable() improved: optional knitr::kable arguments enabled, e.g., format
In print and summary output, “overall” renamed to “cumulative” if means, stDevs, or rate are calculated over stages rather than stage-wise
getDataset: support of emmeans result objects as input improved
Numerical accuracy of qnorm() calculations improved
Analysis enrichment results now support the generic function as.data.frame()
Naming of the stage results parameters in the print output improved
New example data added: “rawDataTwoArmNormal”
Issue in summary fixed: earlyStop and rejectPerStage were no longer displayed
Minor improvements

rpact 3.1.1

Performance of two-sided Pampallona & Tsiatis design improved
12 example datasets added
Sample sizes in plots now have the same format as in print output; format can be changed using setOutputFormat()
getDataset supports emmeans result objects as input
Print output of simulation results improved
Added dependency on R >= 3.5.0 because serialized objects in serialize/load version 3 cannot be read in older versions of R
Plot label interface for configuration via the rpact Shiny app implemented
Minor improvements

rpact 3.1.0

New features

Analysis tools for enrichment design testing means, rates, and hazard ratios: function getAnalysisResults() generalized for enrichment designs; function getDataset() generalized for entering stratified data; manual extended for enrichment designs
Automatic boundary recalculations during the trial for analysis with alpha spending approach, including under- and over-running: setup via the optional parameters ‘maxInformation’ and ‘informationEpsilon’ in function getAnalysisResults()
The new function getObjectRCode() (short: rcmd()) returns the original R command which produced any rpact result object, including all dependencies
getWideFormat() and getLongFormat() return a dataset object in wide format (unstacked) or long format (narrow, stacked)
Generic function kable() returns the output of an rpact result object formatted in Markdown.
Generic function t() returns the transpose of an rpact result object

Improvements, issues, and changes

New argument ‘plotSettings’ added to all plot functions
Summary for design, simulation, and analysis unified and extended
Issue in getDesignFisher() fixed: getDesignFisher(method = "noInteraction", kMax = 3) and getDesignFisher(method = "noInteraction") produced different results
‘normalApproximation’ default value changed to TRUE for multi-arm analysis of rates
Repeated p-values: in search algorithm, upper bound of significance level corrected when considering binding futility bounds
testPackage(): the default call is now running only a small subset of all available unit tests; with the new argument ‘connection’ the owners of the rpact validation documentation can enter a ‘token’ and a ‘secret’ to get full access to all unit tests
Scaling of grid plots improved
Minor improvements

rpact 3.0.4

Beta-spending function approach with binding futility bounds
Pampallona & Tsiatis design with binding and non-binding futility bounds
Argument ‘accrualIntensityType’ added to getSampleSizeSurvival(), getSimulationSurvival(), getNumberOfSubjects(), and getEventProbabilities()
Specification of Weibull survival times possible through definition of hazard rates or medians in simulation tool
Minor improvements

rpact 3.0.3

New utility functions getParameterCaption() and getParameterName() implemented
Design parameters added to simulation print output
Generic function as.matrix() improved for several result objects
Issue in getAvailablePlotTypes() for sample size and power results fixed
Issue for getDesignFisher(kMax = 1) in getSimulationMultiArm...() fixed
getSimulationMultiArmSurvival(): correlation of log-rank statistics revised and improved
getSimulationMultiArmMeans(): name of the first effectMeasure option “effectDifference” changed to “effectEstimate”
getSimulation[MultiArm][Means/Rates/Survival](): argument ‘showStatistics’ now works correctly and is consistently FALSE by default for multi-arm and non-multi-arm
getSimulation[MultiArm]Survival(): generic function summary() improved
getAnalysisResults(): generic function summary() improved
getAccrualTime(): improved and new argument ‘accrualIntensityType’ added
Header text added to design summaries
getSampleSizeSurvival(): field ‘studyDurationH1’ in result object was replaced by ‘studyDuration’, i.e., ‘studyDurationH1’ is deprecated and will be removed in future versions
Minor changes in the inline help and manual
Minor improvements

rpact 3.0.2

getSimulationMultiArmSurvival(): plannedEvents redefined as overall events over treatment arms
getStageResults(): element overallPooledStDevs added; print output improved
Unit tests improved: test coverage and references to the functional specification optimized
plot type 13 of getSampleSizeSurvival() with user defined lambdas with different lengths: issue fixed
Minor improvements

rpact 3.0.1

Vignette “rpact: Getting Started” included into the package
New summary output option “rpact.summary.width” added
Generic function summary() improved for several result objects
Result output of function testPackage() improved
getSimulationMultiArm[Means/Rates/Survival](): stage index corrected for user defined calcSubjectsFunction or calcEventsFunction
getSimulationMultiArmRates(): adjustment for identical simulated rates to account for ties
getSimulationMultiArmSurvival(): corrected correlation of test statistics
Output formatting improved
Minor improvements

rpact 3.0.0

New features

Simulation tools for multi-arm design testing means, rates, and hazard ratios
Analysis tools for multi-arm design testing means, rates, and hazard ratios
getSimulationRates(): exact versions for testing a rate (one-sample case) and equality of rates (two-sample case)
getDataset: multi-arm datasets for means, rates, and survival data
Analysis of fixed designs
Summary for analysis and simulation result objects newly implemented
Summary for most rpact result objects substantially improved and enhanced
getEventProbabilities(): plot of result object
getNumberOfSubjects(): plot of result object
Visual comparison of two designs: plot(design1, design2)
Functions setOutputFormat and getOutputFormat implemented: definition of user defined output formats
getSimulationMeans(): thetaH1 and stDevH1 can be specified for assessment of sample size recalculation (replaces thetaStandardized)
getSimulationSurvival(): separate p-values added to the aggregated simulation data for Fisher designs
getSimulationMeans(), getSimulationRates(): Cumulated number of subjects integrated in getData object
getSimulation[MultiArm][Means/Rates/Survival](): new logical argument ‘showStatistics’ added
Example datasets (csv files) added to the package
plot type “all”: plot all available plots of an object in one step using plot(x, type = "all")
plot type improved: ‘type’ now can be a vector, e.g., plot(x, type = c(1, 3))
plot(x, grid = 1): new plot argument ‘grid’ enables the plotting of 2 or more plots in one graphic

Improvements, issues, and changes

getAnalysisResults(): list output implemented analogous to the output of all other rpact objects
getAnalysisResults(): the following stage result arguments were removed from result object because they were redundant: effectSizes, testStatistics, and pValues. Please use the ‘.stageResults’ object to access them, e.g., results$.stageResults$effectSizes
getAnalysisResults(): the following design arguments were removed from result object because they were redundant: stages, informationRates, criticalValues, futilityBounds, alphaSpent, and stageLevels. Please use the ‘.design’ object to access them, e.g., results$.design$informationRates
Optional argument ‘stage’ removed from functions getConditionalPower, getConditionalRejectionProbabilities, getFinalPValue, getRepeatedPValues, and getTestActions
Function testPackage improved, e.g., results will be displayed now on screen
Help system renewed and approved, e.g., help for corresponding generic functions (e.g., plot) linked where applicable
Function getPiecewiseSurvivalTime improved: pi1 and pi2 will not be calculated any longer for lambda- or median-based definitions; eventTime only required for pi-based definitions
plot(x, showSource = TRUE) improved for all rpact result objects x
Performance of plotting analysis results of Fisher designs improved
getSimulationRates(): issue for futility stopping for Fisher’s combination test fixed
getSimulationSurvival(): issue for expected number of events fixed
getSimulationSurvival(): if eventsNotAchieved > 0, rejection/futility rate and analysis time is estimated for valid simulation runs
getSimulationSurvival(): output improved for lambda1/median1/hazardRatio with length > 1
getSampleSizeSurvival(): calculation of the maximum number of subjects given the provided argument ‘followUpTime’ improved
getPiecewiseSurvivalTime(): delayed response via list-based piecewiseSurvivalTime definition enabled
getAccrualTime() / getSimulationSurvival(): issue with the calculation of absolute accrual intensity by given relative accrual intensity fixed
getRawData(): issue for multiple pi1 solved
Implementation of the generic function ‘names’ improved
Test coverage improved: lots of new unit tests added
License information in the DESCRIPTION file corrected: changed from GPL-3 to LGPL-3
Minor improvements

rpact 2.0.6

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 2.0.5

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

rpact 2.0.4

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

rpact 2.0.3

New features

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

Improvements, issues, and changes

Generic function as.data.frame improved for getDesign[...](), getSampleSize[...](), getPower[...](), and getSimulation[...]() results
Output of getStageResults() improved
Improvements for Shiny app compatibility and better Shiny app performance
Repeated p-values are no longer calculated for typeOfDesign = “WToptimum”
Piecewise survival 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

rpact 2.0.2

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

rpact 2.0.1

Function base::isFALSE replaced to guarantee R 3.4.x compatibility
C++ compiler warning on r-devel-linux-x86_64-debian-clang system removed
C++ compiler error on r-patched-solaris-x86 system fixed

rpact 2.0.0

New features

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

Improvements, issues, and changes

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

rpact 1.0.0

First release of rpact