rpact 4.2.1
New features
efficacyStops and futilityStops parameter
added (issue #88) 
- parameter 
stdErrorEstimate ("pooled" or
"unpooled") added for calculation of final confidence
intervals in two-sample situation for rates 
testPackage() returns an
InstallationQualificationResult object 
Improvements, issues, and
changes
- Issue for conditional power calculation for group sequential designs
in analysis tool fixed
 
- Recruitment times for count and survival data situation improved
(issue #86)
 
- Bug fix for 
getSimulationCounts() (issue #84) 
- Minor improvements
 
rpact 4.2.0
New features
- For the functions 
getSimulationMultiArmMeans(),
getSimulationMultiArmRates(), and
getSimulationMultiArmSurvival() it is now possible to
specify a parameter doseLevels to define the dose levels
for a linear or sigmoidEmax dose-response
relationship (see feature request #63) 
- Added support for unequal variances between two groups in
getSampleSizeMeans(), getPowerMeans(), and
getSimulationMeans() functions, see enhancement #70 
testPackage() produces a comprehensive installation
qualification report in html and pdf format (see new vignette Installation
Qualification of rpact) 
setupPackageTests() sets up the package tests by
downloading the test files and copying them to the rpact installation
directory 
saveOptions() saves the current rpact
options to a configuration file 
resetOptions() resets the rpact options to
their default values 
- Argument 
conservative added to
getSampleSizeRates() function, see enhancement #39 
- Enable futility boundaries in Boundaries p Values Scale
plot plot (type = 3) using
options("rpact.plot.show.futility.on.pvalue.scale" = TRUE)
or argument showFutilityBounds = TRUE, see enhancement #79 
- Enable beta-spending in Error Spending plot (type = 4)
using 
options("rpact.plot.show.beta.spent" = TRUE) or
argument showBetaSpent = TRUE, see enhancement #80.
Furthermore, options("rpact.plot.show.alpha.spent" = FALSE)
or argument showAlphaSpent = FALSE can be used to show only
beta-spending in the plot 
Improvements, issues, and
changes
- Issue for calculation of confidence intervals when using the
conditional Dunnett test design
(
getDesignConditionalDunnett()) in analysis tool is
fixed. 
- The full set of unit tests for rpact is now stored in a private
repository. Only members of the ‘RPACT User Group’ have access to the
tests. For more information, please visit: rpact.org/iq
and RPACT Connect
 
- Usage of 
maxInformation improved (see enhancement #65) 
- Line breaks in the output of 
getObjectRCode() improved
(see #81) 
testPackage(): additional warning details will be added
to the test report if warnings exist* Issue #61 fixed 
- Issue #68
fixed
 
- Flexibility of function 
getPiecewiseSurvivalTime()
improved 
- Simulation allows the case #events = #patients
 
- Test coverage improved
 
- Plot subtitles improved
 
- Warning message added for extreme choice of
informationRates, userAlphaSpending, and
userBetaSpending
 
- Minor improvements
 
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