Recent Releases of r-rpact
r-rpact - rpact 4.2.1
New features
efficacyStopsandfutilityStopsparameter added (issue #88)- parameter
stdErrorEstimate("pooled"or"unpooled") added for calculation of final confidence intervals in two-sample situation for rates testPackage()returns anInstallationQualificationResultobject
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
Changelog
- kMax warning added by @fpahlke in https://github.com/rpact-com/rpact/pull/87
- Several new features and enhancements by @fpahlke in https://github.com/rpact-com/rpact/pull/89
- Multiple updates to the
rpactpackage by @fpahlke in https://github.com/rpact-com/rpact/pull/92
Full Changelog: https://github.com/rpact-com/rpact/compare/v4.2.0...v4.2.1
- R
Published by fpahlke 7 months ago
r-rpact - rpact 4.2.0
New features
- For the functions
getSimulationMultiArmMeans(),getSimulationMultiArmRates(), andgetSimulationMultiArmSurvival()it is now possible to specify a parameterdoseLevelsto define the dose levels for alinearorsigmoidEmaxdose-response relationship (see feature request #63) - Added support for unequal variances between two groups in
getSampleSizeMeans(),getPowerMeans(), andgetSimulationMeans()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 directorysaveOptions()saves the currentrpactoptions to a configuration fileresetOptions()resets therpactoptions to their default values- Argument
conservativeadded togetSampleSizeRates()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 argumentshowFutilityBounds = TRUE, see enhancement #79 - Enable beta-spending in Error Spending plot (type = 4) using
options("rpact.plot.show.beta.spent" = TRUE)or argumentshowBetaSpent = TRUE, see enhancement #80. Furthermore,options("rpact.plot.show.alpha.spent" = FALSE)or argumentshowAlphaSpent = FALSEcan 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
maxInformationimproved (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, anduserBetaSpending - Minor improvements
Full Changelog: https://github.com/rpact-com/rpact/compare/v4.1.0...v4.2.0
- R
Published by fpahlke 11 months ago
r-rpact - 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(), andgetDesignFisher()now support the argumentdirectionUpperto specify the direction of the alternative for one-sided testing early at the design phase, see enhancement #26 getSampleSizeCounts()andgetPowerCounts()output boundary values also on the treatment effect scale, see enhancement #40- The
fetch()andobtain()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
ggplot2changed 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 = FALSEhas no influence in simulation for testing rates in one-sample situation
- R
Published by fpahlke over 1 year ago
r-rpact - 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(), 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. - Same as above for
getSimulationEnrichmentMeans(),getSimulationEnrichmentRates(), andgetSimulationEnrichmentSurvival(). Specifically, support for population selection withselectPopulationsFunctionargument based on predictive/posterior probabilities added (see #32) - The
fetch()andobtain()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
- R
Published by fpahlke over 1 year ago
r-rpact - rpact 3.5.1
- The internal fields
.parameterNamesand.parameterFormatFunctionswere 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
eventsPerStagereplaced bycumulativeEventsPerStage - Field
singleEventsPerStageadded
- Field
getSimulationSurvival():- Field
eventsPerStagereplaced bysingleEventsPerStage - Field
overallEventsPerStagereplaced bycumulativeEventsPerStage
- Field
getSimulationMultiArmSurvival():- Field
eventsPerStagereplaced bycumulativeEventsPerStage - Field
singleNumberOfEventsPerStagereplaced bysingleEventsPerArmAndStage - Field
singleEventsPerStageadded
- Field
getSimulationEnrichmentSurvival():- field
singleNumberOfEventsPerStagereplaced bysingleEventsPerSubsetAndStage
- field
- Test coverage CI/CD pipeline activated with the assistance of GitHub Actions, which runs
covrand uploads the results to codecov.io - Minor improvements
- R
Published by fpahlke almost 2 years ago
r-rpact - rpact 3.5.0
New features
- The new functions
getSampleSizeCounts()andgetPowerCounts()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, andas251StudentT - R package
mnormtdependency has been removed - Argument
thetacan 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
What's Changed
- cran/release/3.4.0 by @fpahlke in https://github.com/rpact-com/rpact/pull/6
- New CRAN release version 3.5.0 by @fpahlke in https://github.com/rpact-com/rpact/pull/13
Full Changelog: https://github.com/rpact-com/rpact/compare/v3.4.0...v3.5.0
- R
Published by fpahlke about 2 years ago
r-rpact - 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 allocationRatioPlannedfor simulating multi-arm and enrichment designs can be a vector of length kMax, the number of stagesgetObjectRCode()(short:rcmd()): with the new argumentspipeOperatorandoutputmany 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_printfor all result objects implemented and automatic code chunk optionresults = 'asis'activated
Improvements, issues, and changes
- Improved speed of numerical computation of group sequential designs and test characteristics
- Multivariate t distribution restricted to
df <= 500because of erroneous results inmnormtpackage otherwise. Fordf > 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
omegatochiin classTrialDesignPlanSurvival - Several minor improvements
- R
Published by fpahlke over 2 years ago
r-rpact - rpact 3.3.4
allocationRatioPlannedfor simulating means and rates for a two treatment groups design can be a vector of length kMax, the number of stagescalcSubjectsFunctioncan be used in C++ version for simulating means and ratescalcEventsFunctionadded 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
- Rcpp sugar function
sapplyremoved from C++ code to stop deprecated warnings on r-devel-linux-x86_64-fedora-clang - Minor improvements
- R
Published by fpahlke about 3 years ago
r-rpact - 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++11added to DESCRIPTION to enable C++ 11 compilation on R 3.x- Minor improvements
- R
Published by fpahlke over 3 years ago
r-rpact - 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
- R
Published by fpahlke over 3 years ago
r-rpact - 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()andgetSimulationEnrichmentSurvival() - Design summary extended by information of
getDesignCharacteristics() getSimulationSurvival(): the result object now contains the new parameteroverallEventsPerStage, which contains the values previously given ineventsPerStage(it was "cumulative" by mistake);eventsPerStagecontains now the non-cumulative values as expected- Minor improvements
- R
Published by fpahlke over 3 years ago