Package: rpact 4.1.0.9271

Friedrich Pahlke

rpact: Confirmatory Adaptive Clinical Trial Design and Analysis

Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.

Authors:Gernot Wassmer [aut], Friedrich Pahlke [aut, cre], Till Jensen [ctb], Stephen Schueuerhuis [ctb], Tobias Muetze [ctb]

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rpact.pdf |rpact.html✨
rpact/json (API)
NEWS

# Install 'rpact' in R:
install.packages('rpact', repos = c('https://rpact-com.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/rpact-com/rpact/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

    On CRAN:

    adaptive-designanalysisclinical-trialscount-datagroup-sequential-designspower-calculationsample-size-calculationsimulationvalidated

    7.86 score 23 stars 1 packages 101 scripts 1.3k downloads 1 mentions 91 exports 8 dependencies

    Last updated 21 hours agofrom:ae013d3280. Checks:OK: 9. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKNov 20 2024
    R-4.5-win-x86_64OKNov 20 2024
    R-4.5-linux-x86_64OKNov 20 2024
    R-4.4-win-x86_64OKNov 20 2024
    R-4.4-mac-x86_64OKNov 20 2024
    R-4.4-mac-aarch64OKNov 20 2024
    R-4.3-win-x86_64OKNov 20 2024
    R-4.3-mac-x86_64OKNov 20 2024
    R-4.3-mac-aarch64OKNov 20 2024

    Exports:as251Normalas251StudentTfetchgetAccrualTimegetAnalysisResultsgetAvailablePlotTypesgetClosedCombinationTestResultsgetClosedConditionalDunnettTestResultsgetConditionalPowergetConditionalRejectionProbabilitiesgetDatagetData.SimulationResultsgetDatasetgetDataSetgetDesignCharacteristicsgetDesignConditionalDunnettgetDesignFishergetDesignGroupSequentialgetDesignInverseNormalgetDesignSetgetEventProbabilitiesgetFinalConfidenceIntervalgetFinalPValuegetGroupSequentialProbabilitiesgetHazardRatioByPigetLambdaByMediangetLambdaByPigetLambdaStepFunctiongetLogLevelgetLongFormatgetMedianByLambdagetMedianByPigetNumberOfSubjectsgetObjectRCodegetObservedInformationRatesgetOutputFormatgetParameterCaptiongetParameterNamegetParameterTypegetPerformanceScoregetPiByLambdagetPiByMediangetPiecewiseExponentialDistributiongetPiecewiseExponentialQuantilegetPiecewiseExponentialRandomNumbersgetPiecewiseSurvivalTimegetPlotSettingsgetPowerAndAverageSampleNumbergetPowerCountsgetPowerMeansgetPowerRatesgetPowerSurvivalgetRawDatagetRepeatedConfidenceIntervalsgetRepeatedPValuesgetSampleSizeCountsgetSampleSizeMeansgetSampleSizeRatesgetSampleSizeSurvivalgetSimulationCountsgetSimulationEnrichmentMeansgetSimulationEnrichmentRatesgetSimulationEnrichmentSurvivalgetSimulationMeansgetSimulationMultiArmMeansgetSimulationMultiArmRatesgetSimulationMultiArmSurvivalgetSimulationRatesgetSimulationSurvivalgetStageResultsgetTestActionsgetWideFormatkablemvnprdmvstudobtainplotTypesppwexpprintCitationqpwexprcmdreadDatasetreadDatasetsresetLogLevelrpwexpsetLogLevelsetOutputFormattest_plan_sectiontestPackagewriteDatasetwriteDatasets

    Dependencies:evaluatehighrknitrR6Rcpprlangxfunyaml

    Getting started with rpact

    Friedrich Pahlke and Gernot Wassmer

    Rendered fromrpact_getting_started.Rmdusingknitr::rmarkdownon Nov 20 2024.

    Last update: 2024-08-24
    Started: 2022-07-15

    Readme and manuals

    Help Manual

    Help pageTopics
    Algorithm AS 251: Normal Distributionas251Normal
    Algorithm AS 251: Student T Distributionas251StudentT
    Get Accrual TimegetAccrualTime
    Get Analysis ResultsgetAnalysisResults
    Get Closed Combination Test ResultsgetClosedCombinationTestResults
    Get Closed Conditional Dunnett Test ResultsgetClosedConditionalDunnettTestResults
    Get Conditional PowergetConditionalPower
    Get Conditional Rejection ProbabilitiesgetConditionalRejectionProbabilities
    Get Simulation DatagetData getData.SimulationResults
    Get DatasetgetDataSet getDataset
    Get Design CharacteristicsgetDesignCharacteristics
    Get Design Conditional Dunnett TestgetDesignConditionalDunnett
    Get Design FishergetDesignFisher
    Get Design Group SequentialgetDesignGroupSequential
    Get Design Inverse NormalgetDesignInverseNormal
    Get Design SetgetDesignSet
    Get Event ProbabilitiesgetEventProbabilities
    Get Final Confidence IntervalgetFinalConfidenceInterval
    Get Final P ValuegetFinalPValue
    Get Group Sequential ProbabilitiesgetGroupSequentialProbabilities
    Get Number Of SubjectsgetNumberOfSubjects
    Get Observed Information RatesgetObservedInformationRates
    Get Output FormatgetOutputFormat
    Get Performance ScoregetPerformanceScore
    Get Piecewise Survival TimegetPiecewiseSurvivalTime
    Get Power And Average Sample NumbergetPowerAndAverageSampleNumber
    Get Power CountsgetPowerCounts
    Get Power MeansgetPowerMeans
    Get Power RatesgetPowerRates
    Get Power SurvivalgetPowerSurvival
    Get Simulation Raw Data for SurvivalgetRawData
    Get Repeated Confidence IntervalsgetRepeatedConfidenceIntervals
    Get Repeated P ValuesgetRepeatedPValues
    Get Sample Size CountsgetSampleSizeCounts
    Get Sample Size MeansgetSampleSizeMeans
    Get Sample Size RatesgetSampleSizeRates
    Get Sample Size SurvivalgetSampleSizeSurvival
    Get Simulation CountsgetSimulationCounts
    Get Simulation Enrichment MeansgetSimulationEnrichmentMeans
    Get Simulation Enrichment RatesgetSimulationEnrichmentRates
    Get Simulation Enrichment SurvivalgetSimulationEnrichmentSurvival
    Get Simulation MeansgetSimulationMeans
    Get Simulation Multi-Arm MeansgetSimulationMultiArmMeans
    Get Simulation Multi-Arm RatesgetSimulationMultiArmRates
    Get Simulation Multi-Arm SurvivalgetSimulationMultiArmSurvival
    Get Simulation RatesgetSimulationRates
    Get Simulation SurvivalgetSimulationSurvival
    Get Stage ResultsgetStageResults
    Get Test ActionsgetTestActions
    Print Summary Factory in Markdown Code Chunksknit_print.SummaryFactory
    Original Algorithm AS 251: Normal Distributionmvnprd
    Original Algorithm AS 251: Student T Distributionmvstud
    Extract a single parameterfetch fetch.ParameterSet obtain obtain.ParameterSet
    Analysis Results Plottingplot.AnalysisResults
    Dataset Plottingplot.Dataset
    Event Probabilities Plottingplot.EventProbabilities
    Number Of Subjects Plottingplot.NumberOfSubjects
    Parameter Set Plottingplot.ParameterSet
    Simulation Results Plottingplot.SimulationResults
    Stage Results Plottingplot.StageResults
    Summary Factory Plottingplot.SummaryFactory
    Trial Design Plottingplot.TrialDesign plot.TrialDesignCharacteristics
    Trial Design Plan Plottingplot.TrialDesignPlan
    Trial Design Set Plottingplot.TrialDesignSet
    Plot Trial Design Summariesplot.TrialDesignSummaries
    Get Available Plot TypesgetAvailablePlotTypes plotTypes
    Summary Factory Printingprint.SummaryFactory
    Trial Design Characteristics Printingprint.TrialDesignCharacteristics
    Print Trial Design Summariesprint.TrialDesignSummaries
    Get Object R CodegetObjectRCode rcmd
    Read DatasetreadDataset
    Read Multiple DatasetsreadDatasets
    rpact - Confirmatory Adaptive Clinical Trial Design and Analysisrpact-package rpact
    Set Output FormatsetOutputFormat
    Test PackagetestPackage
    The Piecewise Exponential DistributiongetPiecewiseExponentialDistribution getPiecewiseExponentialQuantile getPiecewiseExponentialRandomNumbers ppwexp qpwexp rpwexp utilitiesForPiecewiseExponentialDistribution
    Survival Helper Functions for Conversion of Pi, Lambda, MediangetHazardRatioByPi getLambdaByMedian getLambdaByPi getMedianByLambda getMedianByPi getPiByLambda getPiByMedian utilitiesForSurvivalTrials
    Write DatasetwriteDataset
    Write Multiple DatasetswriteDatasets