Package: MedianaDesigner 0.13

Alex Dmitrienko

MedianaDesigner: Power and Sample Size Calculations for Clinical Trials

Efficient simulation-based power and sample size calculations are supported for a broad class of late-stage clinical trials. The following modules are included in the package: Adaptive designs with data-driven sample size or event count re-estimation, Adaptive designs with data-driven treatment selection, Adaptive designs with data-driven population selection, Optimal selection of a futility stopping rule, Event prediction in event-driven trials, Adaptive trials with response-adaptive randomization (experimental module), Traditional trials with multiple objectives (experimental module). Traditional trials with cluster-randomized designs (experimental module).

Authors:Alex Dmitrienko [aut, cre]

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MedianaDesigner.pdf |MedianaDesigner.html✨
MedianaDesigner/json (API)

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

Peer review:

Bug tracker:https://github.com/medianasoft/medianadesigner/issues

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

On CRAN:

56 exports 19 stars 2.02 score 109 dependencies 31 scripts 332 downloads

Last updated 1 years agofrom:bb4dfed25b. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 08 2024
R-4.5-win-x86_64NOTESep 08 2024
R-4.5-linux-x86_64NOTESep 08 2024
R-4.4-win-x86_64NOTESep 08 2024
R-4.4-mac-x86_64NOTESep 08 2024
R-4.4-mac-aarch64NOTESep 08 2024
R-4.3-win-x86_64NOTESep 08 2024
R-4.3-mac-x86_64NOTESep 08 2024
R-4.3-mac-aarch64NOTESep 08 2024

Exports:ADPopSelADPopSelAppADPopSelCADPopSelReportDocADPopSelSingleCoreADRandADRandAppADRandCADRandReportDocADRandSingleCoreADSSModADSSModAppADSSModCADSSModReportDocADSSModSingleCoreADTreatSelADTreatSelAppADTreatSelCADTreatSelReportDocADTreatSelSingleCoreClustRandClustRandAppClustRandGEECClustRandGLMEMRClustRandReportDocClustRandSingleCoreComputeDRFunctionParametersDRFunctionEventPredEventPredAppEventPredEventCountEventPredPriorDistributionEventPredREventPredReportDocEventPredRSingleCoreExportRandomClusterSizeExportTradMultAdjFutRuleFutRuleAppFutRuleCFutRuleReportDocFutRuleSingleCoreGenerateReportMultAdjMultAdj1SingleCoreMultAdjAppMultAdjReportDocprint.ADPopSelResultsprint.ADRandResultsprint.ADSSModResultsprint.ADTreatSelResultsprint.ClustRandResultsprint.EventPredResultsprint.FutRuleResultsprint.MultAdjResultsReportDoc

Dependencies:askpassbackportsbase64encbootbroombslibcachemclicodetoolscolorspacecommonmarkcowplotcpp11crayondata.tableDerivdevEMFdigestdoBydoParalleldoRNGdplyrevaluatefansifarverfastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverforeachfsgdtoolsgenericsggplot2gluegtablehighrhtmltoolshttpuvisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelifecyclelme4lmerTestmagrittrMASSMatrixmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellmvtnormnlmenloptrnumDerivofficeropensslpbkrtestpillarpkgconfigpromisespurrrR6raggrappdirsRColorBrewerRcppRcppEigenRcppNumericalrlangrmarkdownrngtoolsrootSolvesassscalesshinyshinydashboardshinyMatrixsourcetoolsstringistringrsyssystemfontstextshapingtibbletidyrtidyselecttinytexutf8uuidvctrsviridisLitewithrxfunxml2xtableyamlzip

Readme and manuals

Help Manual

Help pageTopics
Efficient Simulation-Based Power and Sample Size Calculations for a Broad Class of Late-Stage Clinical TrialsMedianaDesigner-package MedianaDesigner
Simulation-based design of adaptive trials with data-driven population selectionADPopSel ADPopSelC ADPopSelSingleCore
Graphical user interface to design an adaptive trial with data-driven population selectionADPopSelApp
Simulation-based design of an adaptive trial with population selection (normally distributed endpoint)ADPopSelExample1
Simulation-based design of an adaptive trial with population selection (binary endpoint)ADPopSelExample2
Simulation-based design of an adaptive trial with population selection (time-to-event endpoint)ADPopSelExample3
Simulation-based design of adaptive trials with response-adaptive randomizationADRand ADRandC ADRandSingleCore ComputeDRFunctionParameters DRFunction
Graphical user interface to design an adaptive trial with data-driven population selectionADRandApp
Simulation-based design of dose-finding Phase II trials with response-adaptive randomization (normally distributed endpoint)ADRandExample
Simulation-based design of adaptive trials with data-driven sample size or event count re-estimationADSSMod ADSSModC ADSSModSingleCore
Graphical user interface to design an adaptive trial with data-driven sample size or event count re-estimationADSSModApp
Simulation-based design of an adaptive trial with sample size re-estimation (normally distributed endpoint)ADSSModExample1
Simulation-based design of an adaptive trial with sample size re-estimation (binary endpoint)ADSSModExample2
Simulation-based design of an adaptive trial with event count re-estimation (time-to-event endpoint)ADSSModExample3
Simulation-based design of adaptive trials with data-driven treatment selectionADTreatSel ADTreatSelC ADTreatSelSingleCore
Graphical user interface to design an adaptive trial with data-driven treatment selectionADTreatSelApp
Simulation-based design of an adaptive trial with treatment selection (normally distributed endpoint)ADTreatSelExample1
Simulation-based design of an adaptive trial with treatment selection (binary endpoint)ADTreatSelExample2
Simulation-based design of an adaptive trial with treatment selection (time-to-event endpoint)ADTreatSelExample3
Simulation-based design of cluster-randomized trialsClustRand ClustRandC ClustRandGEEC ClustRandGLMEMR ClustRandSingleCore ExportRandomClusterSize
Graphical user interface to design a cluster-randomized trialClustRandApp
Simulation-based design of a cluster-randomized trial (normally distributed endpoint)ClustRandExample1
Simulation-based design of a cluster-randomized trial (binary endpoint)ClustRandExample2
Simulation-based event prediction in trials with an event-driven designEventPred EventPredEventCount EventPredR EventPredRSingleCore
Graphical user interface for event prediction in trials with an event-driven designEventPredApp
Example data set for EventPredEventPredData
Simulation-based event prediction in trials with an event-driven design (time-to- event endpoint)EventPredExample
Calculation of the parameters of prior gamma distributionsEventPredPriorDistribution
Simulation-based selection of an optimal futility stopping rule at an interim analysisFutRule FutRuleC FutRuleSingleCore
Graphical user interface for an optimal selection of a futility stopping rule at an interim analysisFutRuleApp
Simulation-based selection of an optimal futility stopping rule (normally distributed endpoint)FutRuleExample1
Simulation-based selection of an optimal futility stopping rule (binary endpoint)FutRuleExample2
Simulation-based selection of an optimal futility stopping rule (time-to-event endpoint)FutRuleExample3
Simulation reportADPopSelReportDoc ADRandReportDoc ADSSModReportDoc ADTreatSelReportDoc ClustRandReportDoc EventPredReportDoc FutRuleReportDoc GenerateReport MultAdjReportDoc print.ADPopSelResults print.ADRandResults print.ADSSModResults print.ADTreatSelResults print.ClustRandResults print.EventPredResults print.FutRuleResults print.MultAdjResults ReportDoc
Simulation-based design of traditional trials with multiple objectivesExportTradMultAdj MultAdj MultAdj1SingleCore MultAdjC
Graphical user interface for power calculations in traditional trials with multiple objectivesMultAdjApp
Simulation-based power calculations in Phase III trials with multiple dose-placebo comparisonsMultAdjExample1
Simulation-based power calculations in Phase III trials with multiple endpointsMultAdjExample2
Simulation-based power calculations in Phase III trials with multiple endpoints and multiple dose-placebo comparisonsMultAdjExample3