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]

MedianaDesigner_0.13.tar.gz
MedianaDesigner_0.13.zip(r-4.7-x86_64)MedianaDesigner_0.13.zip(r-4.7-arm64)MedianaDesigner_0.13.zip(r-4.6-x86_64)MedianaDesigner_0.13.zip(r-4.6-arm64)MedianaDesigner_0.13.zip(r-4.5-x86_64)
MedianaDesigner_0.13.tgz(r-4.6-x86_64)MedianaDesigner_0.13.tgz(r-4.6-arm64)MedianaDesigner_0.13.tgz(r-4.5-x86_64)MedianaDesigner_0.13.tgz(r-4.5-arm64)
MedianaDesigner_0.13.tar.gz(r-4.7-arm64)MedianaDesigner_0.13.tar.gz(r-4.7-x86_64)MedianaDesigner_0.13.tar.gz(r-4.6-arm64)MedianaDesigner_0.13.tar.gz(r-4.6-x86_64)
MedianaDesigner_0.13.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MedianaDesigner/json (API)

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

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

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

On CRAN:

Conda:

cpp

3.83 score 22 stars 31 scripts 415 downloads 56 exports 117 dependencies

Last updated from:bb4dfed25b. Checks:13 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE273
linux-devel-x86_64NOTE303
source / vignettesOK226
linux-release-arm64NOTE285
linux-release-x86_64NOTE251
macos-release-arm64NOTE279
macos-release-x86_64NOTE515
macos-oldrel-arm64NOTE281
macos-oldrel-x86_64NOTE511
windows-devel-arm64NOTE732
windows-devel-x86_64NOTE374
windows-release-arm64NOTE518
windows-release-x86_64NOTE338
windows-oldrel-x86_64NOTE339
wasm-releaseOK146

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

Dependencies:askpassbackportsbase64encbootbroombslibcachemclicodetoolscolorspacecommonmarkcowplotcpp11data.tableDerivdevEMFdigestdoBydoParalleldoRNGdplyrevaluatefarverfastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverforeachforecastfracdifffsgdtoolsgenericsggplot2gluegtablehighrhtmltoolshttpuvisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelifecyclelme4lmerTestlmtestmagrittrMASSMatrixmemoisemimeminqamodelrmvtnormnlmenloptrnnetnumDerivofficeropensslotelpbkrtestpillarpkgconfigpromisespurrrR6raggrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppNumericalRdpackreformulasrlangrmarkdownrngtoolsrootSolveS7sassscalesshinyshinydashboardshinyMatrixsourcetoolsstringistringrsyssystemfontstextshapingtibbletidyrtidyselecttimeDatetinytexurcautf8uuidvctrsviridisLitewithrxfunxml2xtableyamlzipzoo

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