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MedianaDesigner (version 0.13)

Power and Sample Size Calculations for Clinical Trials

Description

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).

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Version

Install

install.packages('MedianaDesigner')

Monthly Downloads

289

Version

0.13

License

GPL-3

Issues

1

Pull Requests

0

Stars

21

Forks

3

Maintainer

Alex Dmitrienko

Last Published

August 28th, 2023

Functions in MedianaDesigner (0.13)

ADSSModExample1

Simulation-based design of an adaptive trial with sample size re-estimation (normally distributed endpoint)
ADTreatSelApp

Graphical user interface to design an adaptive trial with data-driven treatment selection
ADTreatSelExample2

Simulation-based design of an adaptive trial with treatment selection (binary endpoint)
ClustRandApp

Graphical user interface to design a cluster-randomized trial
ADSSModExample2

Simulation-based design of an adaptive trial with sample size re-estimation (binary endpoint)
ADSSModExample3

Simulation-based design of an adaptive trial with event count re-estimation (time-to-event endpoint)
ADTreatSelExample3

Simulation-based design of an adaptive trial with treatment selection (time-to-event endpoint)
ClustRand

Simulation-based design of cluster-randomized trials
ADTreatSel

Simulation-based design of adaptive trials with data-driven treatment selection
ADTreatSelExample1

Simulation-based design of an adaptive trial with treatment selection (normally distributed endpoint)
ClustRandExample1

Simulation-based design of a cluster-randomized trial (normally distributed endpoint)
FutRule

Simulation-based selection of an optimal futility stopping rule at an interim analysis
EventPred

Simulation-based event prediction in trials with an event-driven design
EventPredPriorDistribution

Calculation of the parameters of prior gamma distributions
FutRuleApp

Graphical user interface for an optimal selection of a futility stopping rule at an interim analysis
EventPredExample

Simulation-based event prediction in trials with an event-driven design (time-to- event endpoint)
EventPredApp

Graphical user interface for event prediction in trials with an event-driven design
FutRuleExample1

Simulation-based selection of an optimal futility stopping rule (normally distributed endpoint)
ClustRandExample2

Simulation-based design of a cluster-randomized trial (binary endpoint)
EventPredData

Example data set for EventPred
MultAdjExample1

Simulation-based power calculations in Phase III trials with multiple dose-placebo comparisons
MultAdjExample3

Simulation-based power calculations in Phase III trials with multiple endpoints and multiple dose-placebo comparisons
MultAdjApp

Graphical user interface for power calculations in traditional trials with multiple objectives
MultAdj

Simulation-based design of traditional trials with multiple objectives
MultAdjExample2

Simulation-based power calculations in Phase III trials with multiple endpoints
GenerateReport

Simulation report
MedianaDesigner-package

Efficient Simulation-Based Power and Sample Size Calculations for a Broad Class of Late-Stage Clinical Trials
FutRuleExample2

Simulation-based selection of an optimal futility stopping rule (binary endpoint)
FutRuleExample3

Simulation-based selection of an optimal futility stopping rule (time-to-event endpoint)
ADPopSelExample1

Simulation-based design of an adaptive trial with population selection (normally distributed endpoint)
ADPopSelExample3

Simulation-based design of an adaptive trial with population selection (time-to-event endpoint)
ADSSMod

Simulation-based design of adaptive trials with data-driven sample size or event count re-estimation
ADRandApp

Graphical user interface to design an adaptive trial with data-driven population selection
ADPopSel

Simulation-based design of adaptive trials with data-driven population selection
ADPopSelExample2

Simulation-based design of an adaptive trial with population selection (binary endpoint)
ADSSModApp

Graphical user interface to design an adaptive trial with data-driven sample size or event count re-estimation
ADPopSelApp

Graphical user interface to design an adaptive trial with data-driven population selection
ADRandExample

Simulation-based design of dose-finding Phase II trials with response-adaptive randomization (normally distributed endpoint)
ADRand

Simulation-based design of adaptive trials with response-adaptive randomization