Clinical Trial Simulations

Provides a general framework for clinical trial simulations based on the Clinical Scenario Evaluation (CSE) approach. The package supports a broad class of data models (including clinical trials with continuous, binary, survival-type and count-type endpoints as well as multivariate outcomes that are based on combinations of different endpoints), analysis strategies and commonly used evaluation criteria.


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Mediana is an R package which provides a general framework for clinical trial simulations based on the Clinical Scenario Evaluation approach. The package supports a broad class of data models (including clinical trials with continuous, binary, survival-type and count-type endpoints as well as multivariate outcomes that are based on combinations of different endpoints), analysis strategies and commonly used evaluation criteria.

Find out more at http://gpaux.github.io/Mediana/ and check out the case studies.

Installation

Get the released version from CRAN:

install.packages("Mediana")

Or the development version from github:

# install.packages("devtools")
devtools::install_github("gpaux/Mediana")

When installing Mediana package, an error could occur if a java version >= 1.6 is not installed. Java is used in the ReporteRs R package which is required in the Mediana R package to generate Word report.

system("java -version") should return java version ‘1.6.0’ or greater.

In order to ensure a proper installation, it is highly recommended to install the latest version of Java in the same architecture of R (32-bit or 64-bit).

The latest version can be found at https://www.java.com/en/download/manual.jsp.

Online Manual

A detailed online manual is accessible at http://gpaux.github.io/Mediana/

News

Mediana 1.0.7

Bug fixes

  • As the ReporteRs R package is not available on the CRAN anymore, the report generation feature has been revised using the officer and flextable R packages. These packages are now required to use the GenerateReport function.

Mediana 1.0.6

New features

  • Addition of the multinomial distribution (MultinomialDist, see Analysis model).

  • Addition of the ordinal logistic regression test (OrdinalLogisticRegTest, see Analysis model).

  • Addition of the Proportion statistic (PropStat, see Analysis model).

  • Addition of the Fallback procedure (FallbackAdj, see Analysis model).

  • Addition of a function to get the analysis results generated in the CSE using the AnalysisStack function (see Analysis stack).

  • Addition of the ExtractAnalysisStack function to extract a specific set of results in an AnalysisStack object (see Analysis stack).

  • Creation of a vignette to describe the functions implementing the adjusted p-values (AdjustPvalues) and one-sided simultaneous confidence intervals (AdjustCIs).

  • Minor revisions of the generated report

  • It is now possible to use an option to specify the desirable direction of the treatment effect in a test, e.g., larger = TRUE means that numerically larger values are expected in the second sample compared to the first sample and larger = FALSE otherwise. This is an optional argument for all two-sample statistical tests to be included in the Test object. By default, if this argument is not specified, it is expected that a numerically larger value is expected in the second sample (i.e., by default larger = TRUE).

Bug fixes

  • Due to difficulties for several users to install the Mediana R package because of java issue, the ReporteRs R package is not required anymore (remove from Imports). However, to be able to generate the report, the user will require to have the ReporteRs R package installed.

  • Minor revision to the two-sample non-inferiority test for proportions to ensure that the number of successes is not greater than the sample size

Mediana 1.0.5

New features

  • Addition of the AdjustPvalues function which can be used to get adjusted p-values from a Multiple Testing Procedure. This function cannot be used within the CSE framework but it is an add-on function to compute adjusted p-values.

  • Addition of the AdjustCIs function which can be used to get simultaneous confidence intervals from a Multiple Testing Procedure. This function cannot be used within the CSE framework but it is an add-on function to simultaneous confidence intervals.

  • Creation of vignettes

Bug fixes

  • Revision of the dropout generation mechanism for time-to-event endpoints.

Mediana 1.0.4

New features

  • Addition of the Fixed-sequence procedure (FixedSeqAdj, see Analysis model).

  • Addition of the Cox method to calculate the HR, effect size and ratio of effect size for time-to-event endpoint. This can be accomplished by setting the method argument in the parameter list to set-up the calculation based on the Cox method. (par = parameters(method = "Cox"), see Analysis model).

  • Addition of the package version information in the report.

Bug fixes

  • Revision of one-sided p-value computation for Log-Rank test.

  • Revision of the call for Statistic in the core function (not visible).

  • Revision of the function to calculate the Hazard Ratio Statistic (HazardRatioStat method). By default, this calculation is now based on the log-rank statistic ((O2/E2)/(O1/E1) where O and E are Observed and Expected event in sample 2 and sample 1. A parameter can be added using the method argument in the parameter list to set-up the calculation based on the Cox method (par = parameters(method = "Cox"), see Analysis model).

  • Revision of the function to calculate the effect size for time-to-event endpoint (EffectSizeEventStat method, based on the HazardRatioStat method)

  • Revision of the functions to calculate the ratio of effect size for continuous (RatioEffectSizeContStat method), binary (RatioEffectSizePropStat method) and event (RatioEffectSizeEventStat method) endpoint.

  • Revision of the function to generate the Test, Statistic, Design and result tables in the report.

Mediana 1.0.3

New features

  • Addition of the Beta distribution (BetaDist, see Data model).

  • Addition of the Truncated exponential distribution, which could be used as enrollment distribution (TruncatedExpoDist, see Data model).

  • Addition of the Non-inferiority test for proportion (PropTestNI, see Analysis model).

  • Addition of the mixture-based gatekeeping procedure (MixtureGatekeepingAdj see Analysis model).

  • Addition of a function to get the data generated in the CSE using the DataStack function (see Data stack).

  • Addition of a function to extract a specific set of data in a DataStack object (see Data stack).

  • Addition of the "Evaluation Model" section in the generated report describing the criteria and their parameters (see Simulation report).

Bug fixes

  • Revision of the generation of dropout time.

  • Correction of the NormalParamAdj function.

  • Correction of the FisherTest function.

Reference manual

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install.packages("Mediana")

1.0.7 by Gautier Paux, 7 months ago


http://gpaux.github.io/Mediana/


Report a bug at https://github.com/gpaux/Mediana/issues


Browse source code at https://github.com/cran/Mediana


Authors: Gautier Paux , Alex Dmitrienko.


Documentation:   PDF Manual  


Task views: Clinical Trial Design, Monitoring, and Analysis


GPL-2 license


Imports doParallel, doRNG, foreach, MASS, mvtnorm, stats, survival, utils

Suggests flextable, knitr, officer, rmarkdown, pander


See at CRAN