Package: simdistr 1.0.1

Bernardo Sousa-Pinto

simdistr: Assessment of Data Trial Distributions According to the Carlisle-Stouffer Method

Assessment of the distributions of baseline continuous and categorical variables in randomised trials. This method is based on the Carlisle-Stouffer method with Monte Carlo simulations. It calculates p-values for each trial baseline variable, as well as combined p-values for each trial - these p-values measure how compatible are distributions of trials baseline variables with random sampling. This package also allows for graphically plotting the cumulative frequencies of computed p-values. Please note that code was partly adapted from Carlisle JB, Loadsman JA. (2017) <doi:10.1111/anae.13650>.

Authors:Bernardo Sousa-Pinto [aut, cre], Joao Julio Cerqueira [ctb], Cristina Costa-Santos [ctb], John B Carlisle [ctb], John A Loadsman [ctb], Armando Teixeira-Pinto [aut], Hernani Goncalves [aut]

simdistr_1.0.1.tar.gz
simdistr_1.0.1.tar.gz(r-4.5-noble)simdistr_1.0.1.tar.gz(r-4.4-noble)
simdistr_1.0.1.tgz(r-4.4-emscripten)simdistr_1.0.1.tgz(r-4.3-emscripten)
simdistr.pdf |simdistr.html✨
simdistr/json (API)
NEWS

# Install 'simdistr' in R:
install.packages('simdistr', repos = 'https://cloud.r-project.org')
Datasets:
  • example_trials - Data of baseline variables of seven randomised trials.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 116 downloads 1 exports 0 dependencies

Last updated 6 years agofrom:3d00296d21. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 27 2025
R-4.5-linuxOKMar 27 2025
R-4.4-linuxOKMar 27 2025

Exports:sim_distr

Dependencies:

Citation

To cite package ‘simdistr’ in publications use:

Sousa-Pinto B, Teixeira-Pinto A, Goncalves H (2019). simdistr: Assessment of Data Trial Distributions According to the Carlisle-Stouffer Method. R package version 1.0.1, https://CRAN.R-project.org/package=simdistr.

Corresponding BibTeX entry: 

  @Manual{,
    title = {simdistr: Assessment of Data Trial Distributions According
      to the Carlisle-Stouffer Method},
    author = {Bernardo Sousa-Pinto and Armando Teixeira-Pinto and
      Hernani Goncalves},
    year = {2019},
    note = {R package version 1.0.1},
    url = {https://CRAN.R-project.org/package=simdistr},
  }