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]

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simdistr.pdf |simdistr.html
simdistr/json (API)
NEWS

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

Peer review:

Datasets:
  • example_trials - Data of baseline variables of seven randomised trials.

On CRAN:

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

1.00 score 2 scripts 111 downloads 1 exports 0 dependencies

Last updated 5 years agofrom:3d00296d21. Checks:OK: 7. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 07 2024
R-4.5-winOKOct 07 2024
R-4.5-linuxOKOct 07 2024
R-4.4-winOKOct 07 2024
R-4.4-macOKOct 07 2024
R-4.3-winOKOct 07 2024
R-4.3-macOKOct 07 2024

Exports:sim_distr

Dependencies: