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:
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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- example_trials - Data of baseline variables of seven randomised trials.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:3d00296d21. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-linux | OK | Nov 01 2024 |
Exports:sim_distr
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Data of baseline variables of seven randomised trials. | example_trials |
| Assessment of Data Trial Distributions According to the Carlisle-Stouffer Method | sim_distr |