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simdistr  

Assessment of Data Trial Distributions According to the Carlisle-Stouffer Method
View on CRAN: Click here


Download and install simdistr package within the R console
Install from CRAN:
install.packages("simdistr")

Install from Github:
library("remotes")
install_github("cran/simdistr")

Install by package version:
library("remotes")
install_version("simdistr", "1.0.1")



Attach the package and use:
library("simdistr")
Maintained by
Bernardo Sousa-Pinto
[Scholar Profile | Author Map]
First Published: 2018-07-02
Latest Update: 2019-08-02
Description:
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>.
How to cite:
Bernardo Sousa-Pinto (2018). simdistr: Assessment of Data Trial Distributions According to the Carlisle-Stouffer Method. R package version 1.0.1, https://cran.r-project.org/web/packages/simdistr. Accessed 20 Apr. 2025.
Previous versions and publish date:
1.0.0 (2018-07-02 10:40)
Other packages that cited simdistr R package
View simdistr citation profile
Other R packages that simdistr depends, imports, suggests or enhances
Complete documentation for simdistr
Functions, R codes and Examples using the simdistr R package
Some associated functions: example_trials . sim_distr . 
Some associated R codes: CarlisleStouffer.R . data_example_trials.R .  Full simdistr package functions and examples
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