Assessment of Data Trial Distributions According to the Carlisle-Stouffer Method R package simdistr version 1.0.1 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>. Software Depends: R (>= 2.10) Bernardo Sousa-Pinto <bernardo@med.up.pt> Comprehensive R Archive Network (CRAN) 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] GPL-2 2019-08-02 application/tgz https://CRAN.R-project.org/package=simdistr doi:10.32614/CRAN.package.simdistr