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>.

Version: 1.0.1
Depends: R (≥ 2.10)
Published: 2019-08-02
Author: 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]
Maintainer: Bernardo Sousa-Pinto <bernardo at med.up.pt>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
CRAN checks: simdistr results

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Reference manual: simdistr.pdf
Package source: simdistr_1.0.1.tar.gz
Windows binaries: r-devel: simdistr_1.0.1.zip, r-release: simdistr_1.0.1.zip, r-oldrel: simdistr_1.0.1.zip
OS X binaries: r-release: simdistr_1.0.1.tgz, r-oldrel: simdistr_1.0.1.tgz
Old sources: simdistr archive

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