Statistical tests for the comparison between two or more alpha
    coefficients based on either dependent or independent groups of individuals.
    A web interface is available at http://comparingcronbachalphas.org. A plugin
    for the R GUI and IDE RKWard is included. Please install RKWard from https://
    rkward.kde.org to use this feature. The respective R package 'rkward' cannot be
    installed directly from a repository, as it is a part of RKWard.

Provides functions for summarizing and plotting the
	output from Markov Chain Monte Carlo (MCMC) simulations, as
	well as diagnostic tests of convergence to the equilibrium
	distribution of the Markov chain.

A minimum set of functions to perform compositional data analysis
    using the log-ratio approach introduced by John Aitchison (1982). Main functions
    have been implemented in c++ for better performance.

Meta-package for compositional data analysis. It attaches the
    main stable packages of the 'coda' ecosystem, currently 'coda.base' and
    'coda.plot', and provides helper tools to install development extensions
    from 'GitHub'.

Provides a collection of easy-to-use functions for creating 
    visualizations of compositional data using 'ggplot2'. Includes support 
    for common plotting techniques in compositional data analysis.

Functions for microbiome data analysis that take into account its compositional nature. Performs variable selection through penalized regression for both, cross-sectional and longitudinal studies, and for binary and continuous outcomes.

In the context of high-throughput genetic data,
    CoDaCoRe identifies a set of sparse biomarkers that are
    predictive of a response variable of interest (Gordon-Rodriguez 
    et al., 2021) <doi:10.1093/bioinformatics/btab645>. More 
    generally, CoDaCoRe can be applied to any regression problem 
    where the independent variable is Compositional (CoDa), to 
    derive a set of scale-invariant log-ratios (ILR or SLR) that 
    are maximally associated to a dependent variable.