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multilevelcoda

Overview

This package provides functions to model compositional data in a multilevel framework using full Bayesian inference. It integrates the principes of Compositional Data Analysis (CoDA) and Multilevel Modelling and supports both compositional data as an outcome and predictors in a wide range of generalized (non-)linear multivariate multilevel models.

Installation

To install the latest release version from CRAN, run

install.packages("multilevelcoda")

The current developmental version can be downloaded from github via

if (!requireNamespace("remotes")) {
  install.packages("remotes")
}
remotes::install_github("florale/multilevelcoda")

Because multilevelcoda is built on brms, which is based on Stan, a C++ compiler is required. The program Rtools (available on https://cran.r-project.org/bin/windows/Rtools/) comes with a C++ compiler for Windows. On Mac, Xcode is required. For further instructions on how to get the compilers running, see the prerequisites section on https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started.

Resources

You can learn about the package from these vignettes:

• Introduction to Compositional Multilevel Modelling
• Multilevel Models with Compositional Predictors
• Multilevel Models with Compositional Outcome
• Compositional Substitution Multilevel Analysis

Citing multilevelcoda and related software

TBA

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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