multilevelcoda: Estimate Bayesian Multilevel Models for Compositional Data

Implement Bayesian Multilevel Modelling for compositional data in a multilevel framework. Compute multilevel compositional data and Isometric log ratio (ILR) at between and within-person levels, fit Bayesian multilevel models for compositional predictors and outcomes, and run post-hoc analyses such as isotemporal substitution models.

Version: 1.2.1
Depends: R (≥ 4.0.0)
Imports: stats, data.table (≥ 1.12.0), compositions, brms, bayestestR, extraoperators, ggplot2, emmeans, insight, foreach, doFuture, abind, graphics
Suggests: testthat (≥ 3.0.0), covr, withr, knitr, rmarkdown, lme4, cmdstanr (≥ 0.5.0)
Published: 2023-08-13
Author: Flora Le ORCID iD [aut, cre], Joshua F. Wiley ORCID iD [aut]
Maintainer: Flora Le <13florale at gmail.com>
BugReports: https://github.com/florale/multilevelcoda/issues
License: GPL (≥ 3)
URL: https://florale.github.io/multilevelcoda/, https://github.com/florale/multilevelcoda
NeedsCompilation: no
Additional_repositories: https://mc-stan.org/r-packages/
Materials: README NEWS
CRAN checks: multilevelcoda results

Documentation:

Reference manual: multilevelcoda.pdf
Vignettes: Introduction to Bayesian Compositional Multilevel Modelling
Multilevel Models with Compositional Predictors
Multilevel Model with Compositional Outcomes
Compositional Substitution Multilevel Models
Improving MCMC Sampling for Bayesian Compositional Multilevel Models

Downloads:

Package source: multilevelcoda_1.2.1.tar.gz
Windows binaries: r-devel: multilevelcoda_1.2.1.zip, r-release: multilevelcoda_1.2.1.zip, r-oldrel: multilevelcoda_1.2.1.zip
macOS binaries: r-release (arm64): multilevelcoda_1.2.1.tgz, r-oldrel (arm64): multilevelcoda_1.2.1.tgz, r-release (x86_64): multilevelcoda_1.2.1.tgz
Old sources: multilevelcoda archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=multilevelcoda to link to this page.