Data

Tools

Indexes

Applications

Experiments

Open Source Science

multilevelcoda

multilevelcoda R package for Bayesian multilevel compositional data analysis

https://github.com/florale/multilevelcoda

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 10 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.3%) to scientific vocabulary

Keywords

bayesian-inference compositional-data-analysis multilevel-models multilevelcoda r r-package
Last synced: 6 months ago · JSON representation

Repository

multilevelcoda R package for Bayesian multilevel compositional data analysis

Basic Info
Statistics
  • Stars: 19
  • Watchers: 2
  • Forks: 2
  • Open Issues: 0
  • Releases: 5
Topics
bayesian-inference compositional-data-analysis multilevel-models multilevelcoda r r-package
Created about 4 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog License

README.md

multilevelcoda

R-CMD-check CRAN Version lifecycle <!-- Coverage Status --> <!-- badges: end -->

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

```r install.packages("multilevelcoda")

```

The current developmental version can be downloaded from github via

r 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:

Citing multilevelcoda and related software

When using multilevelcoda, please cite one or more of the following publications:

  • Le, F., Stanford, T. E., Dumuid, D., & Wiley, J. F. (2025). Bayesian multilevel compositional data analysis: introduction, evaluation, and application. Psychological Methods. https://doi.org/10.1037/met0000750
  • Le F., Dumuid D., Stanford T. E., Wiley J. F. (2024). Bayesian multilevel compositional data analysis with the R package multilevelcoda. arXiv preprint arXiv:2411.12407.

As multilevelcoda depends on brms and Stan, please also consider citing:

  • Bürkner P. C. (2017). brms: An R Package for Bayesian Multilevel Models using Stan. Journal of Statistical Software. 80(1), 1-28. doi.org/10.18637/jss.v080.i01
  • Bürkner P. C. (2018). Advanced Bayesian Multilevel Modeling with the R Package brms. The R Journal. 10(1), 395-411. doi.org/10.32614/RJ-2018-017
  • Bürkner P. C. (2021). Bayesian Item Response Modeling in R with brms and Stan. Journal of Statistical Software, 100(5), 1-54. doi.org/10.18637/jss.v100.i05
  • Stan Development Team. YEAR. Stan Modeling Language Users Guide and Reference Manual, VERSION. https://mc-stan.org
  • Carpenter B., Gelman A., Hoffman M. D., Lee D., Goodrich B., Betancourt M., Brubaker M., Guo J., Li P., and Riddell A. (2017). Stan: A probabilistic programming language. Journal of Statistical Software. 76(1). doi.org/10.18637/jss.v076.i01

Owner

  • Name: Flora
  • Login: florale
  • Kind: user
  • Location: Melbourne, Australia
  • Company: Monash University

A psychology PhD student diving into the world of coding. Sometimes I drown, sometimes I float, and sometimes I find answers.

GitHub Events

Total
  • Issues event: 3
  • Watch event: 7
  • Delete event: 1
  • Issue comment event: 8
  • Push event: 68
Last Year
  • Issues event: 3
  • Watch event: 7
  • Delete event: 1
  • Issue comment event: 8
  • Push event: 68

Committers

Last synced: 10 months ago

All Time
  • Total Commits: 563
  • Total Committers: 3
  • Avg Commits per committer: 187.667
  • Development Distribution Score (DDS): 0.05
Past Year
  • Commits: 73
  • Committers: 2
  • Avg Commits per committer: 36.5
  • Development Distribution Score (DDS): 0.11
Top Committers
Name Email Commits
Flora Le f****e@m****u 535
Joshua F. Wiley, Ph.D j****h@g****m 27
Paul-Christian Bürkner p****r@g****m 1
Committer Domains (Top 20 + Academic)
monash.edu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 5
  • Total pull requests: 1
  • Average time to close issues: 3 months
  • Average time to close pull requests: 5 days
  • Total issue authors: 4
  • Total pull request authors: 1
  • Average comments per issue: 3.2
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 6.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • LonelyHunter2 (2)
  • barracuda156 (1)
  • evasqin (1)
  • margauxw (1)
Pull Request Authors
  • paul-buerkner (2)
Top Labels
Issue Labels
question (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 520 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 10
  • Total maintainers: 1
cran.r-project.org: multilevelcoda

Estimate Bayesian Multilevel Models for Compositional Data

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 520 Last month
Rankings
Stargazers count: 22.5%
Forks count: 28.8%
Dependent packages count: 29.8%
Average: 35.3%
Dependent repos count: 35.5%
Downloads: 60.0%
Maintainers (1)
floralebui@gmail.com
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.0.0 depends
  • bayestestR * imports
  • brms * imports
  • compositions * imports
  • cowplot * imports
  • data.table >= 1.12.0 imports
  • emmeans * imports
  • extraoperators * imports
  • foreach * imports
  • ggplot2 * imports
  • ggsci * imports
  • insight * imports
  • methods * imports
  • reshape2 * imports
  • stats * imports
  • tidyr * imports
  • zCompositions * imports
  • covr * suggests
  • doFuture * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat >= 3.0.0 suggests
  • withr * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • n1hility/cancel-previous-runs v2 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pkgdown.yaml actions
  • JamesIves/github-pages-deploy-action v4.4.1 composite
  • actions/checkout v3 composite
  • n1hility/cancel-previous-runs v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v3 composite
  • n1hility/cancel-previous-runs v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite