Package: multilevelcoda 1.3.3

multilevelcoda: Estimate Bayesian Multilevel Models for Compositional Data

Implement Bayesian multilevel modelling for compositional data. Compute multilevel compositional data and perform log-ratio transforms 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. References: Le, Stanford, Dumuid, and Wiley (2025) <doi:10.1037/met0000750>, Le, Dumuid, Stanford, and Wiley (2025) <doi:10.1080/00273171.2025.2565598>.

Authors:Flora Le [aut, cre], Joshua F. Wiley [aut]

multilevelcoda_1.3.3.tar.gz
multilevelcoda_1.3.3.zip(r-4.7)multilevelcoda_1.3.3.zip(r-4.6)multilevelcoda_1.3.3.zip(r-4.5)
multilevelcoda_1.3.3.tgz(r-4.6-any)multilevelcoda_1.3.3.tgz(r-4.5-any)
multilevelcoda_1.3.3.tar.gz(r-4.7-any)multilevelcoda_1.3.3.tar.gz(r-4.6-any)
multilevelcoda_1.3.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
multilevelcoda/json (API)

# Install 'multilevelcoda' in R:

install.packages('multilevelcoda', repos = c('https://florale.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/florale/multilevelcoda/issues

Pkgdown/docs site:https://florale.github.io

Datasets:

mcompd - Multilevel Compositional Data
psub - Possible Pairwise Substitutions
sbp - Sequential Binary Partition
sim - Multilevelcoda Simulation Study results

On CRAN:

bayesian-inference compositional-data-analysis multilevel-models multilevelcoda

8.62 score 23 stars 166 scripts 279 downloads 41 exports 138 dependencies

Last updated from:3ea3a7f75a. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	339
source / vignettes	OK	314
linux-release-x86_64	OK	360
macos-release-arm64	OK	227
macos-oldrel-arm64	OK	250
windows-devel	OK	297
windows-release	OK	283
windows-oldrel	OK	278
wasm-release	OK	196

Exports:as.complr as.diagnostics brmcoda bsub bsubmargin build.base build.rg build.sbp compilr complr diagnostics fixef gen_beta gen_binomial gen_categorical gen_custom gen_gamma gen_mvn gen_negbin gen_outcome gen_poisson gen_template get_sbp get_variables is.brmcoda is.complr is.diagnostics is.substitution multilevelcoda_sim pivot_coord pivot_coord_refit pivot_coord_rotate prep_sim_analysis ranef simulate_data sub submargin substitution VarCorr wsub wsubmargin

Dependencies:abind askpass backports base64enc bayesm bayesplot BH bridgesampling brms Brobdingnag bslib cachem callr checkmate cli coda codetools colourpicker commonmark compositions cpp11 crosstalk curl data.table DEoptimR desc digest distributional doFuture dplyr DT dygraphs emmeans estimability evaluate extraoperators farver fastmap fontawesome foreach fs future future.apply generics ggplot2 ggridges globals glue gridExtra gtable gtools highr htmltools htmlwidgets httpuv httr igraph inline isoband iterators jquerylib jsonlite knitr labeling later lattice lazyeval lifecycle listenv litedown loo magrittr markdown MASS Matrix matrixStats memoise mgcv mime miniUI mvtnorm nleqslv nlme numDeriv openssl otel parallelly pillar pkgbuild pkgconfig plotly plyr posterior processx promises ps purrr QuickJSR R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel reshape2 rlang rmarkdown robustbase rstan rstantools S7 sass scales shiny shinyjs shinystan shinythemes sourcetools StanHeaders stringi stringr sys tensorA threejs tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun xtable xts yaml zoo

Data Simulation

Rendered fromF-data-simulation.Rmdusingknitr::rmarkdown

Last update: 2026-05-26
Started: 2026-05-22

Compositional Substitution Multilevel Analysis

Intro | Fitting main model | Substitution models | Basic Substitution Analysis | Average Marginal Substitution Effects

Rendered fromD-substitution.Rmdusingknitr::rmarkdown

Last update: 2025-09-12
Started: 2024-05-26

Multilevel Model with Compositional Outcomes

Multilevel model with compositional outcomes. | Computing compositions and isometric log ratio coordinates. | Fitting model | Bayes Factor for compositional multilevel modelling

Rendered fromC-composition-MMLM.Rmdusingknitr::rmarkdown

Last update: 2025-09-12
Started: 2023-08-04

Multilevel Models with Compositional Predictors

Rendered fromB-composition-MLM.Rmdusingknitr::rmarkdown

Last update: 2025-09-12
Started: 2023-08-04

Improving MCMC Sampling for Bayesian Compositional Multilevel Models

Rendered fromE-simmodel-diag.Rmdusingknitr::rmarkdown

Last update: 2024-11-18
Started: 2023-08-08

Introduction to Bayesian Compositional Multilevel Modelling

Compositional Data Analysis | Multilevel Modelling for Compositional Data

Rendered fromA-introduction.Rmdusingknitr::rmarkdown

Last update: 2024-05-26
Started: 2023-07-27

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Mean and Variance of compositions presented in a 'complr' object.	.meanvar.complr
Coerce a list to a 'complr' object	as.complr
Extract amounts and compositions in conventional formats as data.frames, matrices, or arrays.	as.data.frame.complr as.matrix.complr
Coerce a list to a 'diagnostics' object	as.diagnostics
Bayes Factors from Marginal Likelihoods	bayes_factor.brmcoda
Fit Bayesian generalised (non-)linear multilevel compositional model via full Bayesian inference	brmcoda
Between-person Simple Substitution	bsub
Between-person Average Substitution	bsubmargin
Build Base Pairwise Substitution	build.base
Reference Grid for 'substitution' model.	build.rg
Build Sequential Binary Partition	build.sbp
Model Coefficients	coef coef.brmcoda
Indices from a (dataset of) Multilevel Composition(s) (deprecated.)	compilr
Indices from a (dataset of) Multilevel Composition(s)	complr
Generate Positive and Bounded Continuous Variables	continuous-generators gen_beta gen_gamma
Generate Count Variables	count-generators gen_binomial gen_negbin gen_poisson
Extract Diagnostic Quantities from 'brmsfit' Models in 'brmcoda'	diagnostic-quantities-brmcoda log_posterior log_posterior.brmcoda neff_ratio neff_ratio.brmcoda nuts_params nuts_params.brmcoda rhat rhat.brmcoda
Generic diagnostics function for 'multilevelcoda'	diagnostics
Robust multivariate normal diagnostics for 'complr' coordinates	diagnostics.complr
Index 'brmcoda' objects	draws-index-brmcoda nchains nchains.brmcoda ndraws ndraws.brmcoda niterations niterations.brmcoda nvariables nvariables.brmcoda variables variables.brmcoda
Expected Values of the Posterior Predictive Distribution	fitted fitted.brmcoda
Population-Level Estimates	fixef fixef.brmcoda
Generate Categorical Variables	gen_categorical
Generate Variables with a User-Supplied Function	gen_custom
Generate Normal, Multivariate Normal, and Compositional Variables	gen_mvn
Generate Dynamic Gaussian and Compositional Outcomes	gen_outcome
Create a Parameter Template for 'gen_outcome()'	gen_template
Extract Sequential Binary Partition from a 'complr' object.	get_sbp
Extract variable names from an object	get_variables get_variables.brmcoda get_variables.complr
Substitution analysis helper functions	get-substitution
Checks if argument is a 'brmcoda' object	is.brmcoda
Checks if argument is a 'complr' object	is.complr
Checks if argument is a 'diagnostics' object	is.diagnostics
Checks if argument is a 'substitution' object	is.substitution
Interface to 'shinystan'	launch_shinystan launch_shinystan.brmcoda
Efficient approximate leave-one-out cross-validation (LOO)	loo loo.brmcoda
MCMC Plots Implemented in 'bayesplot'	mcmc_plot.brmcoda
Multilevel Compositional Data	mcompd
Mean amounts and mean compositions presented in a 'complr' object.	mean.complr
Extracting the Model Frame from a Formula or Fit from 'brmcoda' object	model.frame.brmcoda
multilevelcoda Simulation Study Results	multilevelcoda_sim
Extract Number of Observations from 'brmcoda' object	nobs.brmcoda
Create a matrix of output plots from a 'brmcoda''s 'brmsfit' object	pairs.brmcoda
Estimate pivot balance coordinates	pivot_coord
Estimate pivot balance coordinates by refitting model.	pivot_coord_refit
Estimate pivot balance coordinates by rotating sequential binary partition.	pivot_coord_rotate
Trace and Density Plots for MCMC Draws plot	plot.brmcoda
Diagnostics Plot for Compositional Diagnostics	plot.diagnostics
Substitution Plot	plot.substitution
Posterior Predictive Checks for 'brmcoda' Objects	pp_check pp_check.brmcoda
Draws from the Posterior Predictive Distribution	predict predict.brmcoda
Prepare Simulated Outcome Data for Analysis	prep_sim_analysis
Print a Summary for a fitted 'brmsfit' model in a 'brmcoda' object	print.brmcoda
Print a Summary for a 'complr' object	print.complr
Print Simulated Data	print.mlsim_data
Print a Summary for a 'substitution' object	print.substitution
Print a Simulated Data Summary	print.summary.mlsim_data
Extract Priors of a 'brmsfit' from a 'brmcoda' object	prior_summary.brmcoda
Possible Pairwise Substitutions	psub
Group-Level Estimates	ranef ranef.brmcoda
Posterior Draws of Residuals/Predictive Errors	residuals.brmcoda
Sequential Binary Partition	sbp
multilevelcoda Simulation Study results	sim
Simulate Data from Generator Specifications	simulate_data
Simple Substitution	sub
Average Substitution	submargin
Multilevel Compositional Substitution Analysis	substitution
Create a Summary of a fitted 'brmsfit' model in a 'brmcoda' object	summary.brmcoda
Create a Summary of a 'complr' object	summary.complr
Summarize Simulated Data	summary.mlsim_data
Create a Summary of a fitted 'brmsfit' model from a 'pivot_coord' object	summary.pivot_coord
Create a Summary of a Substitution Model represented by a 'substitution' object	summary.substitution
Update 'brmcoda' models	update.brmcoda
Variance of compositions presented in a 'complr' object.	var.complr
Extract Variance and Correlation Components	VarCorr VarCorr.brmcoda
Covariance and Correlation Matrix of Population-Level Effects	vcov.brmcoda
Within-person Simple Substitution	wsub
Within-person Average Substitution	wsubmargin