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Implements Bayesian multiple-membership multilevel models with parameterizable weight functions via 'JAGS' to model how lower-level units jointly shape higher-level outcomes (micro-macro link) across a range of outcome types (e.g., linear, logit, and survival models). Supports estimation and comparison of alternative aggregation mechanisms, allows weight matrices to be endogenized through parameters and covariates, and accommodates complex dependence structures that extend beyond traditional multilevel frameworks. For details, see Rosche (2026) "A Multilevel Model for Coalition Governments. Uncovering Party-Level Dependencies Within and Between Governments" <doi:10.31235/osf.io/4bafr_v2>.
| Version: | 0.9.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | dplyr, readr, tidyr, stringr, R2jags, ggplot2, ggmcmc, coda, patchwork, tibble, purrr, rlang |
| Suggests: | rmarkdown, knitr, testthat (≥ 3.0.0), rjags |
| Published: | 2026-02-20 |
| DOI: | 10.32614/CRAN.package.bml (may not be active yet) |
| Author: | Benjamin Rosche |
| Maintainer: | Benjamin Rosche <benrosche at nyu.edu> |
| BugReports: | https://github.com/benrosche/bml/issues |
| License: | GPL-3 |
| URL: | https://benrosche.github.io/bml/ |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | bml results |
| Reference manual: | bml.html , bml.pdf |
| Vignettes: |
Getting Started with bml (source, R code) Examples (source, R code) Frequently Asked Questions (source, R code) Installation (source, R code) Model Structure (source, R code) |
| Package source: | bml_0.9.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): bml_0.9.0.tgz, r-oldrel (arm64): bml_0.9.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available |
Please use the canonical form https://CRAN.R-project.org/package=bml to link to this page.
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.