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bml

Bayesian Multiple-Membership Multilevel Models with Parameterizable Weight Functions

v0.9.0 · Feb 20, 2026 · GPL-3

Description

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>.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies dplyr readr tidyr stringr R2jags ggplot2 ggmcmc coda patchwork tibble purrr rlang bml

Version History

new 0.9.0 Mar 9, 2026