localhierarchy

Background

Bayesian hierarchical models are widely used in global health estimation, where data availability may vary across national or subnational populations. Such models are typically fitted to a global database, e.g., to produce national-level estimates for all countries in the world or in some region. To facilitate analysis at a local level, models are often desirable that are informed by global models but can be fitted to just a subset of the data, such as data for one country. We refer to such models as local models: models that are derived from global hierarchical models but adapted such that they can be fitted to the data from one population alone.

The localhierarchy R package provides functionality for fitting Bayesian hierarchical models in settings where both global and local estimation is required. The package provides R functions and Stan model components to support global modeling, in which all parameters in hierarchical models are estimated, and local modeling, in which parameters are estimated for only one or a small number of populations, using fixed values from a global model fit.

The article on this website presents a practical introduction to the package for the applied user and illustrates the package’s functionality through examples for national estimation.

Installation

• localhierarchy depends on cmdstanr: Instructions for installing cmdstanr are available in their Getting started guide.

• Install localhierarchy from Github: remotes::install_github("AlkemaLab/localhierarchy")

Examples

See article on package website, at https://alkemalab.github.io/localhierarchy.

Citation

Please cite as follows:

citation("localhierarchy")
#> To cite package 'localhierarchy' in publications use:
#> 
#>   Alkema L, Mooney S, Ray E, Susmann H (2025). _localhierarchy: An R
#>   package to facilitate fitting of global and local Bayesian
#>   hierarchical models_. R package version 0.9,
#>   <https://github.com/AlkemaLab/localhierarchy>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {localhierarchy: An R package to facilitate fitting of global and local Bayesian hierarchical models},
#>     author = {Leontine Alkema and Shauna Mooney and Evan Ray and Herbert Susmann},
#>     year = {2025},
#>     note = {R package version 0.9},
#>     url = {https://github.com/AlkemaLab/localhierarchy},
#>   }

Funding

This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation (INV-00844).