hbamr: Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan'

Perform hierarchical Bayesian Aldrich-McKelvey scaling using Hamiltonian Monte Carlo via 'Stan'. Aldrich-McKelvey ('AM') scaling is a method for estimating the ideological positions of survey respondents and political actors on a common scale using positional survey data. The hierarchical versions of the Bayesian 'AM' model included in this package outperform other versions both in terms of yielding meaningful posterior distributions for respondent positions and in terms of recovering true respondent positions in simulations. The package contains functions for preparing data, fitting models, extracting estimates, plotting key results, and comparing models using cross-validation. The original version of the default model is described in Bølstad (2024) <doi:10.1017/pan.2023.18>.

Package details

AuthorJørgen Bølstad [aut, cre] (<https://orcid.org/0000-0002-7623-5741>)
MaintainerJørgen Bølstad <jorgen.bolstad@stv.uio.no>
LicenseGPL (>= 3)
URL https://jbolstad.github.io/hbamr/
Package repositoryView on CRAN
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hbamr documentation built on June 22, 2024, 9:28 a.m.