R Observatory: Metrics for easyRaschBayes version 0.3.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

easyRaschBayes

0.3.0Package record

Bayesian Rasch Analysis Using 'brms'

0packages depend

3.7Kdownloads / year

0.0%test coverage

13/13flavors OK

Overview

About

Maintained by Magnus JohanssonCRAN page ↗GitHub ↗Website ↗Issues ↗

Reproduces classic Rasch psychometric analysis features using Bayesian item response theory models fitted with 'brms' following Bürkner (2021) doi:10.18637/jss.v100.i05 and Bürkner (2020) doi:10.3390/jintelligence8010005. Supports both dichotomous and polytomous Rasch models. Features include posterior predictive item fit, conditional infit, item-restscore associations, person fit, differential item functioning, local dependence assessment via Q3 residual correlations, dimensionality assessment with residual principal components analysis, person-item targeting plots, item category probability curves, and reliability using relative measurement uncertainty following Bignardi et al. (2025) doi:10.31234/osf.io/h54k8_v1.

Changes in 0.3.0

New custom brms family hurdle_acat for hurdle partial credit models (H-PCM). This is written by Kristoffer Magnusson
Several adapted (experimental) functions for H-PCM, all using the *_hpcm suffix.
infit_statistic_hpcm()
q3_statistic_hpcm()
item_parameters_hpcm()
person_parameters_hpcm()
RMUreliability_hpcm()
plot_icc_hpcm()
plot_targeting_hpcm()
Bug fix - changed post processing functions to use median_hdci() instead of median_hdi() to avoid issues with multimodal posteriors.

Show all changes in 0.3.0Hide the rest of the changes in 0.3.0

Bug fix - corrected the WLE person estimates in person_parameters() and person_parameters_hpcm(). The polytomous Warm bias correction had the wrong sign, biasing estimates outward; WLE now matches catR/TAM. Extreme (minimum and maximum) scores now receive proper finite WLE estimates instead of being clamped to the theta_range bounds.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("easyRaschBayes", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("pgmj/easyRaschBayes")

Development version from pgmj/easyRaschBayes. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-easyraschbayes

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-easyRaschBayes

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-easyRaschBayes

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 4.0 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK8 OK2026-03-12

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.3.0

READMEYes · 438 wordsVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 0.3.0Citation fileNoWebsiteYes · pkgdown

Description cites a JSS article

Help pages: 36 (8 internal)includes a package overview page
Examples that run: 14%3 run in a plain check · 13 only when donttest examples are enabled (R CMD check --as-cran) · 5 never run
Exported functions with examples: 66%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 61%

Vignettes (1)

Rasch Partial Credit Model HTML

How these are measured

Downloads

3.7K

CRAN downloads in the past year

Rank #9,820 · ~10/day · ~305/mo

Releases R versions

Daily download trend is not available in this view yet.

36730 days

1K90 days

3.7K1 year

Compare downloads with other packages →

Also on67 r2u3 autocran

How downloads are counted

Repository

pgmj/easyraschbayes ↗Account: pgmj

0Stars

0Forks

0Open issues

0Open PRs

3Releases

65Commits

2Commit identities

License file reads as GPL-3.0 · 65 commits · Last activity 2026-06-18

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: not measured
Median days to close, 50 most recently updated closed PRs: 0

Releases over time

2026-03-28 · 12026-07-07 · 3

How these are measured

PracticesBeta

6 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/pgmj/easyraschbayes on 2026-10-22.

Continuous integration (1)

GitHub Actions

Docs source (3)

pkgdown

GitHub Pages site last deployed 2026-06-18 · The repository has a site deploy workflow

pkgdown site last built 2026-06-18

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

How this is detected·Detection ruleset v4 (2026-10-20)

AI coding toolsBeta

This repository shows signs of AI coding tools.

GitHub Copilotfirst seen 2026-02-27
Pull request: opened by its own account
Commits: 10 by its own account
Claude Codefirst seen 2026-06-15
Named in .Rbuildignore: .claude

Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

14 external dependencies (excludes base and recommended)

Installing easyRaschBayes adds 73 packages (35 with compiled code, 75 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (1)

R >= 4.1.0

Imports (10)

brms rlang dplyr tidyr tibble ggdiststatsgrDevicesggplot2 forcats

LinkingTo (0)

none

Suggests (6)

ggrepel patchwork eRm testthat knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (3)

Magnus Johansson

Author, Maintainer since 0.1.0 (2026)

Giacomo Bignardi

Contributor

RMU reliability code

Kristoffer Magnusson

Contributor · added in 0.3.0

hurdle_acat custom brms family

Releases (4)

Pick two releases to compare their code metrics.

0.3.0Latest
record
2026-06-18 · current release · diff ↗ ·
added 12 exports
RMUreliability_hpcm, hurdle_acat, hurdle_acat_stanvars, infit_statistic_hpcm, item_parameters_hpcm, log_lik_hurdle_acat, person_parameters_hpcm, plot_icc_hpcm, plot_targeting_hpcm, posterior_epred_hurdle_acat, posterior_predict_hurdle_acat, q3_statistic_hpcm
R
R 4.6.0 released · 2026-04-24
0.2.0.1
record
2026-03-28 · diff ↗
0.2.0
record
2026-03-28 · diff ↗ ·
added 10 exports
infit_post, item_parameters, item_restscore_post, person_parameters, plot_bars, plot_icc, plot_stackedbars, plot_tile, posterior_to_prior, q3_post
0.1.0
record
2026-03-11
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2026-03-11
Total releases: 4 / 1 yrs
License: GPL (>= 3) OSI
Minimum R: ≥ 4.1.0
Download size: 694 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("easyRaschBayes")

Format

Johansson, M., Bignardi, G., & Magnusson, K. (2026). easyRaschBayes: Bayesian Rasch Analysis Using 'brms' (Version 0.3.0) [Computer software]. https://doi.org/10.32614/CRAN.package.easyRaschBayes

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for easyRaschBayes version 0.3.0 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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