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Multidimensional Item Response Theory

44packages dependsuggested by 27
134.1Kdownloads / year
0.0%test coverage
13/13flavors OK

Overview

About

Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) doi:10.18637/jss.v048.i06). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.

Changes in 1.48
  • itemstats() gains ts_fun argument to indicate how the composite score should be formed
  • empirical.plot() gains other type inputs: discrim to plot reduced item-total correlations, difficulty to plot the item means, discrim_diff to produced a bivariate plot, alpha_rm for item-removal behaviour on coefficient alpha, and freq for bar-chart frequencies per item. The first three can be accompanied by a sort logical
  • empirical.plot() gains an org.data argument to substitute un-scored data in when building empirical trace-lines. Useful for simple distractor analysis visualization, where now the scored key(s) are auto-detected and plotted with higher contrast
  • Maximum EM iteration limit warning decreased to message() instead. However, if last iteration had Aitken-accelerated criterion discrepancies greater than 1e-3 then a warning will be raised to indicate that the EM algorithm is likely still climbing

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 8.8 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-26
  • NOTE11 OK, 2 NOTE2026-08-22
  • ERROR6 OK, 3 NOTE, 4 ERROR2026-08-21
  • NOTE11 OK, 2 NOTE2026-07-16
  • OK13 OK2026-05-02
Show 4 earlier changesHide 4 earlier changes
  • ERROR11 OK, 1 ERROR2026-04-25
  • NOTE12 OK, 2 NOTE2026-04-22
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.48
READMEYes · 519 wordsVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 1.48Citation fileYes · cites a publicationWebsiteYes · pkgdown
Cites a JSS article
Help pages
96includes a package overview page
Examples that run
25%21 run in a plain check · 63 only when donttest examples are enabled (R CMD check --as-cran) · 1 never run
Exported functions with examples
100%
Documented parameters
95%
Return-value docs
33%
Help pages citing references
88%

Downloads

134.1K
CRAN downloads in the past year
Rank #1,082 · ~367/day · ~11.2K/mo
Daily download trend is not available in this view yet.
14.2K30 days
34.6K90 days
134.1K1 year
Compare downloads with other packages →
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Repository

235Stars
88Forks
1Open issues
0Open PRs
32Releases
3,463Commits
19Commit identities
irtmirtr
3,463 commits · Last activity 2026-10-23 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
55%
Median days to close, 50 most recently updated closed issues
0
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2025-10-17 · 2222026-09-16 · 235
PracticesBeta

7 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/philchalmers/mirt on 2026-10-21.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux

Docs source (3)
pkgdown

GitHub Pages site last deployed 2026-10-06 · The repository has a site deploy workflow

pkgdown site last built 2026-10-06

Reproducibility and dev environment (1)
Makefile
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
23 external dependencies (excludes base and recommended)

Installing mirt adds 63 packages (30 with compiled code, 27 MB of source tarballs). Heaviest: SimDesign 2.4 MB, Rcpp 1.8 MB, GPArotation 1.6 MB.

Depends (5)
R >= 4.1.0statsstats4latticemethods
LinkingTo (2)
Enhances (0)
none

Datasets

People & History

People (12)
Author, Maintainer since 0.1-13 (2011)
Contributor · added in 1.15
Contributor · added in 1.46.1
Contributor · added in 1.15
Contributor · added in 1.26.1
Contributor · added in 1.27.1
Contributor · added in 1.17
Contributor · added in 1.28
Contributor · added in 3.0.2
Show 3 more contributorsHide 3 contributors
Contributor · added in 1.6.1
Contributor · added in 1.26.1
Contributor · added in 1.3
Releases (84)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • R
    R 3.3.0 released · 2016-05-03
  • R
    R 3.2.0 released · 2015-04-16
  • R
    R 3.1.0 released · 2014-04-10
  • 3.0.3Latest
    record
    2014-02-20 · current release · diff ↗
  • 3.0.2
    record
    2013-08-30 · diff ↗ ·
    removed 2 exports
    confmirt, confmirt.model
    added 4 exports
    PLCI.mirt, expected.item, mirt.model, mirtCluster
  • 3.0.1
    record
    2013-04-20 · diff ↗ ·
    added 1 export
    createItem
Show 85 earlier eventsHide 85 earlier events
Across CRAN, the median accepted release of the past year spent 23 hours in the queue, 90% under 11 days.How queue time is measured

Package metadata

First published
2011-07-02
Total releases
84 / 15 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.1.0
Bundled data
72 KB / 10 files
Download size
799 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("mirt")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.18637/jss.v048.i06.

Cite the R Observatory

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

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mirt version 1.48 [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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