https://github.com/kosukeimai/emIRT

emIRT: EM Algorithms for Estimating Item Response Theory Models
https://github.com/kosukeimai/emIRT

Last synced: 16 days ago
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emIRT: EM Algorithms for Estimating Item Response Theory Models

• Host: GitHub
• URL: https://github.com/kosukeimai/emIRT
• Owner: kosukeimai
• Created: 2015-09-08T19:32:10.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2024-07-05T08:47:53.000Z (4 months ago)
• Last Synced: 2024-08-01T00:38:48.011Z (3 months ago)
• Language: C++
• Size: 2.1 MB
• Stars: 25
• Watchers: 11
• Forks: 11
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Changelog: ChangeLog

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README

        
# emIRT: EM Algorithms for Estimating Item Response Theory Models [![Build Status](https://travis-ci.org/kosukeimai/emIRT.svg?branch=master)](https://travis-ci.org/kosukeimai/emIRT)  [![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/emIRT)](https://cran.r-project.org/package=emIRT) ![CRAN downloads](http://cranlogs.r-pkg.org/badges/grand-total/emIRT)

Various Expectation-Maximization (EM) algorithms are implemented for item

response theory (IRT) models. The current implementation includes IRT models for

binary and ordinal responses, along with dynamic and hierarchical IRT models

with binary responses. Variational algorithms for scaling network and text data

are also included.  The details about the methods implemented in this package are 

described in Imai, Lo, and Olmsted. (2016). "[Fast Estimation of Ideal Points with Massive Data.](https://imai.fas.harvard.edu/research/fastideal.html)" *American Political Science Review*, 

Vol. 110, No. 4 (December), pp. 631-656.

The current release of the R package is available on

[CRAN](https://cran.r-project.org/web/packages/emIRT/).

The github versions of the R package are available with

    library("devtools")

    install_github("kosukeimai/emIRT")

    install_github("kosukeimai/emIRT", ref ="development")