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emIRT  

EM Algorithms for Estimating Item Response Theory Models
View on CRAN: Click here


Download and install emIRT package within the R console
Install from CRAN:
install.packages("emIRT")

Install from Github:
library("remotes")
install_github("cran/emIRT")

Install by package version:
library("remotes")
install_version("emIRT", "0.0.14")



Attach the package and use:
library("emIRT")
Maintained by
Kosuke Imai
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-03-01
Latest Update: 2022-03-04
Description:
Various Expectation-Maximization (EM) algorithms are implemented for item response theory (IRT) models. The package includes IRT models for binary and ordinal responses, along with dynamic and hierarchical IRT models with binary responses. The latter two models are fitted using variational EM. The package also includes variational network and text scaling models. The algorithms are described in Imai, Lo, and Olmsted (2016) .
How to cite:
Kosuke Imai (2015). emIRT: EM Algorithms for Estimating Item Response Theory Models. R package version 0.0.14, https://cran.r-project.org/web/packages/emIRT. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.0.5 (2015-03-01 09:03), 0.0.6 (2016-03-22 23:47), 0.0.7 (2016-07-29 18:27), 0.0.8 (2017-02-14 12:14), 0.0.9 (2019-12-13 21:40), 0.0.11 (2020-02-04 07:20), 0.0.13 (2022-03-04 13:50)
Other packages that cited emIRT R package
View emIRT citation profile
Other R packages that emIRT depends, imports, suggests or enhances
Complete documentation for emIRT
Functions, R codes and Examples using the emIRT R package
Some associated functions: AsahiTodai . binIRT . boot_emIRT . convertRC . dwnom . dynIRT . getStarts . hierIRT . makePriors . manifesto . mq_data . networkIRT . ordIRT . poisIRT . ustweet . 
Some associated R codes: binIRT.R . bootstrap.R . convertRC.R . dynIRT.R . getStarts.R . hierIRT.R . makePriors.R . networkIRT.R . ordIRT.R . poisIRT.R . print.R . zzz.R .  Full emIRT package functions and examples
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