R Packages for Item Response Theory Analysis: Descriptions and Features

Youn Jeng Choi; Abdullah Asilkalkan

doi:10.1080/15366367.2019.1586404

R Packages for Item Response Theory Analysis: Descriptions and Features

Youn Jeng Choi, Abdullah Asilkalkan

Department of Education

Research output: Contribution to journal › Review article › peer-review

14 Scopus citations

Abstract

About 45 R packages to analyze data using item response theory (IRT) have been developed over the last decade. This article introduces these 45 R packages with their descriptions and features. It also describes possible advanced IRT models using R packages, as well as dichotomous and polytomous IRT models, and R packages that contain applications such as differential item functioning and equating are also introduced. Thus, this article helps researchers who plan to use IRT-based analysis to decide on the type of IRT analysis and choose the appropriate R packages.

Original language	English
Pages (from-to)	168-175
Number of pages	8
Journal	Measurement
Volume	17
Issue number	3
DOIs	https://doi.org/10.1080/15366367.2019.1586404
State	Published - 2019

Bibliographical note

Publisher Copyright:
© 2019, © 2019 Taylor & Francis Group, LLC.

Keywords

R package
differential item functioning
equating
item response theory
simulation study

Access to Document

10.1080/15366367.2019.1586404

Cite this

@article{676c3a8c14bf4eb79d53cfdc8aaf81f9,

title = "R Packages for Item Response Theory Analysis: Descriptions and Features",

abstract = "About 45 R packages to analyze data using item response theory (IRT) have been developed over the last decade. This article introduces these 45 R packages with their descriptions and features. It also describes possible advanced IRT models using R packages, as well as dichotomous and polytomous IRT models, and R packages that contain applications such as differential item functioning and equating are also introduced. Thus, this article helps researchers who plan to use IRT-based analysis to decide on the type of IRT analysis and choose the appropriate R packages.",

keywords = "R package, differential item functioning, equating, item response theory, simulation study",

author = "Choi, {Youn Jeng} and Abdullah Asilkalkan",

note = "Publisher Copyright: {\textcopyright} 2019, {\textcopyright} 2019 Taylor & Francis Group, LLC.",

year = "2019",

doi = "10.1080/15366367.2019.1586404",

language = "English",

volume = "17",

pages = "168--175",

journal = "Measurement",

issn = "1536-6367",

publisher = "Taylor and Francis Ltd.",

number = "3",

}

TY - JOUR

T1 - R Packages for Item Response Theory Analysis

T2 - Descriptions and Features

AU - Choi, Youn Jeng

AU - Asilkalkan, Abdullah

PY - 2019

Y1 - 2019

N2 - About 45 R packages to analyze data using item response theory (IRT) have been developed over the last decade. This article introduces these 45 R packages with their descriptions and features. It also describes possible advanced IRT models using R packages, as well as dichotomous and polytomous IRT models, and R packages that contain applications such as differential item functioning and equating are also introduced. Thus, this article helps researchers who plan to use IRT-based analysis to decide on the type of IRT analysis and choose the appropriate R packages.

AB - About 45 R packages to analyze data using item response theory (IRT) have been developed over the last decade. This article introduces these 45 R packages with their descriptions and features. It also describes possible advanced IRT models using R packages, as well as dichotomous and polytomous IRT models, and R packages that contain applications such as differential item functioning and equating are also introduced. Thus, this article helps researchers who plan to use IRT-based analysis to decide on the type of IRT analysis and choose the appropriate R packages.

KW - R package

KW - differential item functioning

KW - equating

KW - item response theory

KW - simulation study

UR - http://www.scopus.com/inward/record.url?scp=85071356234&partnerID=8YFLogxK

U2 - 10.1080/15366367.2019.1586404

DO - 10.1080/15366367.2019.1586404

M3 - Review article

AN - SCOPUS:85071356234

SN - 1536-6367

VL - 17

SP - 168

EP - 175

JO - Measurement

JF - Measurement

IS - 3

ER -

R Packages for Item Response Theory Analysis: Descriptions and Features

Abstract

Bibliographical note

Keywords

Access to Document

Fingerprint

Cite this