Abstract
In the last decade, many R packages were published to perform item response theory (IRT) analysis. Some researchers and practitioners have difficulty in using these functional tools because of their insufficient coding skills. The IRTGUI package provides these researchers a user-friendly GUI where they can perform unidimensional IRT analysis without coding skills. Using the IRTGUI package, person and item parameters, model and item fit indices can be obtained. Dimensionality and local independence assumptions can be tested. With the IRTGUI package, users can generate dichotomous data sets with customizable conditions. Also, Wright Maps, item characteristics and information curves can be graphically displayed. All outputs can be easily downloaded by users.
Keywords: R package, item response theory, graphical user interface, item response theory models
Description
The use of R packages is increasing in the field of psychometrics, as in many other fields. Researchers and practitioners benefit from countless useful R packages. While these packages are quite simple and useful for most researchers, they can be challenging for those with no coding experience. The IRTGUI package has been developed to provide a user-friendly Graphical User Interface (GUI) for researchers with insufficient coding skills to perform unidimensional item response theory (IRT) analyzes.
Users can easily perform their analysis by uploading data sets with the IRTGUI package. If they want, they can generate dichotomous data sets with the properties they want by using the data generation submenu. The number of items, sample size, person and item parameter distributions and desired dichotomous IRT model can be selected for the generated data sets. Rasch, 2 PL, 3 PL, Graded Response Model, and Generalized Partial Credit Models can be used in the analyzes. Akaike Information Criterion, Bayesian Information Criterion, and log-likelihood fit indices can be displayed for each model to select the most suitable model for the data set.
Unidimensionality assumption can be tested before analyzes. Scree plots and eigen values can be displayed as a result of explanatory factor analysis. The local independence assumption can also be tested using Yen’s Q3 test or Chen & Thissen’in G2 statistics. Using the IRTGUI interface, ability and item parameters can be estimated together with their standard errors. Besides, some descriptive statistics about ability parameters and marginal reliability values can be obtained.
The IRTGUI package also provides some graphical outputs. Item characteristic curves can be displayed separatley for each item or collectively for all items. Wright Maps can be created in which ability and b parameters distributions can be displayed on the same graphic.
In the background of IRTGUI package, some functions from mirt (Chalmers, 2012), irtoys (Partchev & Maris, 2017), psych (Revelle, 2020), WrightMap (Irribarra & Freund, 2014) packages were used. The R package IRTGUI is available on Comprehensive R Archive Network (CRAN; http://www.cran.r-project.org). IRTGUI can be installed with install.packages (“IRTGUI”). Source code and documentation are freely available from https://CRAN.R-project.org/package=irtGUI.
Supplemental Material
Supplemental Material, DESCRIPTION for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement
Supplemental Material, NAMESPACE for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement
Supplemental Material, irtGUIR for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement
Supplemental Material, irtGUIRd for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement
Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
Supplementray material: Supplemental material for this article is available online.
ORCID iD
Huseyin Yildiz https://orcid.org/0000-0003-2387-263X
References
- Chalmers R. (2012). mirt: A multidimensional item response theory package for the R environment. Journal of Statistical Sofware, 48(6), 1-29. 10.18637/jss.v048.i06 [DOI] [Google Scholar]
- Irribarra D. T., Freund R. (2014). Wright map: IRT item-person map with ConQuest integration. http://github.com/david-ti/wrightmap
- Partchev I., Maris G. (2017). irtoys: A collection of functions related to item response theory (IRT). R package version 0.2.1. https://CRAN.R-project.org/package=irtoys
- Revelle W. (2020). psych: Procedures for psychological, psychometric, and personality research. R package version 2.0.12. Northwestern University. https://CRAN.R-project.org/package=psych [Google Scholar]
Associated Data
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Supplementary Materials
Supplemental Material, DESCRIPTION for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement
Supplemental Material, NAMESPACE for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement
Supplemental Material, irtGUIR for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement
Supplemental Material, irtGUIRd for IRTGUI: An R Package for Unidimensional Item Response Theory Analysis With a Graphical User Interface by Huseyin Yildiz in Applied Psychological Measurement