RL2021-3: Using R Software for Item Response (IRT) Model Calibrations

This interactive training course will introduce the concepts of unidimensional IRT models and provide instruction, demonstration, and hands-on opportunities of using the free R software to estimate commonly used IRT models. Participants will receive a discount code for Using R for Item Response Theory Model Applications, written by the course instructors. 

Concepts of commonly used unidimensional IRT models will be taught (e.g. Rasch, 1PL, 2PL, 3PL, GR, and GPC), with little focus on statistical theory. Participants will receive detailed training on how to correctly execute the R IRT packages and interpret the results, with ample opportunities for hands-on analysis. Example datasets will be provided for practical applications. 

The target audience for this course includes graduate students, practitioners, and researchers interested in advancing their knowledge of IRT and enhancing skills of using R to do IRT analysis. A basic understanding of IRT is highly recommended. Prior knowledge of R is not required. Familiarity with writing syntax may also be helpful for using R but is not essential. Participants should bring their own laptop with the free R software and packages installed. Instructions for downloading R and installing the necessary packages will be provided prior to the course. Participants may also bring their own dataset for more hands-on assistance.


Ki L. Cole, Oklahoma State University (course director) Insu Paek, Florida State University Sohee Kim, Oklahoma State University


RL2021-3: Using R Software for Item Response (IRT) Model Calibrations
Open to view video.  |   Closed captions available
Open to view video.  |   Closed captions available