Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors, practitioners, and applied researchers who want to learn how to properly use R IRT packages to perform IRT model calibrations with their own data.

This book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling in the book covers almost all models used in practice and in popular research, including:






dichotomous response modeling



polytomous response modeling



mixed format data modeling



concurrent multiple group modeling



fixed item parameter calibration



modelling with latent regression to include person-level covariate(s)



simple structure, or between-item, multidimensional modeling



cross-loading, or within-item, multidimensional modeling



high-dimensional modeling



bifactor modeling



testlet modeling



two-tier modeling

For beginners, this book provides a straightforward guide to learn how to use R for IRT applications. For more intermediate learners of IRT or users of R, this book will serve as a great time-saving tool for learning how to create the proper syntax, fit the various models, evaluate the models, and interpret the output using popular R IRT packages.