Introduction To Item Response Theory Models And Applications

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Using R for Item Response Theory Model Applications

Using R for Item Response Theory Model Applications
Author :
Publisher : Routledge
Total Pages : 281
Release :
ISBN-10 : 9781351008150
ISBN-13 : 1351008153
Rating : 4/5 (153 Downloads)

Book Synopsis Using R for Item Response Theory Model Applications by : Insu Paek

Download or read book Using R for Item Response Theory Model Applications written by Insu Paek and published by Routledge. This book was released on 2019-09-16 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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