Using R for Item Response Theory Model Applications

Using R for Item Response Theory Model Applications
Using R for Item Response Theory Model Applications
By 作者: Insu Paek
ISBN-10 书号: 1138542792
ISBN-13 书号: 9781138542792
Edition 版本: 1
Release Finelybook 出版日期: 2019-09-11
pages 页数: (280 )

$49.95

Book Description to Finelybook sorting

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.

Contents


Preface
1Introduction
2Unidimensional IRT with dichotomous item responses
3 Unidimensional IRT with polytomous item responses
4Unidimensional IRT with other applications
5 Multidimensional IRT for simple structure
6Multidimensional IRT for bifactor structure
7 Limitations and caveat
Index


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