Using R for item response theory model applications

著者

書誌事項

Using R for item response theory model applications

Insu Paek and Ki Cole

Routledge, 2020

  • pbk. : alk. paper

大学図書館所蔵 件 / 全2件

この図書・雑誌をさがす

注記

Includes bibliographical references and index

収録内容

  • Introduction
  • Unidimensional IRT with dichotomous item responses
  • Unidimensional IRT with polytomous item responses
  • Unidimensional IRT for other applications
  • Multidimensional IRT for simple structure
  • Multidimensional IRT for bifactor structure
  • Limitations and caveat

内容説明・目次

内容説明

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.

目次

Preface 1. Introduction 2. Unidimensional IRT with Dichotomous Item Responses 3. Unidimensional IRT with Polytomous Item Responses 4. Unidimensional IRT for Other Applications 5. Multidimensional IRT for Simple Structure 6. Multidimensional IRT for Bifactor Structure 7. Limitations and Caveat

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