The Theory and Practice of Item Response Theory
eBook - PDF

The Theory and Practice of Item Response Theory

  1. 643 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

The Theory and Practice of Item Response Theory

Book details
Table of contents
Citations

About This Book

Noted for addressing both the "hows" and "whys" of item response theory (IRT), this text has been revised and updated with the latest techniques (multilevel models, mixed models, and more) and software packages. Simple to more complex models are covered in consistently formatted chapters that build sequentially. The book takes the reader from model development through the fit analysis and interpretation phases that would be performed in practice. To facilitate understanding, common data sets are used across chapters, with the examples worked through for increasingly complex models. Exemplary model applications include free (BIGSTEPS, NOHARM, Facets, R packages) and commercial (BILOG-MG, flexMIRT, SAS, WINMIRA, SPSS, SYSTAT) software packages. The companion website provides data files and online-only appendices. New to This Edition
*Chapter on multilevel models.
*New material on loglinear models, mixed models, the linear logistic trait model, and fit statistics.
*Many additional worked-through examples.
*Updated guidance on software; now includes R, SAS, and flexMIRT.

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Yes, you can access The Theory and Practice of Item Response Theory by R. J. de Ayala in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Information

Publisher
The Guilford Press
Year
2022
ISBN
9781462547920
Edition
2
Topic
Social Sciences
Subtopic
Social Science Research & Methodology
Index
Social Sciences

Table of contents

  1. Cover
  2. Half Title Page
  3. Series Page
  4. Title Page
  5. Copyright
  6. Dedication
  7. Series Editor’s Note
  8. Preface
  9. Contents
  10. 1. Introduction to Measurement
  11. 2. The One-Parameter Model
  12. 3. Joint Maximum Likelihood Parameter Estimation
  13. 4. Marginal Maximum Likelihood Parameter Estimation
  14. 5. The Two-Parameter Model
  15. 6. The Three-Parameter Model
  16. 7. Rasch Models for Ordered Polytomous Data
  17. 8. Non-Rasch Models for Ordered Polytomous Data
  18. 9. Models for Nominal Polytomous Data
  19. 10. Models for Multidimensional Data
  20. 11. Linking and Equating
  21. 12. Differential Item Functioning
  22. 13. Multilevel IRT Models
  23. References
  24. Author Index
  25. Subject Index
  26. About the Author