The Theory and Practice of Item Response Theory, Second Edition

David J. Weiss, Bruno D. Zumbo, Mark Reckase, Scott Hofer, R. J. de Ayala

ISBN 10: 1462547753 / ISBN 13: 9781462547753

Edité par Guilford Publications, US, 2022

A propos de cet article

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.

N° de réf. du vendeur LU-9781462547753

Détails bibliographiques

• Titre: The Theory and Practice of Item Response Theory, Second Edition
• Éditeur: Guilford Publications, US
• Date de parution: 2022
• Langue: anglais
• ISBN à 10 chiffres: 1462547753
• ISBN à 13 chiffres: 9781462547753
• Reliure: Hardback
• Édition: 2ème Édition
• État de l'article: New
• Poids: 1240 grammes

A propos de ce titre

Synopsis

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.

À propos de l?auteur

R. J. de Ayala, PhD, is Professor of Quantitative, Qualitative, and Psychometric Methods and Director of the Institutional Research Master's Program in the College of Educational and Human Sciences at the University of Nebraska-Lincoln (UNL). His research interests include psychometrics, item response theory, computerized adaptive testing, applied statistics, and multilevel models. His work has appeared in Applied Psychological Measurement, Applied Measurement in Education, the British Journal of Mathematical and Statistical Psychology, Educational and Psychological Measurement, the Journal of Applied Measurement, and the Journal of Educational Measurement. He is a Fellow of the American Psychological Association's Division 5: Evaluation, Measurement, and Statistics and of the American Educational Research Association. He is a recipient of a Big 12 Faculty Fellowship and holds a Gallup Research Professorship at UNL.