"This book is jam-packed with useful information. It includes basic, practical programming examples, with clear explanations of WinSTEPS and BILOG scripts, and step-by-step interpretations of goodness of fit in IRT problems. The author also covers more advanced forms of IRT, including multicategory items, multidimensional latent influences, and advanced multiple-group problems of linking and equating. A tour de force!"--John J. McArdle, PhD, Head, Quantitative Methods Area, Department of Psychology, University of Southern California
"A very well-organized and useful introduction to IRT. The book has an excellent structure that covers widely used IRT models and most of their major applications. The author has done an outstanding job of balancing the mathematical with the conceptual, and each chapter contains examples of applications to real data using commercially available software. The book is liberally supplemented by the kinds of graphic displays that can help neophytes understand the complexities of IRT. An especially useful feature is the up-front glossary of notation and acronyms. This is an excellent text for a one-semester graduate-level course in IRT, and should provide students with the knowledge they require to delve deeper into IRT models and their applications. It is also a useful reference for psychological and educational researchers who apply IRT in their work."--David J. Weiss, PhD, Department of Psychology, University of Minnesota; Editor Emeritus, Applied Psychological Measurement
"This book provides a thorough overview of item response theory methodology, with a nice blend of theoretical psychometrics and practical applications. The coverage is quite complete, including the standard dichotomous and polytomous unidimensional models as well as multidimensional models. The examples are very useful. This book will serve very well as a technical reference and as a text for upper-level psychometric theory courses."--Mark D. Reckase, PhD, Department of Counseling, Educational Psychology, and Special Education, Michigan State University
"De Ayala does a masterful job of describing the fundamental theory and the many applications of IRT. I am impressed by the breadth of models he covers and the detail he presents on various estimation methods. Coverage includes the standard Rasch; one-, two-, and three-parameter models; polytomous and multidimensional models; and applications to linking/equating and differential item functioning. This is a well-written book that will be useful for graduate students, researchers, and practicing measurement specialists in education, health, and psychology. The greatest strength of this book is de Ayala's ability to present IRT in an engaging, accessible manner."--Bruno D. Zumbo, PhD, Measurement, Evaluation, and Research Methodology Program, and Department of Statistics, University of British Columbia, Canada
"Offers a good roadmap to the complex array of IRT model parameters, estimation methods, and readily available IRT programs. By juxtaposing algebraic development of IRT models (and model estimation) alongside annotated results and software output from applied examples, this book provides an excellent resource for both intermediate and advanced IRT practitioners. The applied researcher will find this book to be an excellent practical resource with numerous examples that use multiple software packages to analyze the same datasets."--Scott M. Hofer, PhD, Department of Human Development and Family Sciences, Oregon State University
"The book has an excellent balance among the technical, conceptual, and practical aspects of item response theory. It is comprehensive; provides example scripts and output from a variety of popular item response programs; and uses selected data sets throughout the book, making model and program comparisons possible. I also liked the coverage of commonly asked questions related to model fit, item fit, and appropriate sample sizes, which are often missing in item response theory texts."--Kevin J. Grimm, PhD, Department of Psychology, University of California, Davis
No comments:
Post a Comment