Multidimensional Item Response Theory

Multidimensional Item Response Theory is the first book to give thorough coverage to this emerging area of psychometrics. The book describes the commonly used multidimensional item response theory (MIRT) models and the important methods needed for their practical application. These methods include ways to determine the number of dimensions required to adequately model data, procedures for estimating model parameters, ways to define the space for a MIRT model, and procedures for transforming calibrations from different samples to put them in the same space. A full chapter is devoted to methods for multidimensional computerized adaptive testing.

The text is appropriate for an advanced course in psychometric theory or as a reference work for those interested in applying MIRT methodology. A working knowledge of unidimensional item response theory and matrix algebra is assumed. Knowledge of factor analysis is also helpful.

• Factor Analysis
• methodology
• model
• psychometrics

From the reviews:

“This book is the result of the author’s many years of work in multidimensional item response theory (MIRT) work that builds on the foundations laid by item response theory (IRT) and factor analysis pioneers. … In summary this book seeks to present a complex topic in a readable fashion … . helpful to many IRT researchers especially to young researchers who will further develop theory and apply MIRT in their research–not only in psychology but in other areas of science.” (Fumiko Samfjima, Journal of the American Statistical Association, Vol. 106 (493), March, 2011)

“This book gives a comprehensive review of theories and applications in various aspects of Multidimensional Item Response Theory (MIRT). … Every chapter is self-contained and starts with well-explained background information. … In all, this book is an inspiring book in measurement and, more importantly, there is no other comparable text on the topic. … this book will remain a key resource (handbook and textbook) for many years to come, and we highly recommend the book to teachers, students and researchers who are interested in IRT.” (Hua-Hua Chang and Chun Wang, Psychometrika, Vol. 76 (3), July, 2011)

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