M. D. Reckase

Multidimensional Item Response Theory (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book is a description of the theoretical foundations of multidimensional item response theory and the methodologies for applying multidimensional item response theory to practical testing problems.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 354
• Erscheinungstermin: 7. Juli 2009
• Englisch
• ISBN-13: 9780387899763
• Artikelnr.: 37289179

Inhaltsangabe

Unidimensional Item Response Theory Models.- Historical Background for Multidimensional Item Response Theory (MIRT).- Multidimensional Item Response Theory Models.- Statistical Descriptions of Item and Test Functioning.- Estimation of Item and Person Parameters.- Analyzing the Structure of Test Data.- Transforming Parameter Estimates to a Specified Coordinate System.- Linking and Scaling.- Computerized Adaptive Testing Using MIRT.

Rezensionen

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)