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E-raamat: Item Response Theory: Foundations for Psychologists and Social Scientists 2nd edition [Taylor & Francis e-raamat]

(University of California, Los Angeles, USA), (Georgia Institute of Technology, Atlanta, USA)
  • Formaat: 422 pages, 77 Tables, black and white; 109 Line drawings, black and white; 109 Illustrations, black and white
  • Sari: Multivariate Applications Series
  • Ilmumisaeg: 03-Nov-2025
  • Kirjastus: Routledge
  • ISBN-13: 9781315726557
Teised raamatud teemal:
  • Taylor & Francis e-raamat
  • Hind: 189,26 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 270,37 €
  • Säästad 30%
  • Formaat: 422 pages, 77 Tables, black and white; 109 Line drawings, black and white; 109 Illustrations, black and white
  • Sari: Multivariate Applications Series
  • Ilmumisaeg: 03-Nov-2025
  • Kirjastus: Routledge
  • ISBN-13: 9781315726557
Teised raamatud teemal:
This book provides an intuitive and accessible introduction to item response theory (IRT), making complex psychometric concepts easier to grasp through graphical displays and familiar analogies. It bridges theory and application, helping readers interpret and implement IRT models effectively to improve measurement quality in psychology and the social sciences. Covering both foundational and advanced topics, it offers a clear path for understanding contemporary IRT methods and their relevance in research and practice.

With a strong focus on applications, this book explains contemporary IRT models and estimation methods, placing special emphasis on polytomous IRT models, which are widely used in psychological assessments and rating scales. Applications in various research areas are explored in detail, alongside a dedicated chapter on available software to support implementation. The final section delves into advanced IRT topics, including multidimensional models and explanatory approaches for hypothesis testing, making it a valuable resource for those looking to deepen their understanding of psychometric analysis.

This book is essential for graduate students, researchers, and practitioners in psychology, education, and the social sciences. It is useful for researchers who are implementing or developing person assessments, as well as for professionals in clinical, industrial, counseling, and behavioral medicine fields who need a strong grasp of contemporary psychometric foundations. Professors teaching measurement courses will find it an ideal core textbook, offering a structured and engaging introduction to IRT and its applications in test development and analysis.

Contents: Preface. Part I: Introduction. Introduction. Part II: Item Response Theory Principles: Some Contrasts and Comparisons. The New Rules of Measurement. Item Response Theory as Model-Based Measurement. Part III: The Fundamentals of Item Response Theory. Binary IRT Models. Polytomous IRT Models. The Trait Level Measurement Scale: Meaning, Interpretations, and Measurement-Scale Properties. Measuring Persons: Scoring Examinees With IRT Models. Calibrating Items: Estimation. Assessing the Fit of IRT Models. Part IV: Applications of IRT Models. IRT Applications: DIF, CAT, and Scale Analysis. IRT Applications in Cognitive and Developmental Assessment. Applications of IRT in Personality and Attitude Assessment. Computer Programs for Conducting IRT Parameter Estimation.

Susan E. Embretson is Professor Emeritus at both the University of Kansas and the Georgia Institute of Technology in the USA. She received her Ph.D. from the University of Minnesota. Her primary interest includes developing and applying item response theory (IRT) models for the response processes used by examinees to solve aptitude items.

Steven P. Reise received his Ph.D. from the Department of Psychology at the University of Minnesota in 1990. Currently, he is Professor of Quantitative Psychology at UCLA. His research explores the application of item response theory (IRT) models to personality, psychopathology, and health outcome measures. In recent years, his interests have centered on bifactor modeling and projective IRT models.