Several decades of psychometric research have led to the development of sophisticated models for multidimensional test data, and in recent years, multidimensional item response theory (MIRT) has become a burgeoning topic in psychological and educational measurement. Considered a cutting-edge statistical technique, the methodology underlying MIRT can be complex, and therefore doesn’t receive much attention in introductory IRT courses. However author Wes Bonifay shows how MIRT can be understood and applied by anyone with a firm grounding in unidimensional IRT modeling. His volume includes practical examples and illustrations, along with numerous figures and diagrams. Multidimensional Item Response Theory includes snippets of R code interspersed throughout the text (with the complete R code included on an accompanying website) to guide readers in exploring MIRT models, estimating the model parameters, generating plots, and implementing the various procedures and applications discussed throughout the book.
表中的内容
Series Editor′s Introduction
Acknowledgments
About the Author
1. Introduction
2. Unidimensional Item Response Theory
3. MIRT Models for Dichotomous Data
4. MIRT Models for Polytomous Data
5. Descriptive MIRT Statistics
6. Item Factor Structures
7. Estimation in MIRT Models
8. MIRT Model Diagnostics and Evaluation
9. MIRT Applications
References
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