Diagnostic measurement : theory, methods, and applications
著者
書誌事項
Diagnostic measurement : theory, methods, and applications
（Methodology in the social sciences）
Guilford Press, c2010
- : hardcover
- : pbk
大学図書館所蔵 件 / 全7件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references (p. 331-338) and indexes
内容説明・目次
内容説明
This book provides a comprehensive introduction to the theory and practice of diagnostic classification models (DCMs), which are useful for statistically driven diagnostic decision making. DCMs can be employed in a wide range of disciplines, including educational assessment and clinical psychology. For the first time in a single volume, the authors present the key conceptual underpinnings and methodological foundations for applying these models in practice. Specifically, they discuss a unified approach to DCMs, the mathematical structure of DCMs and their relationship to other latent variable models, and the implementation and estimation of DCMs using Mplus. The book's highly accessible language, real-world applications, numerous examples, and clearly annotated equations will encourage professionals and students to explore the utility and statistical properties of DCMs in their own projects. The companion website (www.guilford.com/rupp-materials) features chapter exercises with answers, data sets, Mplus syntax code, and output.
Winner--Award for Significant Contribution to Educational Measurement and Research Methodology, AERA Division D
目次
Index of Notation
1. Introduction
I. Theory: Principles of Diagnostic Measurement with DCMs
2. Implementation, Design, and Validation of Diagnostic Assessments
3. Diagnostic Decision Making with DCMs
4. Attribute Specification for DCMs
II. Methods: Psychometric Foundations of DCMs
5. The Statistical Nature of DCMs
6. The Statistical Structure of Core DCMs
7. The LCDM Framework
8. Modeling the Attribute Space in DCMs
III. Applications: Utilizing DCMs in Practice
9. Estimating DCMs Using Mplus
10. Respondent Parameter Estimation in DCMs
11. Item Parameter Estimation in DCMs
12. Evaluating the Model Fit of DCMs
13. Item Discrimination Indices for DCMs
14. Accommodating Complex Sampling Designs in DCMs
Glossary
「Nielsen BookData」 より