Diagnostic Measurement : Theory, Methods, and Applications book cover
1st Edition

Diagnostic Measurement
Theory, Methods, and Applications

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ISBN 9781606235270
Published May 21, 2010 by Guilford Press
348 Pages


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Book Description

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

Table of Contents

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


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André A. Rupp is Assistant Professor in the Department of Measurement, Statistics, and Evaluation at the University of Maryland. Dr. Rupp’s current research centers on developing methodological frameworks and modeling approaches that support rigorous interdisciplinary exchange between measurement specialists, substantive researchers, and applied practitioners. Two promising research areas in which he is intimately involved are diagnostic classification models (DCMs), which are the focus of this book, and modern measurement approaches for innovative digital learning environments.
Jonathan Templin is Professor and E. F. Lindquist Chair in the Department of Psychological and Quantitative Foundations at the University of Iowa. His research focuses on diagnostic classification models--psychometric models that seek to provide multiple actionable and reliable scores from educational and psychological assessments. He also studies Bayesian statistics, as applied in psychometrics, broadly. Dr. Templin is an elected member of the Society of Multivariate Behavioral Psychology. He received the Outstanding Contribution to Research in Cognition and Assessment Award from the Cognition and Assessment Special Interest Group of the American Educational Research Association, as well as the inaugural Robert L. Linn Memorial Lecture Award from the University of Colorado Boulder and the University of California, Los Angeles.
Robert A. Henson is Assistant Professor in the Department of Educational Research Methodology at the University of North Carolina at Greensboro. His major research interests have focused on DCMs, with a primary focus on developing concepts and procedures for DCMs that are analogous to common concepts and procedures of more traditional measurement techniques. Dr. Henson’s hope is that, by expanding concepts that are already familiar in other settings, DCMs will be developed using a common methodology for assessments that will provide fine-grained information. Additional interests include latent-variable models in general and mixed linear models.


Rupp, Templin, and Henson have contributed significantly to the advancement of educational and psychological measurement by providing a comprehensive and lucid treatment of this critical contemporary measurement issue. Particularly noteworthy is the clear voice leading the reader logically and thoughtfully through theory, methods, and applications; throughout, one is never in doubt that the authors’ primary objectives are to promote rigorous intellectual dialogue about the current and future state of DCMs and to facilitate their meaningful and practical application.--Kristen Huff, EdD, Senior Director, Research and Development, The College Board, New York
The readability of the book is excellent. It offers a good, basic-level exposition of the underpinnings of cognitive diagnostic assessment. It is particularly important for a book like this to be accessible to a broader audience beyond experts in cognitive diagnosis. The book covers cognitive foundations, makes connections with the most salient aspects of assessment validity, and includes detailed derivations and discussion of core cognitive diagnostic models. The examples are especially effective and clear, as is the tabulation of model parameters in the discussion of six core models and their relationship to the log-linear modeling framework. I would recommend this text for use in graduate seminars and expect to quote from it and cite it in professional presentations and papers. There is no other book available with comparable breadth.--Lou DiBello, PhD, Associate Director, Learning Sciences Research Institute, University of Illinois-Chicago
The coverage in this book is rich and clear. It addresses all of the current topics in diagnostic assessment. Each topic is explained in detail, along with examples and diagrams. The sequence of the materials is easy to follow. I love the Applications section, which illustrates how DCMs can be estimated with the software program Mplus.--Yi-hsin Chen, PhD, Department of Educational Measurement and Research, University of South Florida
The most authoritative, comprehensive source to date on every important aspect of diagnostic measurement, including theory, methods, and applications. The book includes recent advances in the unification of cognitive theory and psychometric methodology. It covers technical issues, such as model specification and parameter estimation, and extends the treatment to a variety of disciplines, from education to clinical and business settings. I was impressed by the reader-friendly presentation. The writing is clear and smooth, making this complex subject matter much more accessible and less intimidating than one might expect. The authors effectively use many examples, tables, and figures to explain difficult concepts. I would definitely consider this book for my professional use and my class use with doctoral psychometric students.--Lihshing Leigh Wang, PhD, School of Education, University of Cincinnati
I would strongly recommend this book to colleagues and students. It provides an interdisciplinary perspective on diagnostic testing; has a strong instructional focus, where concepts and statistical models are explained in a concise and clear way; and covers the entire range of testing, from item development to test score reporting.--Mark J. Gierl, PhD, Director, Centre for Research in Applied Measurement and Evaluation, Department of Educational Psychology, University of Alberta, Canada
-_x000D_The importance of the objective of this book cannot be overstated scientifically: to classify respondents based on different combinations of multiple qualitative attributes or skills underlying assessment items, with the goal of providing differentiated profiles for individualized feedback and intervention....It summarizes the current state-of-the-art of DCMs in a comprehensive and unified manner, starting from substantive theory via statistical methods and going to software applications. It is the first book of such a kind currently available on this topic. The intended audience...consists of professionals in the testing industry, professors, and students in educational and psychological sciences. All those who are interested in model-based classification and cluster analysis will benefit from it including, for example, applied statisticians and computer scientists. The book's text is conceptual rather than technical, and emphasizes the understanding and proper use of the discussed materials more than it elaborates on the mathematical or statistical theory....A valuable contribution to the literature on diagnostic measurement models, and this book is definitely worth the price. We can strongly recommend it, whether as a textbook for teaching or as a reference volume for research.--Psychometrika, 4/12/2010