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Diagnostic Measurement : Theory, Methods, and Applications

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Title: Diagnostic Measurement : Theory, Methods, and Applications
Author: Andre A. Rupp, Jonathan Templin, Robert A. Henson
ISBN: 1606235273 / 9781606235270
Format: Soft Cover
Pages: 348
Publisher: The Guilford Press
Year: 2010
Availability: Out of Stock
  • Description
  • Contents

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 (projects.coe.uga.edu/dcm) features data sets, Mplus syntax code, and output.

Index of Notation

Chapter 1 : Introduction

Part I : Theory : Principles of Diagnostic Measurement with DCMs
Chapter 2 :
Implementation, Design, and Validation of Diagnostic Assessments
Chapter 3 : Diagnostic Decision Making with DCMs
Chapter 4 : Attribute Specification for DCMs

Part II : Methods : Psychometric Foundations of DCMs
Chapter 5 :
The Statistical Nature of DCMs
Chapter 6 : The Statistical Structure of Core DCMs
Chapter 7 : The LCDM Framework
Chapter 8 : Modeling the Attribute Space in DCMs

Part III : Applications : Utilizing DCMs in Practice
Chapter 9 :
Estimating DCMs Using Mplus
Chapter 10 : Respondent Parameter Estimation in DCMs
Chapter 11 : Item Parameter Estimation in DCMs
Chapter 12 : Evaluating the Model Fit of DCMs
Chapter 13 : Item Discrimination Indices for DCMs
Chapter 14 : Accommodating Complex Sampling Designs in DCMs


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