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Psychometrics
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Psychometrics
An Introduction

Fourth Edition


July 2021 | 704 pages | SAGE Publications, Inc

In this fully revised Fourth Edition of Psychometrics: An Introduction, author R. Michael Furr centers his presentation around a conceptual understanding of psychometric core issues, such as scales, reliability, and validity. Focusing on purpose rather than procedure and the “why” rather than the “how to," this accessible book uses a wide variety of examples from behavioral science research so readers can see the importance of psychometric fundamentals in research. By emphasizing concepts, logic, and practical applications over mathematical proofs, this book gives students an appreciation of how measurement problems can be addressed and why it is important to address them. The book offers readers the most contemporary views of topics in psychometrics available in the nontechnical psychometric literature.

New to this edition:

  • Technical appendices in R at the end of most chapters help students apply concepts in a free and powerful software program.
  • Dataset and syntax files in R help students apply and practice the concepts they learn.
  • Expanded figures and tables (more than twice as many as the previous edition) present information in condensed and visual formats for increased understanding.
  • Additional coverage of fundamental statistics and concepts ensures readers start each chapter with the appropriate context and background.
  • Expanded depth and breadth of coverage of key issues in psychometrics, including summaries of relevant statistical packages, introduces readers to a wide range of important concepts, principles, and procedures.
  • Enhanced clarity and accessibility helps students understand and appreciate the diverse and often highly technical material in psychometric theory.
 
Preface
The Conceptual Orientation of This Book, Its Purpose, and the Intended Audience

 
Organizational Overview

 
New to This Edition

 
Author’s Acknowledgments

 
Publisher’s Acknowledgments

 
 
About the Author
 
Chapter 1. Psychometrics and the Importance of Psychological Measurement
Why Psychological Testing Matters to You

 
Observable Behavior and Unobservable Psychological Attributes

 
Psychological Tests: Definition and Types

 
What Is Psychometrics?

 
Challenges to Measurement in Psychology

 
The Importance of Individual Differences

 
But Psychometrics Goes Well Beyond “Differential” Psychology

 
Suggested Readings

 
 
PART I. BASIC CONCEPTS IN MEASUREMENT
 
Chapter 2. Scaling
Fundamental Issues With Numbers

 
Units of Measurement

 
Additivity and Counting

 
Four Scales of Measurement

 
Scales of Measurement: Practical Implications

 
Additional Issues Regarding Scales of Measurement

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
 
Chapter 3. Differences, Consistency, and the Meaning of Test Scores
The Nature of Variability

 
Importance of Individual Differences

 
Variability and Distributions of Scores

 
Quantifying the Association or Consistency Between Distributions

 
Variance and Covariance for “Composite Variables”

 
Binary Items

 
Interpreting Test Scores

 
Test Norms

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
 
Chapter 4. Test Dimensionality and Factor Analysis
Test Dimensionality

 
Factor Analysis: Examining the Dimensionality of a Test

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
 
PART II. RELIABILITY
 
Chapter 5. Reliability: Conceptual Basis
Overview of Reliability and Classical Test Theory

 
Observed Scores, True Scores, and Measurement Error

 
Variances in Observed Scores, True Scores, and Error Scores

 
Four Ways to Think of Reliability

 
Reliability and the Standard Error of Measurement

 
From Theory to Practice: Measurement Models and Their Implications for Estimating Reliability

 
Domain Sampling Theory

 
Summary

 
Suggested Readings

 
 
Chapter 6. Empirical Estimates of Reliability
Alternate Forms Method of Estimating Reliability

 
Test–Retest Method of Estimating Reliability

 
Internal Consistency Method of Estimating Reliability

 
Sample Heterogeneity and Reliability Generalization

 
Reliability of Difference Scores

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
Note

 
 
Chapter 7. The Importance of Reliability
Applied Behavioral Practice: Evaluation of an Individual’s Test Score

 
Behavioral Research

 
Test Construction and Refinement

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
 
PART III. VALIDITY
 
Chapter 8. Validity: Conceptual Basis
What Is Validity?

 
The Importance of Validity

 
Validity Evidence: Test Content

 
Validity Evidence: Internal Structure of the Test

 
Validity Evidence: Response Processes

 
Validity Evidence: Associations With Other Variables

 
Validity Evidence: Consequences of Testing

 
Other Perspectives on Validity

 
Contrasting Reliability and Validity

 
Summary

 
Suggested Readings

 
 
Chapter 9. Estimating and Evaluating Convergent and Discriminant Validity Evidence
A Construct’s Nomological Network

 
Methods for Evaluating Convergent and Discriminant Validity

 
Factors Affecting a Validity Coefficient

 
Interpreting a Validity Coefficient

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
Notes

 
 
PART IV. THREATS TO PSYCHOMETRIC QUALITY
 
Chapter 10. Response Biases
Types of Response Biases

 
Methods for Coping With Response Biases

 
Response Biases, Response Sets, and Response Styles

 
Summary

 
Suggested Readings

 
 
Chapter 11. Test Bias
Why Worry About Test Score Bias?

 
Detecting Construct Bias: Internal Evaluation of a Test

 
Detecting Predictive Bias: External Evaluation of a Test

 
Other Statistical Procedures

 
Test Fairness

 
Example: Is the SAT Biased in Terms of Race or Socioeconomic Status?

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
Notes

 
 
PART V. ADVANCED PSYCHOMETRIC APPROACHES
 
Chapter 12. Confirmatory Factor Analysis
On the Use of EFA and CFA

 
The Process of CFA for Analysis of a Scale’s Internal Structure

 
CFA and Reliability

 
CFA and Validity

 
CFA and Measurement Invariance

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
 
Chapter 13. Generalizability Theory
Multiple Facets of Measurement

 
Generalizability, Universes, and Variance Components

 
G Studies and D Studies

 
Conducting and Interpreting Generalizability Theory Analysis: A One-Facet Design

 
Conducting and Interpreting Generalizability Theory Analysis: A Two-Facet Design

 
Other Measurement Designs

 
A Practical, Consistency-Oriented Interpretation of Variance Components

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
Notes

 
 
Chapter 14. Item Response Theory and Rasch Models
Factors Affecting Responses to Test Items

 
IRT Measurement Models

 
Obtaining Parameter Estimates: A 1PL Example

 
Model Fit

 
Item and Test Information

 
Applications of IRT

 
Technical Appendix: R Syntax

 
Summary

 
Suggested Readings

 
 
Glossary
 
References
 
Index

Supplements

Instructor Resource Site
edge.sagepub.com/furr4e


For additional information, custom options, or to request a personalized walkthrough of these resources, please contact your sales representative.


LMS cartridge included with this title for use in Blackboard, Canvas, Brightspace by Desire2Learn (D2L), and Moodle

The LMS cartridge makes it easy to import this title’s instructor resources into your learning management system (LMS). These resources include:

  • Test banks
  • Editable chapter-specific PowerPoint® slides
  • All tables and figures from the textbook 
Don’t use an LMS platform?

You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
Student Resource Site

edge.sagepub.com/furr4e

 

The open-access Student Study Site makes it easy for students to maximize their study time, anywhere, anytime. It offers flashcards that strengthen understanding of key terms and concepts, and datasets for use in SPSS and R.

I'm excited to teach my undergrads IRT!

Dr Lucie Kocum
Psychology Dept, Saint Marys University
August 31, 2023

Ease of reading yet comprehensive.

Dr Amy Martin
Psychology Dept, Rockford University
June 16, 2022

R code added to what was already one of the best graduate-level psychometrics books on the market, Concepts are explained with plain language and examples.

Dr Mark Rose
Psychology Dept, St Marys University
August 17, 2022