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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.

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

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


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


Suggested Readings

Chapter 4. Test Dimensionality and Factor Analysis
Test Dimensionality

Factor Analysis: Examining the Dimensionality of a Test

Technical Appendix: R Syntax


Suggested Readings

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


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


Suggested Readings


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


Suggested Readings

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


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


Suggested Readings


Chapter 10. Response Biases
Types of Response Biases

Methods for Coping With Response Biases

Response Biases, Response Sets, and Response Styles


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


Suggested Readings


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


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


Suggested Readings


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


Suggested Readings



Instructor Resource Site

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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


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.

Key features


  • 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.
  • Information is presented in an easy-to-understand, conversational writing style that does not compromise the academic integrity of the material.
  • Practical applications are highlighted through examples to enhance readers' appreciation of the importance of psychometrics.
  • Statistical procedures are introduced in the context of their use, rather than in a separate chapter, for a more intuitive approach to understanding the material.
  • Integration of statistics with a discussion of their use as tools to solve particular psychometric problems encourages a more complete understanding of both.
  • PowerPoint(R) slides and a test bank enhance course preparation.