Description
Book SynopsisIn 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.
Table of ContentsPreface 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
