Overview

Using a meaning-based approach that emphasizes the ""why"" over the ""how to"" of core psychometric issues, this fully revised Fourth Edition of Furr's accessible text uses a wide variety of examples from behavioral science research so readers can see the importance of psychometric fundamentals in research.

Full Product Details

Author:   Richard Michael Furr
Publisher:   SAGE Publications Inc
Imprint:   SAGE Publications Inc
Edition:   4th Revised edition
Weight:   1.180kg
ISBN:  

9781071824078

ISBN 10:   1071824074
Pages:   704
Publication Date:   15 October 2021
Audience:   College/higher education ,  Tertiary & Higher Education
Replaced By:   9781506389875
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock  
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

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

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Author Information

Michael Furr is Professor of Psychology and Wright Faculty Fellow at Wake Forest University, where he teaches and conducts research in personality psychology, psychological measurement, and quantitative methods. He earned a BA from the College of William and Mary, an MS from Villanova University, and a PhD from the University of California at Riverside. He is an editor of the “Statistical Developments and Applications” section of the Journal of Personality Assessment, a former associate editor of the Journal of Research in Personality, a former executive editor of the Journal of Social Psychology, and a consulting editor for several other scholarly journals. He received Wake Forest University’s 2012 Award for Excellence in Research, and he won the Society for Personality Assessment’s 2017 Bruno Klopfer Award for Distinguished Contributions to the Literature in Personality Assessment,. He is a fellow of Divisions 5 (Quantitative and Qualitative Methods) and 8 (Social and Personality Psychology) of the American Psychological Association, a fellow of the Association for Psychological Science, and a fellow of the Society for Personality and Social Psychology.

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