In Psychometrics: An Introduction, R. Michael Furr centres his presentation of material around a conceptual understanding of psychometric issues, such as validity and reliability, and on purpose rather than procedure, the why rather than the how to." By emphasizing concepts over mathematical proofs and by focusing on practical significance, this book assists students in appreciating not just how measurement problems can be addressed, but why it is important to address them. Key features: Presents information in a clear, easy-to-read, conversational style Highlights practical applications…mehr
In Psychometrics: An Introduction, R. Michael Furr centres his presentation of material around a conceptual understanding of psychometric issues, such as validity and reliability, and on purpose rather than procedure, the why rather than the how to." By emphasizing concepts over mathematical proofs and by focusing on practical significance, this book assists students in appreciating not just how measurement problems can be addressed, but why it is important to address them.
Key features: Presents information in a clear, easy-to-read, conversational style Highlights practical applications Offers an up-to-date treatment of topics in psychometrics Introduces statistical procedures in the context of their use rather than in a separate chapter
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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.
Inhaltsangabe
Chapter 1: Psychometrics and the Importance of Psychological Measurement PART I. BASIC CONCEPTS IN MEASUREMENT Chapter 2: Scaling Chapter 3: Individual Differences and Correlations Chapter 4: Test Dimensionality and Factor Analysis PART II. RELIABILITY Chapter 5: Reliability: Conceptual Basis Chapter 6: Empirical Estimates of Reliability Chapter 7: The Importance of Reliability PART III. VALIDITY Chapter 8: Validity: Conceptual Basis Chapter 9: Estimating and Evaluating Convergent and Discriminant Validity Evidence PART IV. THREATS TO PSYCHOMETRIC QUALITY Chapter 10: Response Biases Chapter 11: Test Bias PART V. ADVANCED PSYCHOMETRIC APPROACHES Chapter 12: Confirmatory Factor Analysis Chapter 13: Generalizability Theory Chapter 14: Item Response Theory and Rasch Models Glossary
Chapter 1: Psychometrics and the Importance of Psychological Measurement PART I. BASIC CONCEPTS IN MEASUREMENT Chapter 2: Scaling Chapter 3: Individual Differences and Correlations Chapter 4: Test Dimensionality and Factor Analysis PART II. RELIABILITY Chapter 5: Reliability: Conceptual Basis Chapter 6: Empirical Estimates of Reliability Chapter 7: The Importance of Reliability PART III. VALIDITY Chapter 8: Validity: Conceptual Basis Chapter 9: Estimating and Evaluating Convergent and Discriminant Validity Evidence PART IV. THREATS TO PSYCHOMETRIC QUALITY Chapter 10: Response Biases Chapter 11: Test Bias PART V. ADVANCED PSYCHOMETRIC APPROACHES Chapter 12: Confirmatory Factor Analysis Chapter 13: Generalizability Theory Chapter 14: Item Response Theory and Rasch Models Glossary
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