Presents an introduction to educational and psychological testing and measurement theory that reflects the various intellectual developments. This book introduces psychometric theory using a latent variable modeling (LVM) framework and emphasizes interval estimation. It also offers tips on how to use test theory in the actual testing situations.
Presents an introduction to educational and psychological testing and measurement theory that reflects the various intellectual developments. This book introduces psychometric theory using a latent variable modeling (LVM) framework and emphasizes interval estimation. It also offers tips on how to use test theory in the actual testing situations.
Tenko Raykov is Professor of Measurement and Quantitative Methods at Michigan State University. He received his Ph.D. in Mathematical Psychology from Humboldt University in Berlin. He teaches courses in psychometric theory, multivariate statistics, latent variable and structural equation modeling, and multilevel modeling at Michigan State University. He serves on the editorial board of Psychological Methods, Structural Equation Modeling, the British Journal of Mathematical and Statistical Psychology, and Multivariate Behavioral Research. George A. Marcoulides is Professor of Statistics at the University of California - Riverside. He is the Series Editor of the Quantitative Methodology Series, Editor of the Structural Equation Modeling journal, and on the editorial board of several other measurement and statistics journals.
Inhaltsangabe
1. Measurement, Measuring Instruments, and Psychometric Theory. 2. Basic Statistical Concepts and Relationships. 3. An Introduction to Factor Analysis. 4. Introduction to Latent Variable Modeling and Confirmatory Factor Analysis. 5. Classical Test Theory. 6. Reliability. 7. Procedures for Estimating Reliability. 8. Validity. 9. Generalizability Theory. 10. Introduction to Item Response Theory. 11. Fundamentals and Models of Item Response Theory. Chapter Notes. Appendix. A Brief Introduction to Some Graphics Applications of R in Item Response Modeling.
1. Measurement, Measuring Instruments, and Psychometric Theory. 2. Basic Statistical Concepts and Relationships. 3. An Introduction to Factor Analysis. 4. Introduction to Latent Variable Modeling and Confirmatory Factor Analysis. 5. Classical Test Theory. 6. Reliability. 7. Procedures for Estimating Reliability. 8. Validity. 9. Generalizability Theory. 10. Introduction to Item Response Theory. 11. Fundamentals and Models of Item Response Theory. Chapter Notes. Appendix. A Brief Introduction to Some Graphics Applications of R in Item Response Modeling.
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