Description
Book SynopsisMeasurement in the social sciences often refers to standardized answers to close-ended questions, in which answers are analyzed as if they were measurements on an interval scale. This volume presents a measurement model that maintains the ordinal aspects of the data in order to establish how well the model fits and how it measures subjects and items. It relaxes the most stringent assumptions from parametric item response theory, while maintaining its advantages over classical measurement methods, such as reliability and factor analysis. This volume is less technical than other books on the topic and is ideal for introductory courses in social science measurement.
Table of ContentsAbout the Author Series Editor′s Introduction Acknowledgments Chapter 1. Introduction Chapter 2. The Guttman Scale Chapter 3. The Imperfect Cumulative Scale Chapter 4. Confirmation or Exploration Chapter 5. An Example of a Cumulative Scale: American Religious Beliefs Chapter 6. The Probabilistic Dominance Model: Monotone Homogeneity Chapter 7. The Probabilistic Dominance Model: Double Monotonicity Chapter 8. Cumulative Scaling with Polytomous Items Chapter 9. Remaining Issues References Selected Bibliography Appendices Author Index Subject Index
