Measurement 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.
|Series:||Quantitative Applications in the Social Sciences Series , #169|
|Product dimensions:||5.40(w) x 8.40(h) x 0.40(d)|
About the Author
Wijbrandt H. van Schuur is associate professor at the Faculty of Behavioral and Social Sciences of the University of Groningen, The Netherlands. He is interested in measurement models and has taught measurement and scaling models in Groningen and at the Essex Summer School in Social Science Data Analysis. He has developed an ordinal unidimensional unfolding model and a model for the ordinal circumplex (for the first see Political Analysis, 1993, and Applied Psychological Measurement, 1994; and for the second, Essays in item response theory: Lecture notes in statistics, Vol. 157, 2001). His main substantive research interest is in the measurement of political knowledge (e.g. Acta Politica 2000), and, in collaboration with the Documentation Centre Dutch Political Parties, the study of party membership (e.g. Research in Political Sociology, Vol. 18, 2010).
Table of Contents
About the AuthorSeries Editor's IntroductionAcknowledgmentsChapter 1. IntroductionChapter 2. The Guttman ScaleChapter 3. The Imperfect Cumulative ScaleChapter 4. Confirmation or ExplorationChapter 5. An Example of a Cumulative Scale: American Religious BeliefsChapter 6. The Probabilistic Dominance Model: Monotone HomogeneityChapter 7. The Probabilistic Dominance Model: Double MonotonicityChapter 8. Cumulative Scaling with Polytomous ItemsChapter 9. Remaining IssuesReferencesSelected BibliographyAppendicesAuthor IndexSubject Index