Ordinal item response theory : Mokken scale analysis

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Title:

Author:

Schuur, Wijbrandt van.

ISBN:

9781412988049

Personal Author:

Schuur, Wijbrandt van.

Publication Information:

Thousand Oaks, Calif. : SAGE, c2011.

Physical Description:

xi, 114 p. : ill. ; 22 cm.

Series:

Quantitative applications in the social sciences ; 169

Quantitative applications in the social sciences ; 169.

General Note:

Machine generated contents note: 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 Appendix: The null-distribution of the H-coefficient Appendix: Preventing capitalizing on chance Appendix: Calculation of Reliability.

Contents:

Abstract:

"Ordinal Item Response Theory is volume 169 in the SAGE Series "Quantitative Applications in the Social Sciences" (QASS). The of Ordinal Item Response Theory is referred to throughout many other QASS titles and fills a gap between the more classical topics of undimensional scaling, test theory, principal component and factor analysis. In addition, this volume also discusses parametric item response theory and latent class analysis. This monograph is less technical than many books on the market and is best suited for an introductory course in social science measurement"--

Subject Term:

Social sciences -- Methodology.

Social sciences -- Research.

Copies:

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Library	Material Type	Item Barcode	Shelf Number	Copy	Status
Searching... 1:IIEMSA	1:GEN-BOOK	33168025589959	001.42 S396.O 2011	1	Searching... Unknown

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Summary

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.