Howard Wainer

Testlet Response Theory and Its Applications (eBook, PDF)

• Format: PDF

Produktbeschreibung

The measurement models employed to score tests have been evolving over the past century from those that focus on the entire test (true score theory) to models that focus on individual test items (item response theory) to models that use small groups of items (testlets) as the fungible unit from which tests are constructed and scored (testlet response theory, or TRT). In this book, the inventors of TRT trace the history of this evolution and explain the character of modern TRT. Written for researchers and professionals in statistics, psychometrics, and educational psychology, the first part offers an accessible introduction to TRT and its applications. The second part presents a comprehensive, self-contained discussion of the model couched within a fully Bayesian framework. Its parameters are estimated using Markov chain Monte Carlo procedures, and the resulting posterior distributions of the parameter estimates yield insights into score stability that were previously unsuspected.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 19. März 2007
• Englisch
• ISBN-13: 9780511276163
• Artikelnr.: 38192715

Autorenporträt

Dr Howard Wainer is a Distinguished Research Scientist for the National Board of Medical Examiners and Adjunct Professor of Statistics at the Wharton School of the University of Pennsylvania.

Inhaltsangabe

Preface
Part I. Introduction to Testlets: 1. Introduction to testing
2. Traditional true score theory
3. Item response theory
4. Testlet response theory: introduction and preview
5. The origins of testlet response theory: three alternatives
6. Fitting testlets with polytomous IRT models: the Law School Admissions Test as an example
Part II. Bayesian Testlet Response Theory: Introduction
7. A brief history and the basic ideas of modern testlet response theory
8. The 2-PL Bayesian testlet model
9. The 3-PL Bayesian testlet model
10. A Bayesian testlet model for a mixture of binary and polytomous data
11. A Bayesian testlet model with covariates
12. Testlet nonresponse theory: dealing with missing data
Part III. Applications and Ancillary Topics: Introduction
13. Using posterior distributions to evaluate passing scores: The PPoP curve
14. DIF - Differential Testlet Functioning
15. Estimation: a Bayesian primer.