Testlet Response Theory and Its Applications

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. Eric T. Bradlow is the K. P. Chao Professor, Professor of Marketing and Statistics, and Academic Director of the Wharton Small Business Development Center, Wharton School of the University of Pennsylvania. Before joining the Wharton faculty, he worked in the Corporate Marketing and Business Research Division at the DuPont Corporation, and in the Statistics and Psychometrics Research Group at the Educational Testing Service. Bradlow was recently named a Fellow of the American Statistical Association. Dr Xiaohui Wang is an Assistant Professor in the Department of Statistics at the University of Virginia. She worked as a Principal Data Analyst for three years in the Division of Data Analysis and Research Technology at the Educational Testing Service. She has twice received the National Council on Measurement in Education Award for Scientific Contribution to a Field of Educational Measurement.

• 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.

'… a very accessible and incredibly delightful book to read. … an excellent resource … a valuable addition to the bookshelves of teachers, students and researchers in testing and measurement.' Psychometrika