Statistical Models for Test Equating, Scaling, and Linking

Dr. Alina A. von Davier is a Strategic Advisor and a Director of Special Projects in Research and Development at Educational Testing Service (ETS). During her tenure at ETS, she has led an ETS Research Initiative called “Equating and Applied Psychometrics” and has directed the Global Psychometric Services Center. The center supports the psychometric work for all ETS international programs, including TOEFL iBT and TOEIC. She is a co-author of a book on the kernel method of test equating, an author of a book on hypotheses testing in regression models, and a guest co-editor for a special issue on population invariance of linking functions for the journal Applied Psychological Measurement.

• Overview.- A Statistical Perspective on Equating Test Scores (Alina A. von Davier).- Part I: Research Questions and Data Collection Designs.- Equating Test Scores: Toward Best Practices Neil J. Dorans, Tim P. Moses, and Daniel R. Eignor).- Scoring and Scaling Educational Tests Michael J. Kolen, Ye Tong, and Robert L. Brennan).- Statistical Models for Vertical Linking James E. Carlson).- An Empirical Example of Change Analysis by Linking Longitudinal Item Response Data From Multiple Tests (John J. McArdle and Kevin J. Grimm).- How to Average Equating Functions, If You Must (Paul W. Holland and William E. Strawderman).- New Approaches to Equating With Small Samples (Samuel A. Livingston and Sooyeon Kim).- Part II: Measurement and Equating Models.- Using Exponential Families for Equating (Shelby J. Haberman).- An Alternative Continuization Method: The Continuized Log-Linear Method (Tianyou Wang).- Equating Through Alternative Kernels (Yi-Hsuan Lee and Alina A. von Davier).- A BayesianNonparametric Model for Test Equating (George Karabatsos and Stephen G. Walker).- Generalized Equating Functions for NEAT Designs (Haiwen H. Chen, Samuel A. Livingston, and Paul W. Holland).- Local Observed-Score Equating (Wim J. van der Linden).- A General Model for IRT Scale Linking and Scale Transformations (Matthias von Davier and Alina A. von Davier).- Linking With Nonparametric IRT Models (Xueli Xu, Jeff A. Douglas, and Young-Sun Lee).- Part III: Evaluation.- Applications of Asymptotic Expansion in Item Response Theory Linking (Haruhiko Ogasawara).- Evaluating the Missing Data Assumptions of the Chain and Poststratification Equating Methods (Sandip Sinharay, Paul W. Holland, and Alina A. von Davier).- Robustness of IRT Observed-Score Equating (C. A. W. Glas and Anton A. Beguin).- Hypothesis Testing of Equating Differences in the Kernel Equating Framework (Frank Rijmen, Yanxuan Qu, and Alina A. von Davier).- Applying Time-Series Analysis to Detect Scale Drift (Deping Li, ShuhongLi, and Alina A. von Davier).

From the reviews: "The intended audience of the book consists of graduate students, researchers, statisticians and psychometricians who are interested in equating theory, as well as practitioners who equate tests. ... volume is easy to understand since overall it is clear and well written, and has examples that are nice and easy to follow. ... I recommend this book for anyone with an interest in the equating research field, and ... the book has succeeded in providing a statistical view on equating which has long been searched for." (Marie Wiberg, Psychometrika, Vol. 78 (1), January, 2013)