Statistical Models for Test Equating, Scaling, and Linking

  • Alina A. von Davier

Part of the Statistics for Social and Behavioral Sciences book series (SSBS)

Table of contents

  1. Front Matter
    Pages i-xix
  2. Research Questions and Data Collection Designs

    1. Front Matter
      Pages 19-19
    2. Alina A. von Davier
      Pages 1-17
  3. Research Questions and Data Collection Designs

    1. Front Matter
      Pages 19-19
    2. Neil J. Dorans, Tim P. Moses, Daniel R. Eignor
      Pages 21-42
    3. Michael J. Kolen, Ye Tong, Robert L. Brennan
      Pages 43-58
    4. James E. Carlson
      Pages 59-70
    5. Paul W. Holland, William E. Strawderman
      Pages 89-107
    6. Samuel A. Livingston, Sooyeon Kim
      Pages 109-122
  4. Measurement and Equating Models

    1. Front Matter
      Pages 123-123
    2. Shelby J. Haberman
      Pages 125-140
    3. Yi-Hsuan Lee, Alina A. von Davier
      Pages 159-173
    4. George Karabatsos, Stephen G. Walker
      Pages 175-184
    5. Haiwen H. Chen, Samuel A. Livingston, Paul W. Holland
      Pages 185-200
    6. Wim J. van der Linden
      Pages 201-223
    7. Matthias von Davier, Alina A. von Davier
      Pages 225-242
    8. Xueli Xu, Jeff A. Douglas, Young-Sun Lee
      Pages 243-258
  5. Evaluation

    1. Front Matter
      Pages 259-259

About this book

Introduction

The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statistical perspective (new models, robustness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equating practice. The book contributes to establishing “equating” as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as a craft, which implies that only with years of experience under the guidance of a knowledgeable practitioner could one acquire the required skills. This book challenges this view by indicating how a good equating framework, a sound understanding of the assumptions that underlie the psychometric models, and the use of statistical tests and statistical process control tools can help the practitioner navigate the difficult decisions in choosing the final equating function. This book provides a valuable reference for several groups: (a) statisticians and psychometricians interested in the theory behind equating methods, in the use of model-based statistical methods for data smoothing, and in the evaluation of the equating results in applied work; (b) practitioners who need to equate tests, including those with these responsibilities in testing companies, state testing agencies, and school districts; and (c) instructors in psychometric, measurement, and psychology programs. 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.

Keywords

Measurement Model Psychometric Model Standardized Assessment Test Equating

Editors and affiliations

  • Alina A. von Davier
    • 1
  1. 1.Educational Testing ServicePrincetonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-98138-3
  • Copyright Information Springer Science+Business Media, LLC 2011
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-98137-6
  • Online ISBN 978-0-387-98138-3
  • About this book