Applying Test Equating Methods

Using R

  • Jorge González
  • Marie Wiberg

Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Jorge González, Marie Wiberg
    Pages 1-18
  3. Jorge González, Marie Wiberg
    Pages 19-42
  4. Jorge González, Marie Wiberg
    Pages 43-72
  5. Jorge González, Marie Wiberg
    Pages 73-110
  6. Jorge González, Marie Wiberg
    Pages 111-136
  7. Jorge González, Marie Wiberg
    Pages 137-155
  8. Jorge González, Marie Wiberg
    Pages 157-178
  9. Back Matter
    Pages 179-196

About this book


This book describes how to use test equating methods in practice. The non-commercial software R is used throughout the book to illustrate how to perform different equating methods when scores data are collected under different data collection designs, such as equivalent groups design, single group design, counterbalanced design and non equivalent groups with anchor test design. The R packages equate, kequate and SNSequate, among others, are used to practically illustrate the different methods, while simulated and real data sets illustrate how the methods are conducted with the program R. The book covers traditional equating methods including, mean and linear equating, frequency estimation equating and chain equating, as well as modern equating methods such as kernel equating, local equating and combinations of these. It also offers chapters on observed and true score item response theory equating and discusses recent developments within the equating field. More specifically it covers the issue of including covariates within the equating process, the use of different kernels and ways of selecting bandwidths in kernel equating, and the Bayesian nonparametric estimation of equating functions. It also illustrates how to evaluate equating in practice using simulation and different equating specific measures such as the standard error of equating, percent relative error, different that matters and others.


Test equating using R Equating data collection designs Presmoothing score distributions Polynomial log-linear models for presmoothing Traditional equating methods Kernel equating using R Bandwidth selection in kernel equating IRT equating using R Item parameter linking Local equating using R IRT kernel equating Assessment of equating Kernel equating under the NEC design Bayesian equating Equating using R R code for equating Concurrent calibration Fixed item parameter calibration Comparison of equating methods Equating with covariates

Authors and affiliations

  • Jorge González
    • 1
  • Marie Wiberg
    • 2
  1. 1.Faculty of MathematicsPontificia Universidad Católica de ChileSantiagoChile
  2. 2.Department of Statistics, Umeå School of Business and EconomicsUmeå UniversityUmeåSweden

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Education Education (R0)
  • Print ISBN 978-3-319-51822-0
  • Online ISBN 978-3-319-51824-4
  • Series Print ISSN 2367-170X
  • Series Online ISSN 2367-1718
  • Buy this book on publisher's site