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.
