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.
