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.
General
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