This book is aimed at (a) practitioners who need to equate tests- including those with these responsibilities in testing companies, state testing agencies and school districts; (b) statisticians and other research workers interested in the theory behind such work and the use of model based statistical methods of data smoothing in applied work; (c) advanced graduate students in psychometric and measurement programs. While there are other books on test equating, and books of the use of kernel smoothing, no one has published any work on the kernel method of test equating. It is something of a unifying idea in equating and brings together several methods into an organized whole rather than treating them as a group of disparate methods.

KE is applied to the four major equating designs and to both Chain Equating and Post-Stratification Equating for the Non-Equivalent groups with Anchor Test Design. It will be an important reference for several groups: (a) Statisticians (b) Practitioners and (c) Instructors in psychometric and measurement programs. The authors assume some familiarity with linear and equipercentile test equating, and with matrix algebra.