THE KERNEL METHOD OF EQUATING SCORE DISTRIBUTIONS

Paul W. Holland · Dorothy T. Thayer

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Psychometric Methodologies and Testing Educational Assessment and Pedagogy Educational Technology and Assessment

Abstract

ABSTRACT A new and unified approach to test equating is described that is based on log‐linear models for smoothing score distributions and on the kernel method of non‐parametric density estimation. The new method contains both linear and standard equipercentile methods as special cases and can handle several important equating data collection designs. An example is used to illustrate the new method for the random groups and external anchor‐test designs.

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1987NOTES ON THE USE OF LOG‐LINEAR MODELS FOR FITTING DISCRETE PROBABILITY DISTRIBUTIONS

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2002Two Measures of Change in the Gaps Between the CDFs of Test-Score Distributions 2000Equating and Linking of Performance Assessments 2013Performing the Kernel Method of Test Equating with the Packagekequate 1991Smoothing Methods for Estimating Test Score Distributions

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