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Specifying Optimum Examinees for Item Parameter Estimation in Item Response Theory

Published online by Cambridge University Press:  01 January 2025

Martha L. Stocking*
Affiliation:
Educational Testing Service
*
Requests for reprints should be sent to Martha L. Stocking, Mail Stop 03-T, Educational Testing Service, Princeton, NJ 08541.

Abstract

Information functions are used to find the optimum ability levels and maximum contributions to information for estimating item parameters in three commonly used logistic item response models. For the three and two parameter logistic models, examinees who contribute maximally to the estimation of item difficulty contribute little to the estimation of item discrimination. This suggests that in applications that depend heavily upon the veracity of individual item parameter estimates (e.g. adaptive testing or text construction), better item calibration results may be obtained (for fixed sample sizes) from examinee calibration samples in which ability is widely dispersed.

Information

Type
Original Paper
Copyright
Copyright © 1990 The Psychometric Society

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