Specifying Optimum Examinees for Item Parameter Estimation in Item Response Theory
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 test construction) , better item calibration results may be obtained (for fixed sample sizes) from examinee calibration samples in which ability is widely dispersed.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1988
- Accession Number
- ADA203835
Entities
People
- Martha L. Stocking
Organizations
- Educational Testing Service