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Best Linear Prediction of Composite Universe Scores

Published online by Cambridge University Press:  01 January 2025

David Jarjoura
David Jarjoura*
Affiliation:
American College Testing Program
*
Requests for reprints should be sent to David Jarjoura, Measurement Research Department, ACT, P.O. Box 168, Iowa City, Iowa 52243.
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Abstract

The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. A general measurement procedure is described in which multiple test forms are developed from a table of specifications and each form is administered to a different sample of examinees. The measurement model categorizes items according to the cells of such a table, and the linear function derived for minimizing error variance in prediction uses responses to these categories. In addition, some distinctions are drawn between aspects of the approach taken here and the familiar regressed score estimates.

Keywords

best linear predictiontest specificationsgeneralizability theorymeasurement error varianceregressed score estimates
Type
Original Paper
Information
Psychometrika , Volume 48 , Issue 4 , December 1983 , pp. 525 - 539
Copyright
Copyright © 1983 The Psychometric Society

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Footnotes

The author thanks Robert L. Brennan, Michael J. Kolen, and Richard Sawyer for helpful comments and corrections, and anonymous reviewers for suggested improvements.

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