Best linear prediction of composite universe scores |
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Authors: | David Jarjoura |
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Institution: | (1) Measurement Research Department, ACT, P.O. Box 168, 52243 Iowa City, Iowa |
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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.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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Keywords: | best linear prediction test specifications generalizability theory measurement error variance regressed score estimates |
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