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Maximum likelihood estimation of the joint covariance matrix for sections of tests given to distinct samples with application to test equating

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Abstract

Consider an old testX consisting ofs sections and two new testsY andZ similar toX consisting ofp andq sections respectively. All subjects are given testX plus two variable sections from either testY orZ. Different pairings of variable sections are given to each subsample of subjects. We present a method of estimating the covariance matrix of the combined test (X 1, ...,X s ,Y 1, ...,Y p ,Z 1, ...,Z q ) and describe an application of these estimation techniques to linear, observed-score, test equating.

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Authors and Affiliations

  1. Educational Testing Service 21-T, 08541, Princeton, New Jersey

    Dorothy T. Thayer

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  1. Dorothy T. Thayer
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Additional information

The author is indebted to Paul W. Holland and Donald B. Rubin for their encouragement and many helpful comments and suggestions that contributed significantly to the development of this paper.

This research was supported by the Program Statistics Research Project of the ETS Research Statistics Group.

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Thayer, D.T. Maximum likelihood estimation of the joint covariance matrix for sections of tests given to distinct samples with application to test equating. Psychometrika 48, 293–297 (1983). https://doi.org/10.1007/BF02294023

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  • DOI: https://doi.org/10.1007/BF02294023

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