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Abstract

This study examined three statistical methods for selecting items for mastery tests. One is the pretest-posttest method due to Cox and Vargas (1966); it is computationally simple, but has a number of serious limitations. The second is a latent trait method recommended by van der Linden (1981); it is computationally complex, but has a number of theoretical advantages. The third method, proposed herein, parallels the latent trait method in many respects; but it is computationally simple, like the pretest-posttest procedure. A number of distinct data sets were simulated; and the three item selection methods were applied to each data set for the purpose of studying relationships among the methods. The correlation between the latent trait method and the one proposed herein was substantial, suggesting that the latter might be recommended as a practical alternative to the former. The results for the pretest-posttest method tended to confirm its reputed limitations.

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Item Analysis: A Short-Cut Statistic for Mastery Tests

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