Some Paths Toward Making Praxis Scores More Useful

Abstract

In this study we describe an analytic method for aiding in the generation of subscales that characterize the deep structure of tests. In addition we also derive a procedure for estimating scores for these scales that are much more statistically stable than subscores computed solely from the items that are contained on that scale. These scores achieve their stability through augmentation with information from other related information on the test. These methods were used to complement each other on a data set obtained from a Praxis administration. We found that the deep structure of the test yielded ten subscales and that, because the test was essentially unidimensional, ten subscores could be computed, all with very high reliability. This result was contrasted with the calculation of six traditional subscales based on surface features of the items. These subscales also yielded augmented subscores of high reliability.

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