Abstract
This paper presents a multilevel variance component analysis of data from the pilot year of pretesting of an educational test. The multilevel nature of the data is induced by the clustering of students within colleges and by having multivariate observations (scores) on students. The presence of a multidimensional trait underlying the scores is formulated as a hypothesis about the full rank of a variance matrix.
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