A basic structure approach is proposed for ob taining multidimensional scale values for attitude, achievement, or personality items from response data. Based on conventional components analysis, and described in terms of singular value or Eckart- Young decomposition of a data matrix, basic struc ture scaling yields projections of items upon axes in the person space, equivalent to obtaining com ponent scores for items, with component loadings associated with individuals. Unlike multidimension al scaling methods, the scaling of large sets of stimuli is practical and judgments of items are obviated. In attitude and personality item scaling, the technique permits the unconfounding of scale values due to response bias and to content. It also permits the partitioning of item indices of pop ularity or difficulty among a number of relevant dimensions, a property of possible relevance to tailored or adaptive testing.
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