Item Selection Procedures for Item Variables with a Known Factor Structure

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Abstract
This paper discusses the item selection problem when the item responses follow a linear multiple factor model. Because of this restrictive assumption, not too unrealistic in situations such as mental testing, it is possible to select optimal sets of items without going through all possible combinations. A method proposed by Elfving to accomplish this is analyzed and then demonstrated through the use of two illustrations. The common and often used procedure of observing the magnitude of the correlation coefficient as an index in item selection is shown to have some merit in the single-factor case.

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