The identification of two factors when one factor is expected is an artifact caused by using factor analysis on data that would be more appropriately analyzed with a unidimensional unfolding model. A numerical illustration is given, and ways to determine whether data conform to the unidimensional unfolding model are reviewed. (SLD)

The Cartesian theory of dimensionality (defined in terms of geometric distances between points in the test space) and Leibnitzian theory (defined in terms of order-generative connected, transitive, and asymmetric relations) are contrasted in terms of the difference between a factor analysis and an order analysis of the same data. (Author/CTM)

Two sets of five items each from the Law School Admission Test were analyzed by two methods of factor analysis, and by the Krus-Bart ordering theoretic method of multidimensional scaling. The results indicated a conceptual gap between latent trait theoretic procedures and order theoretic procedures. (Author/CTM)

Path analyses of two multitrait-multimethod matrices are used as examples of the kind of information afforded by application of the technique. It is concluded that the technique should be of considerable aid to researchers who want to evaluate the convergent and discriminant validity of their measures. (Author/CTM)

The fundamental mathematical model of L. L. Thurstone's common factor analysis is reviewed, and basic covariance matrices of maximum likelihood factor analysis and alpha factor analysis are presented. The methods are compared in terms of computational and scaling contrasts. Weighting and the appropriate number of common factors are considered.…

Geometric approaches to representing interrelations among tests and items are compared with an additive tree model (ATM), using 2,644 examinees and 2 other data sets. The ATM's close fit to the data and its coherence of presentation indicate that it is the best means of representing tests and items. (TJH)