Multidimensional scaling (MDS) a highly reliable measurement technique, often requires an overwhelming task of the subject in the data collection procedure. This investigation was designed to determine the loss of precision in solution associated with five degrees of systematic reduction in the data collection task. Data were simulated via Monte…

Restricted multidimensional scaling models, allowing constraints on parameters, are extended to the case of asymmetric data. Examples of several models are provided, using journal citation data. Possible extensions of the models are considered. (Author/JKS)

A class of closely related hierarchical grouping methods are discussed and a procedure which implements them in an integrated fashion is presented. These methods avoid some theoretical anomalies inherent in clustering and provide a framework for viewing partitioning and nonpartitioning grouping. Significant relationships between these methods and…

Many data analysis problems in psychology may be posed conveniently in terms which place the parameters to be estimated on one side of an equation and an expression in these parameters on the other side. A rule for improving the rate of convergence of the iterative solution of such equations is developed and applied to four problems. (Author/RC)

Six major problems confronting attempts to use nonmetric multidimensional scaling to represent structures underlying similarity data are identified and the author's prospects for over-coming each of these problems are presented. (RC)

Examines the similarity between the coordinates which resulted when correlations were used as similarity measures and the factor loadings obtained by factor analyzing the same correlation matrix. Real data, a set of error free data, and some computer generated data containing deliberately introduced sampling error are analyzed. (RC)

Concerned with another form of analysis of m sets of matrices, the Procrustes idea is generalized so that all m sets are simultaneously translated, rotated, reflected and scaled so that a goodness of fit criterion is optimised. A computational technique is given, results of which can be summarized in analysis of variance form. (RC)

The problem of dimensionality with respect to Raven's Advanced Progressive Matrices (APM) specifically and, more generally, "g" or fluid intelligence, has been a long-standing issue. The present article reports two studies examining the dimensionality of both the original Set II of the APM (n = 506) and a short form (n = 644), using principal…