Data generated by the pair-comparison method can be analyzed by least squares. A system of normal equations is derived by which the original objects are scaled. One advantage of this method is that it is not necessary to compare all object pairs. Examples are provided. (Author/JKS)

The G index of agreement does not permit the use of various weights for its various items. The weighted G index described here, make it possible to use unequal weights. An example of the procedure is provided. (Author/JKS)

Research into statistical validations of constructs in physical education obtained by seriation and multidimensional scaling, revealed that (a) larger matrix sizes produced the most accurate results; (b) as data error introduction was increased, solution accuracy decreased; and (c) seriation produced slightly more accurate results than one- and…

Describes the use of multidimensional scaling (MDS), emphasizing applications in counseling and vocational psychology. Includes an example of one standard nonmetric scaling method. Addresses conceptual and practical considerations associated with the use of MDS. (Author/KS)

Critical examination is made of the recent controversy over the value of Monte Carlo techniques in nonmetric multidimensional scaling procedures. The case is presented that the major relevance of Monte Carlo studies is not for the local minima problem but for the meaningfulness of the obtained solutions. (Author)

It is the purpose of this paper to suggest the orthogonal analysis of variance as a device for simplifying either the analytic or iterative problem of finding LS (least squares) estimates for the parameters of particular nonlinear models. (Author/RK)

Author argues that simplistic and/or heuristic approaches to the Tucker and Messick model (an individual differences model for multidimensional scaling, 1963) are often inadequate. (Author/CB)

The concept of sequential estimation is introduced in multidimensional scaling. The sequential estimation method developed in this paper refers to continually updating estimates of a configuration as new observations are added. Using artificial data, the performance of this sequential method is illustrated. (Author/JKS)

A method for externally constraining certain distances in multidimensional scaling configurations is introduced and illustrated. The method is described in detail and several examples are presented. (Author/JKS)

Two least squares procedures for symmetrization of a conditional proximity matrix are derived. The solutions provide multiplicative constants for scaling the rows or columns of the matrix to maximize symmetry. (Author/JKS)

The stability of dimensions extracted from a body of free response data was studied using 1,523 expressions of concern and questions raised by 271 elderly persons and analyzed by 2 groups of experimenters. The structures of resulting multidimensional configurations obtained by the 2 groups were identical. (SLD)

An Extended Two-Way Euclidean Multidimensional Scaling (MDS) model that assumes both common and specific dimensions is described and contrasted with the "standard" (Two-Way) MDS model. Illustrations with both artificial and real data on the judged similarity of nations are provided. (TJH)

Investigated concept of happiness in 100 adults, aged 19 to 90, and in 126 Catholic nuns, aged 26 to 89. Subjects gave word associates to words "happiness" and "unhappiness." In both samples, two-dimensional space was judged to optimally fit data. First dimension was interpreted as bipolar affective dimension; second as representing personal…

Presents two methods for including weights in distance-based nonlinear multivariate data analysis. One method assigns weights to the objects, while the other is concerned with differential weighing of groups of variables. Discusses applications of these weighting schemes and proposed an algorithm to minimize the corresponding loss function. (SLD)