A method of nonmetric multidimensional scaling is described which minimizes pairwise departures from monotonicity. (Author)

Tree representations of similarity data are investigated. Hierarchical clustering is critically examined, and a more general procedure, called the additive tree, is presented. The additive tree representation is then compared to multidimensional scaling. (Author/JKS)

This paper presents a simple random procedure for selecting subsets of stimulus pairs for presentation to subjects. The resulting set of ratings from the group of subjects allows the construction of a group space through the use of an existing computer program. (Author/JKS)

Factor analysis programs in SAS, BMDP, and SPSS are discussed and compared in terms of documentation, methods and options available, internal logic, computational accuracy, and results provided. Based on these comparisons, preferences for SAS and against SPSS factor analysis programs are recommended. (Author/JKS)

ORDMET is applicable to structures obtained from additive conjoint measurement designs, unfolding theory, general Fechnerian scaling, types of multidimensional scaling, and ordinal multiple regression. A description is obtained of the space containing all possible numerical representations which can satisfy the structure, size, and shape of which…

In this paper a rapid and reliable method is found for estimating the value of the Bivariate Normal Correlation Coefficient, p, given values of the joint probability and the normal deviates, h and k, or the related areas. (Editor)

Current computer programs for analyzing linear structural models will apparently handle only two types of constraints: fixed parameter and equal parameters. In this paper, a method for imposing several types of inequality of parameter constraints is described. Several examples are presented. (Author/JKS)

A Monte Carlo study investigated the ability of the ALSCAL multidimensional scaling program to recover true structure inherent in simulated proximity measures when data were missing. The program worked well with up to 60 percent missing data as long as sample size was large and random error was low. (Author/JKS)

Two revisions of computer-interactive multidimensional scaling data selection procedures are presented. One revision--based on randomly ordering the list of stimuli--improves the estimates of the multidimensional scaling parameters and the other permits more efficient data designs. (Author/JKS)

A maximum likelihood estimation procedure was developed to fit weighted and unweighted additive models of conjoint data obtained by categorical rating, paired comparisons or directional ranking methods. Practical uses of the procedure are presented to demonstrate various advantages of the procedure as a statistical method. (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)

In maximum likelihood factor analysis, there arises a situation whereby improper solutions occur. The causes of those improper solution are discussed and illustrated. (JKS)

Discusses the different strategies employed by three practical nonmetric multidimensional scaling algorithms using Monte Carlo techniques. (Author/RK)