Two popular models for performing multidimensional scaling, Tucker and Messick's points-of-view model, and Tucker's three mode model, are combined into a single analytic procedure, the 3M-POV model. The procedure is described and its strengths are discussed. Carroll and Chang's INDSCAL model is also mentioned. (JKS)

The logic and procedures underlying a disturbance term regression test of logical consistency for structural models are reviewed for recursive and nonrecursive designs. It is shown that in a simple three-variable, complete mediational case the test procedure is mathematically equivalent to a part correlation. (Author/LMO)

A Statistical Analysis System (SAS) macro procedure for performing a jackknife analysis on structure coefficients in discriminant analysis is described together with issues and caveats about its use in multivariate methods. An example of use of the SAS macro is provided. (SLD)

Canonical correlation analysis is considered to be a general model for bivariate and multivariate statistical methods. Some problems involving assumptions and statistical tests for parameters exist for social science data. A resolution for these problems is presented by treating canonical correlation as a special case of linear structural…

Conditions necessary and sufficient for the determination of LISREL model solutions are identified. The reasons for indeterminacy of LISREL solutions are discussed, and an index of determinacy is presented and related to the covariance matrix of latent variables. (SLD)

The strategy for investigating convergent and discriminant test validity, known as the multitrait-multimethod matrix, is investigated. A nonparametric significance testing procedure is suggested and demonstrated. (JKS)

Many models have been proposed for examining factors from several batteries of tests. A model for such an analysis is presented which allows for maintaining the distinction among batteries. A discussion of the computational procedures is given, and examples are provided. (Author/JKS)

An algorithm for obtaining initial values for the minimization process in covariance structure analysis is developed that is more generally applicable for computing parameters connected to latent variables than the currently existing ones. The algorithm is formulated in terms of the RAM model but can be extended. (SLD)

Decomposable models, which allow for the interdependence of structure among observable variables, are described. Each model is fully characterized by a set of conditional interdependence restrictions and can be visualized with an undirected as well as a special type of directed graph. (Author/JKS)

D.V. Budescu and J.L. Rogers (1981) proposed a method of adjusting correlations of scales to eliminate spurious components resulting from the overlapping of scales. Three reliability correction formulas are derived in this article that are based on more tenable assumptions. (SLD)

Effects of overextracting factors and components within and between maximum likelihood factor analysis and principal components analysis were examined through computer simulation of a range of factor and component patterns. Results demonstrate similarity of component and factor scores during overextraction. Overall, results indicate that…

The use of analysis of covariance in conjunction with the multivariate approach to analyzing repeated measures designs is considered for designs involving between- and within-subject factors, one dependent variable, and one observation per subject on the covariate. (Author/RL)

Two versions of a decision rule for determining the most appropriate number of clusters on the basis of a correlation matrix are presented, applied, and compared with three other decision rules. The new rule is efficient for determining the number of clusters on the surface level for multilevel data. (SLD)

Using a Monte Carlo simulation, a bootstrap procedure was evaluated for setting a confidence interval on the unrestricted population correlation (rho) assuming various degrees of incomplete truncation on the predictor. Sample size was the most important factor in determining accuracy and stability. Sample size should be at least 50. (SLD)