A way of identifying non-random patterns of effects on a group of individuals as a result of some intervention when a sample of participants is arrayed according to some indices of similarity is presented. The principle of proximal similarity and the concept of pattern matching provide the background for this effort. Major advantages are the…

Various analytic choices in principal components and common factor analysis are discussed. Differences and similarities among these extraction methods are explained, and aids in interpreting the origin of detected effects are explored. Specifically, the nature and use of structure and pattern coefficients are examined. Communalities and methods…

Data reduction techniques seek to combine variables that account for patterns of variation in observed dependent variables in such a way that a simpler model is available for analysis. Factor analysis is a data reduction technique that attempts to model or explain a set of variables in terms of their associations. To understand why this technique…

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Many researchers acknowledge the prominent role that factor analysis can play in efforts to establish construct validity. Data can be analyzed with no preconceived ideas about the underlying constructs of structure of the data. This approach is exploratory factor analysis, Another approach is used when the researcher has an understanding of the…

In many testing situations, differential item functioning (DIF) is a potentially serious problem. It occurs when a test item appears to be easier for one group of examinees than another even after controlling for overall skill level. Differential person functioning (DPF) can occur when "items" can be considered raters and the persons are the…

Described herein are formulas and computational procedures for estimating the mean and second through fourth central moments of universe scores through multiple matrix sampling. Additionally, procedures are given for approximating the standard error associated with each estimate. All procedures are applicable when items are scored either…

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…

The Individual Scaling with Individual Subjects (ISIS) procedure appears to be a viable implementation of an incomplete design for collecting real as well as simulated data. Applied to a multidimensional set of data, it reduced the number of judgments required by more than half and yet gave the same number of dimensions. (Author/RC)

A relatively simple technique for assessing the convergence of sets of variables across method domains is presented. The technique, two-step principal components analysis, empirically orthogonalizes each method domain into sets of components, and then analyzes convergence among components across domains. (Author)

The use of multiple regression as a data-analytic tool is examined for the cases of balanced and unbalanced designs. The utility of this method for testing specific contrasts, both orthogonal and nonorthogonal is discussed and some interpretive cautions are examined. (Author)

Although the issue of dimensionality of the data obtained from educational and psychological tests has received considerable attention, the terms "unidimensional" and "multidimensional" have not been used very precisely. One use of the term dimensionality is to refer to the number of hypothesized psychological constructs…

A method is proposed and illustrated for estimating the degree to which a factor rotation to a hypothesized target represents an improvement over rotation to a random target. (Author)

Monte Carlo procedures were used to investigate the properties of a nonmetric multidimensional scaling algorithm when used to scale an incomplete matrix of dissimilarities. Recommendations for users wishing to scale incomplete matrices are made. (Author/RC)