A generalized measure of association and an associated test of significance are presented for nominal independent variables in which any number or combination of interval, ordinal, or nominal dependent variables can be analyzed. A permutation test of significance is provided for the new measure. (SLD)

Conceptual rationales from five research contexts are presented, which all posit unmeasured variables that interact with observed independent variables to produce a complete model of the dependent variable. Strategies for overcoming related difficulties are outlined, including increased longitudinal assessment, oversampling of levels of…

The overidentification of structural equation models with latent variables is discussed. The use of two- and three-indicator models is not recommended since such models do not allow a testing of the crucial assumption of unidimensionality among indicators in most cases. Models with four or more indicators may be more sensitive to departures from…

Commonality analysis may be used as an adjunct to general linear methods as a means of determining the degree of predictive ability shared by two or more independent variables. For each independent variable, commonality analysis indicates how much of the variance of the dependent variable is unique to the predictor and how much of the predictor's…

Advantages of the use of multivariate commonality analysis are discussed and a small data set is used to illustrate the analysis and as a model to enable readers to conduct such an analysis. A noteworthy advantage of commonality analysis is that commonality honors the relationships among variables by determining the degree to which predictors in a…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Canonical correlation analysis is a multivariate statistical model which facilitates the study of interrelationships among multiple dependent variables and multiple independent variables. It identifies components of one set of variables that are most highly related linearly to the components of the other set of variables. The underlying logic of…

Identification and explication of construct relationships, under conditions of extraneous variable control in multiple regression and its multivariate analog, canonical analysis, were studied. Several data models were generated as a function of the interaction of partial correlation and orthogonal linear transformations on nursing examination…

The relationship between analysis of variance (ANOVA) methods and their analogs (analysis of covariance and multiple analyses of variance and covariance--collectively referred to as OVA methods) and the more general analytic case is explored. A small heuristic data set is used, with a hypothetical sample of 20 subjects, randomly assigned to five…

Analyzes a sample of over 4,700 orders for library materials at the University of California, Berkeley, in terms of the probability that the material will arrive and the factors that determine arrival. Models to evaluate the book ordering process are presented, and variables that may affect arrival time are discussed. (six references) (Author/LRW)

Variance formulas of H. E. Daniels and M. G. Kendall (1947) are generalized to allow for the presence of ties and variance of the sample tau correlation. Applications of these generalized formulas are discussed and illustrated using data from a 1965 study of contraceptive use in 15 developing countries. (SLD)

This paper reports the results of a Monte Carlo investigation of Type I errors in the single group repeated measures design where multiple measures are collected from each observational unit at each measurement occasion. The Type I error of three multivariate tests were examined. These were the doubly multivariate F test, the multivariate mixed…