This paper provides a tutorial on epistemic network analysis (ENA), a novel method for identifying and quantifying connections among elements in coded data and representing them in dynamic network models. Such models illustrate the structure of connections and measure the strength of association among elements in a network, and they quantify…

Principal Component Analysis is widely used in applied multivariate data analysis, and this article shows how to motivate student interest in this topic using cricket sports data. Here, principal component analysis is successfully used to rank the cricket batsmen and bowlers who played in the 2012 Indian Premier League (IPL) competition. In…

The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…

It is known that for trivariate distributions, if two correlations are fixed, the remaining correlation is constrained. If just one is fixed, the remaining two are constrained. Both results are extended to the case of a multivariate distribution. (Author/JKS)

The goodness-of-fit of correlational pattern hypotheses has traditionally been assessed either with a likelihood ratio statistic or with a quadratic form statistic. Several alternative statistics, based on the use of the Fisher r-to-z transform, are proposed and assessed in a Monte Carlo experiment. (Author/JKS)

Illustrates a simple nonparametric alternative that can be used to test a hypothesis that two proximity matrices on the same set of variables or objects reflect a similar pattern of high and low entries. (RC)

Several important issues related to canonical correlation have been recognized and resolved during the last several years. The purpose of this presentation is to offer an organized, comprehensive, and current annotated bibliography of the many recent developments and extensions of canonical methods. The bibliography does not emphasize references…

Factor and cluster analyses are distinctly different multivariate procedures with different goals. However, when used in a complementary fashion, each set of methods can be used to enhance the interpretation of results found in the other set of methods. Simple examples illustrating the joint use of the methods are provided. (Author)

Presents a new approach for estimating missing observations together with the results of a Monte Carlo study of the relative strengths and weaknesses of this technique and three other available methods. These techniques are then examined with respect to their ability to use incomplete data to estimate the correlation matrix obtained using a full…

This paper reviews and develops summary measures of associations between multiple sets of variables through the application of canonical correlation analysis. These measures are subsequently applied to a specific research problem: a study of the determinants of housing status. Some of the data analysis situations for which canonical correlation is…

A method for obtaining teacher ratings from incomplete student ranking data is presented. The procedure involves finding the scores for the teachers on the first principal component of a student intercorrelation matrix, where the missing data are supplied by least squares. (Author)

Part and bi-partial canonical correlations were developed by extending the definitions of part and bi-partial correlation to sets of variates. These coefficients may be used to help researchers explore relationships which exist among several sets of normally distributed variates. (Author)

A Computer program written in FORTRAN IV is presented which will create a population of desired size with marginally normal score vectors manifesting any desired centroid and covariance matrix. Uses and documentation are provided. (Author)

A method for estimating variance-covariance matrices with incomplete data for use in discriminant function analysis is presented. An example of its use in college algebra course placement is also presented. (JKS)

The basic notion of variability is generalized from a univariate context to a multivariate context using two matrix functions, a determinant, and a trace, yielding a number of alternative multivariate indices of shared variation. Some problems in the interpretation of tests of multivariate hypotheses are reviewed. (Author/BW)