Intersectional approaches have become increasingly important for explaining educational inequalities because they help to improve our understanding of how individual experiences are shaped by simultaneous membership in multiple social categories that are associated with interconnected systems of power, privilege, and oppression. For years, there…

A large sample of 33,000 university alumni records were cluster-analyzed to generate six groups relatively unique in their respective attribute values. The attributes used to cluster the former students included average gift to the university's foundation and to the alumni association for the same institution. Cluster detection is useful in this…

C. Huberty (1994) recently noted that "It is quite common to find the use of 'stepwise analyses' reported in empirically based journal articles." Stepwise methods are used (incorrectly) by some researchers either to select variables to retain for further analyses or to evaluate the relative importance of various variables. Of course,…

Although comments of D.J. Nordlund and R. Nagel are welcomed, their arguments are not sufficient to accept the recommendation of using total variance estimates to standardize canonical discriminant function coefficients. If standardized coefficients are used to help interpret a discriminant analysis, pooled within-group variance estimates should…

The purpose of this paper is to assist researchers, practitioners, and graduate students in identifying and addressing key questions related to the task of choosing among the analytic techniques designed to analyze a dichotomized dependent variable with a set of independent variables. The discussion is limited to (1) the analysis of data by the…

A brief historical background of discriminant analysis is given, with a description of the variety of roles that discriminant analysis can perform. Focus is on the classification role of discriminant analysis and how it can be performed by using Fisher's classification functions or the canonical discriminant functions. A small hypothetical data…

The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)

Mathematical programing formulas are introduced as new approaches to solve the classification problem in discriminant analysis. The research literature is reviewed, and an illustration using a real-world classification problem is provided. Issues relevant to potential uses of these formulations are discussed. (TJH)

Addresses the delivery of supervision skills by presenting a model for identification and training of those skills, the roles in which skills are demonstrated, and types of choices or discriminations necessary to make in tutoring trainees through the counseling practicum. (Author)

Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…

Compares assessment results of inpatients with alcoholism who have made a serious suicide attempt and a matched sample of inpatients with alcoholism who have no history of suicide attempts. Discriminant function analysis reveals that depression, social hopelessness, and socially prescribed perfectionism are unique discriminators of suicide groups.…

Presents a microcomputer-based qualitative discriminant process (QDP) for scoring and ranking in group support systems that is relevant to group decision-making situations that involve the evaluation of alternatives. Scoring and ranking techniques are described, and a case illustration using the QDP is discussed. (Contains 50 references.) (LRW)

Describes two invariance tests, the jackknife procedure and Procrustean rotation, and applies them in a discriminant analysis for this heuristic study. Invariance testing helps to prevent overemphasis on findings of statistical significance and overgeneralization of a research result, and thus is gaining favor as an indicator of result importance.…

This study presents an overview of Monte Carlo studies in discriminant analysis. Some common questions about the use of Monte Carlo techniques are answered through a brief literature review of articles on discriminant analysis in which Monte Carlo methods are used. The articles cover many research points, such as comparing error rate estimates,…

This paper reports on a study conducted to determine the extent to which failing secondary school students can be identified in advance through analysis of student records. The research, conducted in an urban school district, utilized data such as achievement test results, school attendance, and course grades, as well as a survey of sample…