There are two distinct but related purposes for carrying out a "discriminant analysis": (1) discrimination, and (2) classification. The primary objective of this paper was to review the outputs of selected computer programs often used to carry out a "discriminant analysis" with respect to these two purposes. Information provided by the programs on…

Adult subjects (N=10) were studied to determine whether inconsistent information about others produces more discrimination of people or leads to alternative ways of categorizing. Pretest-posttest indications indicated inconsistency produced more discrimination of others and alternative ways of categorizing others. (SBP)

A Monte Carlo study evaluated the effectiveness of three rules of classifying objects into clusters: nearest neighbor classification; nearest centroid assignment; and quadratic discriminant analysis. Results suggest that the nearest neighbor rule is a useful tool for assessing the validity of the clustering procedure of J. H. Ward (1963). (SLD)

Tests for and identifies populations within a family of electronics industries. Data include 669 United States and 144 Japanese electronics firms. Demonstrates the relevance of a general organizational classification for explaining how different natural selection processes affect different populations. (75 references) (MLF)

Predictive discriminant analysis involves a technique used in multivariate classification, i.e., in predicting membership in well-defined groups for units on which multiple measures are available. The validation (assessment) of group membership predictions pertains to two problems: estimating true proportions of correct classifications (i.e., hit…

"Classification: Purposes, Principles, Progress, Prospects" by Robert R. Sokal is reprinted in this document. It summarizes the principles of classification and cluster analysis in a manner which is of specific value to the Marine Corps Office of Manpower Utilization. Following the article is a 184 item bibliography on cluster analysis…

Interprets College Interest Inventory, administered to 284 students, both ways, with neither method proving superior. Suggests that under restricted conditions, discriminant function might be more appropriate for counseling purposes than configural analysis. (Author/CJ)

We examined how strongly motivation, metacognition, and psychopathology acted as predictors of learning disabilities (LD). The results from five studies suggested that level of motivation (as shown through self-efficacy, motivational force, task avoidance, goal commitment, or self-concept) was highly accurate in classifying students with or at…

The authors examined the Trauma Symptom Inventorys (TSI) ability to discriminate 88 student post-traumatic stress disorder (PTSD) simulators screened for genuine PTSD from 48 clinical PTSD-diagnosed outpatients. Results demonstrated between-group differences on several TSI clinical scales and the Atypical Response (ATR) validity scale.…

Multiple samples of university students (N = 1,537) completed the Almost Perfect Scale-Revised (APS-R; R. B. Slaney, M. Mobley, J. Trippi, J. Ashby, & D. G. Johnson, 1996). Cluster analyses, cross-validated discriminant function analyses, and receiver operating characteristic curves for sensitivity and specificity of APS-R scores were used to…

This paper focuses on three aspects related to the conceptualization and application of canonical correlation analysis as a dominant statistical model: (1) partial canonical correlation analysis and its application in statistical testing; (2) the relation between canonical correlation analysis and discriminant analysis; and (3) the relation…

Discriminant analysis of Holland's Self Directed Search and Vocational Preference Inventory significantly improved the predictive validity of his classification scheme, over the traditional method of assigning high point codes. These results were obtained with both an initial and a replication sample of undergraduates pursuing various degrees. The…

Three estimates of the probabilities of correct classification in predictive discriminant analysis were computed using mathematical formulas, resubstitution, and external analyses: (1) optimal hit rate; (2) actual hit rate; and (3) expected actual hit rate. Methods were compared using Monte Carlo sampling from two data sets. (Author/GDC)

Seven discriminant analyses were performed with significant group separation occurring for six of these. Classification analyses indicated that using the 10 major subtests produced accurate classification in approximately 71 percent of cases. Results were discussed in the light of previous research methodologies and the debate as to the…

The issues in the interpretation of discriminant analyses presented are restricted to the typical uses of discriminant analysis by behavioral science researchers. Because behavioral researchers use computer programs packages, the issues discussed deal with information obtainable from the package discriminant analysis programs. The following issues…