ERIC Number: ED395981
Record Type: RIE
Publication Date: 1996-Jan-26
Reference Count: N/A
Descriptive versus Predictive Discriminant Analysis: A Comparison and Contrast of the Two Techniques.
The use of multivariate statistics in the social and behavioral sciences is becoming more and more widespread. One multivariate technique that is commonly used is discriminant function analysis. This paper compares and contrasts the two purposes of discriminant analysis, prediction and description. Using a heuristic data set, a conceptual explanation of both techniques is provided with emphasis on which aspects of the computer printouts are essential for the interpretation of each type of discriminant analysis. Initially, discriminant analysis was designed to predict group membership, given a number of continuous variables. It also is used to study and explain group separation or group differences. Descriptive discriminant analysis has been used traditionally as a followup to a multivariate analysis of variance. The explanation of the differences in these two approaches includes discussion of how to: (1) detect violations in the assumptions of discriminant analysis; (2) evaluate the importance of the omnibus null hypothesis; (3) calculate the effect size; (4) distinguish between the structure matrix and canonical discriminant function coefficient matrix; (5) evaluate which groups differ; and (6) understand the importance of hit rates in predictive discriminant analysis. An appendix presents a syntax file from the Statistical Package for the Social Sciences. (Contains 7 tables and 20 references.) (SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Authoring Institution: N/A
Identifiers: Descriptive Discriminant Analysis; Predictive Discriminant Analysis
Note: Paper presented at the Annual Meeting of the Southwest Educational Research Association (New Orleans, LA, January 1996).