Factorial-Design Multiple-Discriminant Analysis

The standard, or simple, multiple-discriminant analysis is a statistical technique for analyzing data that consist of several measures on each individual in each of several groups. The technique is analogous to the analysis of variance (except that more than one measure is involved) in that it can be used for testing hypotheses about group differences. It is analogous to factor analysis (except that more than one group is involved) in that it provides a basis for interpreting the nature of group differences in terms of dimensions. It is analogous to multiple correlation (except that the criterion is group membership and not a linear variate) in that the results of the analysis can be used to predict the group to which an unclassified individual belongs. The purpose of this paper is to describe an extension of the simple multiple-discriminant analysis to the case where groups can be classified on some factorial basis: that is, where there is more than one basis for classifying groups. This factorial-design multiple-discriminant technique will be applied to a set of data that was previously analyzed by the conventional multiple-discriminant procedure

Analysis of variance · Basis (linear algebra · Discriminant · Factorial · Factorial experiment · Fractional factorial design · Group (periodic table · Linear discriminant analysis · Optimal discriminant analysis · Pattern recognition (psychology · Set (abstract data type · Simple (philosophy · Statistics · Advanced Statistical Methods and Models · Advanced Statistical Modeling Techniques · Artificial Intelligence · Computer Science · Mathematics

• Parameter Sensitivity for Discriminant Analysis

  Richard L Tate, John Bryant et al.•Multivariate Behavioral Research•1986

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