Comparing Linear Discriminant Function With Logistic Regression for the Two-Group Classification Problem

ArticleinThe Journal of Experimental Education 67(3):265-286 · March 1999with30 Reads
Impact Factor: 1.09 · DOI: 10.1080/00220979909598356

    Abstract

    The performances of predictive discriminant analysis (PDA) and logistic regression (LR) for the 2-group classification problem were compared. The authors used a fully crossed 3-factor experimental design (sample size, group proportions, and equal or unequal covariance matrices) and 2 data patterns. When the 2 groups had equal covariance matrices, PDA and LR performed comparably for the conditions of both equal and unequal group proportions. When the 2 groups had unequal covariance matrices (4:1, as implemented in this study) and very different group proportions, PDA and LR differed somewhat with regard to the classification error rates of the 2 groups, but the classification error rates of the 2 methods for the total sample remained comparable. Sample size played a relatively minor role in the classification accuracy of the 2 methods, except when LR was used under relatively small sample-size conditions.