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Stability and bias of classification rates in biological applications of discriminant analysis

Journal of Wildlife Management

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Abstract

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Stability and bias of classification rates in biological applications of discriminant analysis
Series title:
Journal of Wildlife Management
Volume
54
Issue:
2
Year Published:
1990
Language:
English
Contributing office(s):
Patuxent Wildlife Research Center
Description:
331-341
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Journal of Wildlife Management
First page:
331
Last page:
341
Number of Pages:
11