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A robust logistic discrimination model

Lookup NU author(s): Dr Kim Pearce

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Abstract

Logistic discrimination is a well documented method for classifying observations to two or more groups. However, estimation of the discriminant rule can be seriously affected by outliers. To overcome this, Cox and Ferry produced a robust logistic discrimination technique. Although their method worked in practice, parameter estimation was sometimes prone to convergence problems. This paper proposes a simplified robust logistic model which does not have any such problems and which takes a generalized linear model form. Misclassification rates calculated in a simulation exercise are used to compare the new method with ordinary logistic discrimination. Model diagnostics are also presented. The newly proposed model is then used on data collected from pregnant women at two district general hospitals. A robust logistic discriminant is calculated which can be used to predict accurately which method of feeding a woman will eventually use: breast feeding or bottle feeding.


Publication metadata

Author(s): Cox TF, Pearce KF

Publication type: Article

Publication status: Published

Journal: Statistics and Computing

Year: 1997

Volume: 7

Issue: 3

Pages: 155-161

ISSN (print): 0960-3174

ISSN (electronic): 0960-3174

Publisher: Springer New York LLC

URL: http://dx.doi.org/10.1023/A:1018530001135

DOI: 10.1023/A:1018530001135


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