Logistic regression diagnostics in ridge regression

Ozkale M. R., Lemeshow S., STURDIVANT R.

COMPUTATIONAL STATISTICS, vol.33, no.2, pp.563-593, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 33 Issue: 2
  • Publication Date: 2018
  • Doi Number: 10.1007/s00180-017-0755-x
  • Journal Name: COMPUTATIONAL STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.563-593
  • Keywords: Logistic regression, Regression diagnostics, Ridge logistic estimator, Multicollinearity, INFLUENTIAL OBSERVATIONS, LINEAR-REGRESSION, ESTIMATORS, MODELS
  • Çukurova University Affiliated: Yes

Abstract

The adverse effects of multicollinearity and unusual observations are seen in logistic regression and attention had been given in the literature to each of these problems separately. However, multicollinearity and unusual observations can arise simultaneously in logistic regression. The objective of this paper is to propose the statistics for detecting the unusual observations in an ill-conditioned data set under the ridge logistic estimator. A numerical example and two Monte Carlo simulation studies are used to illustrate the methodology. The present investigation shows that ridge logistic estimation copes with unusual observations by downweighting their influence.