On the Restricted Liu Estimator in the Logistic Regression Model


Siray G. U. , Toker S., KAÇIRANLAR S.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, vol.44, no.1, pp.217-232, 2015 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 44 Issue: 1
  • Publication Date: 2015
  • Doi Number: 10.1080/03610918.2013.771742
  • Journal Name: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.217-232
  • Keywords: Logistic regression, Multicollinearity, Restricted Liu estimator, Restricted maximum likelihood estimator, RIDGE-REGRESSION

Abstract

The logistic regression model is used when the response variables are dichotomous. In the presence of multicollinearity, the variance of the maximum likelihood estimator (MLE) becomes inflated. The Liu estimator for the linear regression model is proposed by Liu to remedy this problem. Urgan and Tez and Mansson et al. examined the Liu estimator (LE) for the logistic regression model. We introduced the restricted Liu estimator (RLE) for the logistic regression model. Moreover, a Monte Carlo simulation study is conducted for comparing the performances of the MLE, restricted maximum likelihood estimator (RMLE), LE, and RLE for the logistic regression model.