Special Issue 2022 – Call for Papers
A New Role for Statistics: The Joint Special Issue of "Statistics in Transition New Series" (SiTns) and "Statystyka Ukraïny" (SU)
Varathan Nagarajah https://orcid.org/0000-0003-2014-8144

© Nagarajah Varathan. Article available under the CC BY-SA 4.0 licence

ARTICLE

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ABSTRACT

In this paper, an improved ridge type estimator is introduced to overcome the effect of multicollinearity in logistic regression. The proposed estimator is called a modified almost unbiased ridge logistic estimator. It is obtained by combining the ridge estimator and the almost unbiased ridge estimator. In order to asses the superiority of the proposed estimator over the existing estimators, theoretical comparisons based on the mean square error and the scalar mean square error criterion are presented. A Monte Carlo simulation study is carried out to compare the performance of the proposed estimator with the existing ones. Finally, a real data example is provided to support the findings.

KEYWORDS

Logistic Regression, Multicollinearity, ridge estimator, Modified almost unbiased ridge logistic estimator, Mean square error

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