Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/266324 
Year of Publication: 
2022
Citation: 
[Journal:] Statistics in Transition new series (SiTns) [ISSN:] 2450-0291 [Volume:] 23 [Issue:] 3 [Publisher:] Sciendo [Place:] Warsaw [Year:] 2022 [Pages:] 113-126
Publisher: 
Sciendo, Warsaw
Abstract: 
In this paper, an improved ridge type estimator is introduced to overcome the effect of multi-collinearity 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.
Subjects: 
Logistic Regression
Multicollinearity
ridge estimator
Modified almost unbiased ridge logistic estimator
Mean square error
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Article

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