1984•Communication in Statistics- Theory and MethodsRequires access

A ridge logistic estimator

Robert L. Schaefer, Larry D. Roi, Robert A. Wolfe

Open publisher page 274 citations

Abstract

It is found that multicollinearity among the independent variables in logistic regression inflates the variances of the maximum likelihood estimator. A Ridge type estimator is proposed that will have smaller total mean squared error than the maximum likelihood estimator under certain conditions. Empirical study results are presented that evaluate this estimator for different sample sizes and degrees of multicollinearity.

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What this paper is about

It is found that multicollinearity among the independent variables in logistic regression inflates the variances of the maximum likelihood estimator. A Ridge type estimator is proposed that will have smaller total mean squared error than the maximum likelihood estimator under certain conditions. Empirical study results are presented that evaluate this estimator for different sample sizes and degrees of multicollinearity.

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OpenAlex reports 274 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

It is found that multicollinearity among the independent variables in logistic regression inflates the variances of the maximum likelihood estimator. A Ridge type estimator is proposed that will have smaller total mean squared error than the maximum likelihood estimator under certain conditions. Empirical study results are presented that evaluate this estimator for different sample sizes and degrees of multicollinearity.

Key concepts: Ridge, Estimator, Geology, Computer science, Statistics, Environmental science, Mathematics, Paleontology

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