A new kind of stochastic restricted biased estimator for logistic regression model

In the logistic regression model, the variance of the maximum likelihood estimator is inflated and unstable when the multicollinearity exists in the data. There are several methods available in literature to overcome this problem. We propose a new stochastic restricted biased estimator. We study the statistical properties of the proposed estimator and compare its performance with some existing estimators in the sense of scalar mean squared criterion. An example and a simulation study are provided to illustrate the performance of the proposed estimator.

Automated summary

In logistic regression model, multicollinearity can cause the variance of the maximum likelihood estimator to be inflated and unstable. A new stochastic restricted biased estimator is proposed to address this issue and its performance is compared with existing estimators through statistical properties and scalar mean squared criterion.