ABSTRACT
It is known that when the multicollinearity exists in the logistic regression model, variance of maximum likelihood estimator is unstable. As a remedy, Schaefer et al. presented a ridge estimator in the logistic regression model. Making use of the ridge estimator, when some linear restrictions are also present, we introduce a restricted ridge estimator in the logistic regression model. Statistical properties of this newly defined estimator will be studied and comparisons are done in the simulation study in the sense of mean squared error criterion. A real-data example and a simulation study are introduced to discuss the performance of this estimator.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (No. 11501072), the Natural Science Foundation Project of CQ CSTC (No. cstc2015jcyjA00001), and the Scientific and Technological Research Program of Chongqing Municipal Education Commission (No. KJ1501114).