Abstract:
In this paper, we propose a new efficient estimator namely Optimal
Generalized Logistic Estimator (OGLE) for estimating the parameter in
a logistic regression model when there exists multicollinearity among
explanatory variables. Asymptotic properties of the proposed estimator
are also derived. The performance of the proposed estimator over the
other existing estimators in respect of Scalar Mean Square Error crite rion is examined by conducting a Monte Carlo simulation.
