Multicollinearity in Binomial Regression: A comparison between CERES and PR Plots for detection

Abstract

For identification of multicollinearity, residuals are most common tool in linear regression model, but a limited literature is available which describe this situation in case of GLM. Binomial regression model has extensive applicability in analyzing with heart disease and many other types of data. Here, we have offered a comparison between CERES and PR plots in BRM to detect the multicollinearity problem. At first, we have developed a comparison tool and then apply them to real-world and simulated data. We examine and compare these plots on the detection of a possible multicollinearity separately and observe that the performance of CERES plot is better than compare to the PR plots.