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

Authors

  • Nasir Saleem saleem a:1:{s:5:"en_US";s:72:"Department of Statistics Bahauddin Zakariya University, Multan, Pakistan";}
  • Atif Akbar Associated professor Department of Statistics Bahauddin Zakariya University (BZU), Multan, Pakistan
  • A. H. M. Rahmatullah Imon Professor Department of mathematical sciences, Ball State university, (USA)
  • Javaria Ahmad khan Department of Statistics Bahauddin Zakariya University (BZU), Multan, Pakistan

DOI:

https://doi.org/10.22452/josma.vol6no1.3

Keywords:

Diagnostics, Binomial regression model, GLM, CERES and PR plots, multicollinearity

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.

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Published

2024-05-30

How to Cite

saleem, N. S., Akbar, A. ., Rahmatullah Imon, A. H. M. ., & Ahmad khan, J. . (2024). Multicollinearity in Binomial Regression: A comparison between CERES and PR Plots for detection. Journal of Statistical Modeling &Amp; Analytics (JOSMA), 6(1). https://doi.org/10.22452/josma.vol6no1.3

Issue

Vol. 6 No. 1 (2024): Journal of Statistical Modeling & Analytics (JOSMA)

Section

Articles