Assessing the effects of different types of covariates for binary logistic regression

Hamzah Abdul Hamid, Yap Bee Wah, Xian-Jin Xie, Hezlin Aryani Abd Rahman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

It is well known that the type of data distribution in the independent variable(s) may affect many statistical procedures. This paper investigates and illustrates the effect of different types of covariates on the parameter estimation of a binary logistic regression model. A simulation study with different sample sizes and different types of covariates (uniform, normal, skewed) was carried out. Results showed that parameter estimation of binary logistic regression model is severely overestimated when sample size is less than 150 for covariate which have normal and uniform distribution while the parameter is underestimated when the distribution of covariate is skewed. Parameter estimation improves for all types of covariates when sample size is large, that is at least 500.

Original languageEnglish (US)
Title of host publication2nd ISM International Statistical Conference 2014, ISM 2014
Subtitle of host publicationEmpowering the Applications of Statistical and Mathematical Sciences
EditorsNor Aida Zuraimi Md Noar, Roslinazairimah Zakaria, Wan Nur Syahidah Wan Yusoff, Mohd Sham Mohamad, Mohd Rashid Ab Hamid
PublisherAmerican Institute of Physics Inc.
Pages425-430
Number of pages6
ISBN (Electronic)9780735412811
DOIs
Publication statusPublished - Jan 1 2015
Event2nd ISM International Statistical Conference 2014: Empowering the Applications of Statistical and Mathematical Sciences, ISM 2014 - Kuantan, Pahang, Malaysia
Duration: Aug 12 2014Aug 14 2014

Publication series

NameAIP Conference Proceedings
Volume1643
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2nd ISM International Statistical Conference 2014: Empowering the Applications of Statistical and Mathematical Sciences, ISM 2014
CountryMalaysia
CityKuantan, Pahang
Period8/12/148/14/14

    Fingerprint

Keywords

  • Binary logistic regression
  • Parameter estimation
  • Simulation

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Hamid, H. A., Wah, Y. B., Xie, X-J., & Rahman, H. A. A. (2015). Assessing the effects of different types of covariates for binary logistic regression. In N. A. Z. M. Noar, R. Zakaria, W. N. S. W. Yusoff, M. S. Mohamad, & M. R. A. Hamid (Eds.), 2nd ISM International Statistical Conference 2014, ISM 2014: Empowering the Applications of Statistical and Mathematical Sciences (pp. 425-430). (AIP Conference Proceedings; Vol. 1643). American Institute of Physics Inc.. https://doi.org/10.1063/1.4907476