Abstract
In general regression analysis, standardized beta weights are often used to compare strength of prediction across variables. In order to consider obtaining an estimation of standardized logistic regression coefficients, the model must be rescaled to include such coefficients. One of the reasons to have the coefficient standardized is we will have more informative coefficients compared to unstandardized coefficients, especially for variables which have no natural metric. Several approaches of obtaining standardized coefficients in logistic regression are available in literatures. This article studies the performance of the existing approaches to obtain standardized logistic regression coefficient based on real data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Menard, S. (2002). Applied logistic regression analysis (Quantitative applications in the social sciences, no. 106). Thousand Oaks: Sage.
Menard, S. (2011). Standards for standardized logistic regression coefficients. Social Forces, 89(4), 1409–1428.
Kim, J., & Ferree, G. D. (1996). Standardization in causal analysis. Sociological Methods and Research, 10, 187–210.
Menard, S. (2004). Six approaches to calculating standardized logistic regression coefficients. The American Statistician, 58(3), 218–223.
Agresti, A. (2007). An introduction to categorical data analysis (2nd ed.). New York: Wiley.
Goodman, L. A. (1972). A modified multiple regression approach to the analysis of dichotomous variables. American Sociological Review, 37, 28–46.
Menard, S. (1995). Applied logistic regression analysis. Thousand Oaks: Sage.
Brockmann, H. J. (1996). Satellite male groups in horseshoe crabs; Limulus polyphemus. Ethology, 102, 1–21.
Long, J. S. (1997). Regression models for categorical and limited dependent variables. Thousand Oaks: Sage.
Acknowledgment
The authors are grateful to University Grants Scheme by Universiti Putra Malaysia for awarding a research grant for supporting the research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media Singapore
About this paper
Cite this paper
Fitrianto, A., Hanafi, I. (2014). On the Performance of Several Approaches to Obtain Standardized Logistic Regression Coefficients. In: Kasim, A., Wan Omar, W., Abdul Razak, N., Wahidah Musa, N., Ab. Halim, R., Mohamed, S. (eds) Proceedings of the International Conference on Science, Technology and Social Sciences (ICSTSS) 2012. Springer, Singapore. https://doi.org/10.1007/978-981-287-077-3_63
Download citation
DOI: https://doi.org/10.1007/978-981-287-077-3_63
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-287-076-6
Online ISBN: 978-981-287-077-3
eBook Packages: Humanities, Social Sciences and LawSocial Sciences (R0)