Binary Logistic Regression Analysis to Study Factors Affecting Addiction
DOI:
https://doi.org/10.31272/jae.i151.1538Keywords:
Binary , Logistic , Addicted , Not Addicted , categories, Binary, Logistic, Addicted, Not Addicted, categoriesAbstract
The problem of drug addiction is considered one of the most dangerous health, social, and psychological issues facing the world. The research aims to study the effect of some variables on addiction. Factors influencing addiction using the logistic regression model. Cases were classified into addicted and non-addicted based on variations in the level of addiction and the number of times the individual visited the hospital, which represents the dependent variable. The independent variables represent the factors influencing addiction. The sample consists of 160 cases of both genders and various ages, based on a questionnaire that includes 20 questions about the causes of addiction. The results showed that the most significant factors leading to addiction were chronic diseases, imprisonment or detention, as well as smoking and hookah use. The SPSS statistical software was applied to obtain and analyse the results.
Downloads
References
[1] Al-Rawi, Khasha'a Mahmoud (1987). "Introduction to Regression Analysis." Directorate of Dar Al-Kutub for Printing and Publishing / University of Mosul.
[2] Abd Al-Mun'im, Dr. Tharwat Mohammed (2005). "Regression Book." Anglo-Egyptian Library.
[3] Anthony Hayter, Wei Liu, & Chanita Tantipoj (2022). "Binary Response Analysis Using Logistic Regression in Dentistry." Department of Anatomy, Faculty of Dentistry, Mahidol University, Bangkok 10400, Thailand. DOI: https://doi.org/10.1155/2022/5358602
[4] Hajar, F. T., & Ibrahim, W. S. (2019). Use the logistic regression model to find the most important factors affecting lung cancer in Iraq in 2017. Journal of Administration and Economics, 44, 121.
[5] Ibrahim, W. S. (2020). To determine the most important factors affecting pancreatic cancer in Iraq using the logistic regression model. Periodicals of Engineering and Natural Sciences (PEN), 8(1), 277-283. DOI: 10.21533/pen.v8i1.1189 DOI: https://doi.org/10.21533/pen.v8.i1.1046
[6] Irfan, P., & Heman, D. (2006). "A Logistic Regression Analysis of Ischemic Heart Disease." Journal of Applied Sciences. o DOI: 10.3923/jas.2006
[7] Mohammed, A. J., & Ibrahim, W. S. (2020). Study of the probability of change in share prices based on the value of the Babylon Hotel using logistic regression. Journal of College of management and Economics, 43(123), 434-446.
[8] Sekulovski, N., Bartoš, F., Bergh, D., Arena, G., Godmann, R., Goyal, V., Julius M. Pfadt, Marsman, M., & Adrian E. Raftery (2025). "Comparing Variable Selection and Model Averaging Methods for Logistic Regression." December 1. 10.31234/osf.io/7g29a.
[9] Ghanem, Dr. Adnan, & Al-Jaouni, Dr. Fereed Khalil (2011). "Using Binary Logistic Regression Technique in Studying the Economic and Social Determinants of Household Income Sufficiency (An Empirical Study on a Random Sample of Families in Damascus Governorate)." Journal of Damascus University for Economic and Legal Sciences, Volume 9.
[10] Ibrahim, W. S., Majeed, G. H., & Anber, J. A. (2022). Determine the most important factors affecting breast cancer in Iraq. Periodicals of Engineering and Natural Sciences, 10(2), 260-266. https://doi.org/10.21533/pen.v10.i2.604 DOI: https://doi.org/10.21533/pen.v10.i2.604
[11] Daeesh, A. Mohammed Amin, & Mohammed Sari (2017). "Logistic Regression Model: Its Concept, Characteristics, and Applications." Algeria.
[12] Hosmer, D. W., & Lemeshow, S. (2000). "Applied Logistic Regression" (Second Edition). New York: John Wiley & Sons, Inc. DOI: 10.1002/0471722146 DOI: https://doi.org/10.1002/0471722146
[13] Talib, Haider Raed, & Mazloom, Sara Adel (2020). "Using Binary Logistic Regression Technique to Analyze Factors Affecting Heart Disease Mortality." Applied Study on a Sample of Patients in Dhi Qar Governorate. Journal of Al-Rafidain University College for Sciences, Issue (46). DOI: 10.55562/jrucs.v46i1 DOI: https://doi.org/10.55562/jrucs.v46i1
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Suhad Ahmed Ahmed
This work is licensed under a Creative Commons Attribution 4.0 International License.
The journal of Administration & Economics is an open- access journal that all contents are free of charge. Articles of this journal are licensed under the terms of the Creative Commons Attribution International Public License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) that licensees are unrestrictly allowedto search, download, share, distribute, print, or link to the full text of the articles, crawl them for indexing and reproduce any medium of the articles provided that they give the author(s) proper credits (citation). The journal allows the author(s) to retain the copyright of their published article.
Creative Commons-Attribution (BY) 
