Application of Cox Regression in Modeling Survival Rate of Drug Abuse
American Journal of Theoretical and Applied Statistics
Volume 7, Issue 1, January 2018, Pages: 1-7
Received: Jun. 28, 2017; Accepted: Jul. 10, 2017; Published: Dec. 20, 2017
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Authors
Robert Kasisi, Department of Mathematics and Computer Science, Moi University, Eldoret, Kenya
Joseph Koske, Department of Mathematics and Computer Science, Moi University, Eldoret, Kenya
Mathew Kosgei, Department of Mathematics and Computer Science, Moi University, Eldoret, Kenya
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Abstract
Drug and substance abuse is a serious health problem in many countries. In Kenya drug abuse is one of the leading causes of mortality. Modeling the rate of survival of drug users involves determining time to relapse of drug users and the number of treatment episodes for full recovery. A study of the treatment programs that the subjects are enrolled was conducted. Those subjects who completed the treatment program and fully recovered from drug use were said to have survived while those who dropped out of the treatment program were said to have not survived. The objective of this study was to fit a cox repression model in determining a set of significant covariates for survival of drug users in Kenya. The dependent variable was survival time of the subject and the independent variables were age, gender, residence, marital status, job status, mode of drug abused and the type of drug abused. The study used data on drug use from Mathari National Hospital. Cox proportional hazards model was used to establish the hazard rate of a subject entering into drug use at different stages of life. Survival rate was 36.37% with the females having higher survival rates compared to male drug users. Age, gender, marital status and employment status were significant predictors of survival rate of drug users. The study recommended that subjects who were aged below 30 years, single and jobless required more intensive and specialized treatment. More intervention programs should be targeted to these subjects.
Keywords
Survival Rate, Cox Regression, Intervention Programs, Hazard Rate, Drug Abuse
To cite this article
Robert Kasisi, Joseph Koske, Mathew Kosgei, Application of Cox Regression in Modeling Survival Rate of Drug Abuse, American Journal of Theoretical and Applied Statistics. Vol. 7, No. 1, 2018, pp. 1-7. doi: 10.11648/j.ajtas.20180701.11
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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