Fitting Models of Vulnerability to Toxicity with Generalized Linear Models
International Journal of Data Science and Analysis
Volume 3, Issue 5, October 2017, Pages: 46-57
Received: Aug. 21, 2017; Accepted: Sep. 15, 2017; Published: Nov. 8, 2017
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Ganiyu Abayomi Dawodu, Statistics Department, College of Physical Sciences, Federal University of Agriculture, Abeokuta (FUNAAB), Nigeria
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People are often exposed to toxic or hazardous (e.g. radioactive radon and lead) elements and rays, without even knowing so. Toxicity often results from an individual’s prolonged exposure to toxic substances. A thorough examination of some individuals’ blood or urine samples for the quantities of hazardous substances or elements, often gives a multivariate data (i.e. matrix of cases against elements) on toxicity. The pertinent response variable is often binary response (or count data) type and hence the Generalized Linear Models (GLM) of it can be fitted using our proposed techniques. This paper purports to identify models in GLM that can be used to study toxicity when it is ‘captured’ as count data or Binary Response Variables (BRV). An illustration of how the techniques work is done by using a sample of data on some artisans.
GLM, Exploratory Data Analysis (EDA), BRV, Count Data (CD), Toxicity, R
To cite this article
Ganiyu Abayomi Dawodu, Fitting Models of Vulnerability to Toxicity with Generalized Linear Models, International Journal of Data Science and Analysis. Vol. 3, No. 5, 2017, pp. 46-57. doi: 10.11648/j.ijdsa.20170305.13
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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