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TY  - JOUR
AU  - Sagamiko, Thadei
AU  - Mbare, Nyimvua 
PY  - 2021/02/15
Y2  - 2025/07/30
TI  - Modelling Road Traffic Accidents Counts in Tanzania: A Poisson Regression Approach
JF  - Tanzania Journal of Science
JA  - Tanz. J. Sci.
VL  - 47
IS  - 1
SE  - Articles
DO  - 10.4314/tjs.v47i1.26
UR  - http://tjs.udsm.ac.tz/index.php/tjs/article/view/48
SP  - 308-314
AB  - &lt;p&gt;Road traffic accidents have become serious threats to Tanzanians in recent years. The outcry&lt;br&gt;emanates from the increasing prevalence of negative effects of accidents on human lives,&lt;br&gt;properties, environments and the economy. Poisson regression model was used to study the&lt;br&gt;relationship between road accidents and the factors facilitating them in Tanzania. Count data on&lt;br&gt;yearly road traffic accidents for Tanzania covering the period 1993 to 2019 were used. Due to&lt;br&gt;over-dispersion of Poisson regression model, quasi-Poisson regression model was found the most&lt;br&gt;appropriate approach for the analysis of these data. Results indicated that all predictors are&lt;br&gt;significant under Poisson regression model with p-value less than 0.05 but high speed was found&lt;br&gt;insignificant using quasi-Poisson regression model. All factors causing road accidents predicted&lt;br&gt;minor increase of accidents, showing that current control measures on road accidents are likely to&lt;br&gt;be effective.&lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;strong&gt;Keywords&lt;/strong&gt;: Road accidents; Poisson regression; Over-dispersion; Deviance; Variance inflation&lt;br&gt;factor.&lt;/p&gt;
ER  -