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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/8069

Title: Statistical models for count data with applications to road accidents in Ghana
Authors: Adjei, Isaac Mensah
Issue Date: 9-Nov-2015
Abstract: Road accidents in Ghana seems to be on ascendency and the root causes of these accidents have been attributed to issues such as human errors and superstitions. Since the occurrence of accidents are discrete, they are often modeled using count regression models. It is therefore the purpose of this study to determine an appropriate count regression model that adequately fits road accidents on urban roads in Ghana and to determine the key predictors of road accidents using the appropriate count model with respect to the expected number of person killed in an accident. Several models fitted using count data (occurrences of road accidents) in the field of transportation were compared.These models include Poisson,Negative Binomial and Conway-Maxwell-Poisson count regression models . To compare the performance of these models, the various model selection methods such as Deviance goodness of fit, Akaike’s Information Criterion (AIC)and Bayesian Information Criterion (BIC) were employed. Because the values of the Deviance goodness of fit, AIC and BIC respectively of the Negative Binomial was the smallest as compared to that of Conway-Maxwell-Poisson and Poisson models, it appeared that the Negative Binomial model performed best as compared to the Poisson and the CMP model. Base on the appropriate count regression model selected (Negative Binomial model) the key predictors that contributed significantly and had a high effect on the expected number of persons to be killed in a road accidents within a particular time were Head-on collision as Collision type, Improper-overtaking and Loss of control as Driver errors, Bus/minibus as Type of vehicle, Fig/midst as Weather condition and Night with street lights off as Light condition.
Description: A Thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology In partial fulfillment of the requirement for the Degree of M.Phil Mathematical Statistics, 2015
URI: http://hdl.handle.net/123456789/8069
Appears in Collections:College of Science

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