Concomitant with Nigerian Road Traffic Accidents: An Application of a Generalized Linear Model - Oluwafemi Samson BALOGUN; Sunday Adewale OLALEYE; Xiao-Zhi GAO; Pekka TOIVANEN (Communications of International Proceedings, 2021)
This study aims to apply a generalized linear model for investigating the relationship between road traffic accidents and the resulting fatalities in Nigeria. The main objectives are to determine the most suitable model fits, compare the models used, and examine the relationship between the total cases and log deaths by modelling the number of road traffic accidents in Nigeria. The study adopts Poisson regression and negative binomial regression model for data analysis to achieve the set goals. The data used for this research are secondary data collected from annual reports on road traffic accidents of the Federal Road Safety Commission of Nigeria between 1960 and 2017. The study establishes that the number of traffic accidents on roads in Nigeria is continually increasing, and efforts by the government and relevant agencies have been mostly unsuccessful in addressing this danger. Moreover, the highly dangerous conditions on Nigerian roads result in a daily loss of innocent lives that otherwise would have significantly contributed to economic growth.
Keywords: Regression ‧ Poisson ‧ Negative Binomial ‧ Road Traffic Accident ‧ Count Data