AN APPLICATION OF POISSON REGRESSION MODEL ON ROAD ACCIDENTS DATA IN KADUNA STATE, NIGERIA
DOI:
https://doi.org/10.33003/fjs-2024-0803-2472Keywords:
Poisson, Model, Accidents, Akaike Information Criterion (AIC)Abstract
The Poisson Regression model was used to analyze the data on road traffic crashes of Kaduna State from year 2014 to 2017. The data was collected from the Kaduna State Command of the Federal Road Safety Corps (FRSC). The analysis was carried out using the R (MASS Package) software. The variables considered are; Number of Persons Involved in accidents, Season (months of the year), Number of Crashes and Causes of Accidents. The results from the model were analyzed using the Akaike Information Criterion (AIC) and goodness of fit. Result shows that the Poisson Regression Model has an AIC value of 1185.7. The scatter-plots are clustered and it has few outliers from the predicted line. This is due to the good value of the deviance and the parameters of the model are very much estimated. The result of the Poisson Regression Model aids in overcoming the over-dispersion problem, resulting in a better fit. Thus, indicating the existence of significant dispersion.
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