Statistical Model Of Road Traffic Crashes Data In Anambra State Nigeria A Poisson Regression Approach

Abstract Road traffic crashes are count discrete in nature. When modeling discrete data for characteristics and prediction of events it is appropriate using the Poisson Regression Model. However the condition that the mean and variance of the Poisson are equal poses a great constraint hence necessitating the use of the Generalized Poisson Regression GPR and the Negative Binomial Regression NBR models which do not require these constraints that the mean and the variance be equal as proxies. Data on Road traffic crashes from the Anambra State Command of the Federal Road Safety Commission FRSC Nigeria were analyzed using these three methods the results from the two proxies are compared using the Akaike Information Criterion AIC with GPR showing an AIC value of 3508.595 and the NBR showing an AIC value of 2742. Having shown a smaller AIC value the NBR was considered a better model when analyzing road traffic crashes in Anambra State Nigeria