No abstract

No abstract

In the presence of multicollinearity in logistic regression, the variance of the Maximum Likelihood Estimator (MLE) becomes inflated. Şiray et al.

Traffic accidents have become a very serious public health problem around the world. It was identified as one of the leading causes of the death and injury in Sri Lanka. Each year over 40,887 road accidents occur in Sri Lanka, causing on average six fatalities every day, several hundred are left seriously injured, and some with lifelong consequences. Jaffna district is the northernmost region of the Island of Sri Lanka and it is now experiencing rapid economic growth after the civil war. This leads to a huge increase in motorization rate associated with rapidly expanding road construction. As a result, in recent years, the rate of occurrence of traffic accidents in Jaffna is increasing drastically. This motivated us to study the factors influencing the severity of the accidents in Jaffna. In this study, based on Jaffna police records, 692 accident cases were considered during the period 2010-2013. The variable "Accident severity" (Fatal/Non-fatal) is considered as a dichotomous response variable, and the factors Time, Location, Type of vehicle, Gender, License status, Cause of accident, and Type of accident are treated as influencing factors on the accident severity. The main focus of this study is to identify the most influential factors involved in accident severity. Because of the binary nature of the response variable, we have used logistic regression approach for the analysis. After a series of statistical analyses were conducted, independent variables "Type of vehicle" and "Age" were identified as more influential variables influencing the accident severity. Results from this study reveal that the fitted logistic regression model can be used for the safety improvements against the traffic accidents in Jaffna.