Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has
been an area of research focus for many decades. However, in the absence of detailed …

BACKGROUND: Traditional crash prediction models, such as generalized linear regression
model, are incapable of taking into account multilevel data structure. Therefore they suffer …

Factors that cause heterogeneity in crash data are often unknown to researchers and failure
to accommodate such heterogeneity in statistical models can undermine the validity of …

This paper develops a step-by-step methodology for the application of Full Bayes (FB)
approach for before-and-after analysis of road safety countermeasures. As part of this …

Few behavioral interventions have been conducted to reduce high-risk sexual behavior
among HIV-positive Men who have Sex with Men (HIV+ MSM). Hence, we lack well-proven …

The report presents an analysis of the current use of ten different formal tools for the safety
management of roads in seventeen European countries. The relationship between use of …

Large speed differentials between highway segments are associated with an increase in the
number of accidents. Traditional speed differential measures, derived from single-level …

Animal-vehicle collisions (AVCs) have been increasing with increases in both animal
populations and motor vehicle miles of travel and have become a major safety concern …

Statistical models have frequently been used in highway safety studies. They can be utilized
for various purposes, including establishing relationships between variables. Generalized …

Many models and statistical techniques have been proposed in transportation literature to
model crash count data. Although there has been some effort to compare and evaluate …