01552341

Component

In order to analyze crash data, many new analysis tools are being developed by transportation safety analysts. The Negative Binomial-Generalized Exponential distribution (NB-GE) is such a tool that was recently introduced to handle datasets characterized by a large number of zero counts and are over-dispersed. As the name suggests, this three-parameter distribution is a combination of both Negative binomial and Generalized Exponential distributions. So far, nobody has used this distribution in the context of a regression model for analyzing datasets with excess zeros. This paper therefore describes the application of the NB-GE generalized linear model (GLM). The distribution and GLM were applied to four datasets known to have large dispersion and/or a large number of zeros. The NB-GE was compared to the Poisson, NB as well as the Negative Binomial- Lindley (NB-L) model, another three-parameter recently introduced in the safety literature. The study results show that for datasets characterized by a sizable over-dispersion and contain a large number of zeros, the NB-GE performs as well as the NB-L, but significantly outclass the traditional NB model. Furthermore, the NB-GE model has a simpler modeling framework than the NB-L, which makes its application relatively straight forward.

This paper was sponsored by TRB committee ABJ80 Statistical Methods.

01550057

15-3383

English

14p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References (20) ; Tables

Crash data; Data analysis; Mathematical models; Safety audits; Transportation safety

Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics

Transportation Research Board Annual Meeting 2015 Paper #15-3383

TRIS, TRB, ATRI

Dec 30 2014 1:08PM