This study aims to evaluate the impact of pavement physical characteristics on the frequency of single-vehicle run-off-road (ROR) crashes in two-lane separated rural highways. In order to achieve this goal and to introduce the most accurate crash prediction model (CPM), authors have tried to develop generalized linear models, including the Poisson regression (PR), negative binomial regression (...

A number of methods have been proposed for dealing with extra-Poisson variation when doing regression analysis of count data. This paper studies negative-binomial regression models and examines efficiency and robustness properties of inference procedures based on them. The methods are compared with quasilikelihood methods. RESUME Plusieurs mkthodes ont ktk propokes en vue de traiter le probltme...

In this paper, a new bivariate negative binomial regression (BNBR) model allowing any type of correlation is defined and studied. The marginal means of the bivariate model are functions of the explanatory variables. The parameters of the bivariate regression model are estimated by using the maximum likelihood method. Some test statistics including goodness-of-fit are discussed. Two numerical da...

In regression analysis of counts, a lack of simple and efficient algorithms for posterior computation has made Bayesian approaches appear unattractive and thus underdeveloped. We propose a lognormal and gamma mixed negative binomial (NB) regression model for counts, and present efficient closed-form Bayesian inference; unlike conventional Poisson models, the proposed approach has two free param...

The Poisson-Gamma model has properties that are very similar to the Poisson model discussed in Appendix C, in which the dependent variable i y is modeled as a Poisson variable with a mean i  where the model error is assumed to follow a Gamma distribution. As it names implies, the Poisson-Gamma is a mixture of two distributions and was first derived by Greenwood and Yule (1920). This mixture di...