In crash frequency studies, correlated multivariate data are often obtained for each roadway entity longitudinally. The multivariate models would be a potential useful method for analysis, since they can account for the correlation among the specific crash types. However, one issue that arises with this correlated multivariate data is the number of zero counts increases as crash counts have man...

In recent years, there has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a ...

Poisson regression has been widely used to model count data. However, it is often criticized for its restrictive assumption of equi-dispersion, meaning equality between the variance and the mean. In real-life applications, count data often exhibits over-dispersion and excess zeroes. While Negative binomial regression is able to model count data with over-dispersion, both Hurdle (Mullahy, 1986) ...

The purpose of this study was to explore factors that facilitate or hinder effective use of computers in Australian general medical practice. This study is based on data extracted from a national telephone survey of 480 general practitioners (GPs) across Australia. Clinical functions performed by GPs using computers were examined using a zero-inflated Poisson (ZIP) regression modelling. About 1...

BACKGROUND The number of failed courses and semesters in students are indicators of their performance. These amounts have zero inflated (ZI) distributions. Using ZI Poisson and negative binomial distributions we can model these count data to find the associated factors and estimate the parameters. This study aims at to investigate the important factors related to the educational performance of ...

In this paper we address the problem of building user models that can predict the rate at which individuals consume items from a finite set, including items they have consumed in the past and items that are new. This combination of repeat and new item consumption is common in applications such as listening to music, visiting web sites, and purchasing products. We use zero-inflated Poisson (ZIP)...