In recent years, complex statistical modeling approaches have being proposed to handle the
unobserved heterogeneity and the excess of zeros frequently found in crash data, including …

This study investigated the effects of including spatial heterogeneity in multivariate random
parameters models and their influence on different collision severity levels. The models …

A large body of previous literature has used a variety of count-data modeling techniques to
study factors that affect the frequency of highway accidents over some time period on …

Random parameters logit models have become an increasingly popular method to
investigate crash-injury severities in recent years. However, there remain potential elements …

This study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly
models crash frequency and severity accounting for correlations. The ordinary univariate …

This study investigates the inclusion of spatio-temporal correlation and interaction in a
multivariate random-parameters Tobit model and their influence on fitting areal crash rates …

Random effects tobit models are developed in predicting hourly crash rates with refined-
scale panel data structure in both temporal and spatial domains. The proposed models …

This paper presents an empirical inquiry into the applicability of zero-altered counting
processes to roadway section accident frequencies. The intent of such a counting process is …

In safety literature, simulation-based multivariate framework is the most commonly employed
approach for analyzing multiple crash frequency dependent variables. The current research …

Zero-inflated count models are increasingly employed in many fields in case of “zero-
inflation”. In modeling road traffic crashes, it has also shown to be useful in obtaining a better …