Relatively recent research has illustrated the potential that tobit regression has in studying
factors that affect vehicle accident rates (accidents per distance traveled) on specific …

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 …

In this study, a multivariate random-parameters Tobit model is proposed for the analysis of
crash rates by injury severity. In the model, both correlation across injury severity and …

Over the last few decades, interstate speed limits in different US states have been increased
from 70 mi/h to 75 mi/h or 80 mi/h, even to 85 mi/h in some instances. The implication of …

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 …

This study develops three temporal multivariate random parameters Tobit models to analyze
crash rate by injury severity; these models simultaneously accommodate temporal …

Numerous studies have previously used a variety of count-data models to investigate factors
that affect the number of crashes over a certain period of time on roadway segments. Unlike …

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 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 …

This study develops a Bayesian spatial random parameters Tobit model to analyze crash
rates on road segments, in which both spatial correlation between adjacent sites and …