A note on modeling vehicle accident frequencies with random-parameters count models

The influence of economic incentives linked to road safety indicators on accidents: The case of toll concessions in Spain

“…The longer the length of the road section, the more likely accidents, injuries and fatalities will occur on theses sections. These results confirm the hypothesis proposed by Mohamed et al (2000), Persaud et al (2000) and Anastasopoulos and Mannering (2009).…”

“…Results show that accident rate decrease with increasing traffic flow (Martin, 2002;Hauer and Bamfo, 1997); and accident frequency increases with traffic flow (Mohamed et al, 2000;Persaud et al, 2000;Anastasopoulos and Mannering, 2009). …”

Bias properties of Bayesian statistics in finite mixture of negative binomial regression models in crash data analysis

“…Over-dispersion caused by unobserved heterogeneity in crash data is a serious problem and has been addressed in a variety of ways within the negative binomial (NB) modeling framework (Hauer, 2001;Heydecker and Wu, 2001;Miaou and Lord, 2003;Geedipally et al, 2009;Anastasopoulos and Mannering, 2009). However, the true factors that affect heterogeneity are often unknown to researchers and failure to accommodate such heterogeneity in the model can undermine the validity of the empirical results.…”

“…Washington et al (2003) noted that it could lead to inconsistent and biased parameter estimates when the coefficients actually vary across observations. In this context, Anastasopoulos and Mannering (2009) recently applied random-parameter count models to vehicle crash data by employing a normal error term in the coefficients to allow them to vary. The finite mixture regression model is different from the random-parameter models in that the parameter heterogeneity is approximated by a finite number of support points and their probability masses without making a distributional assumption on the regression coefficients or mixing variable.…”

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

“…If some parameters do vary across observations and the model is estimated as if they were fixed, the resulting parameter estimates will be biased and possible erroneous inferences could be drawn. Estimation techniques do exist for allowing parameters to vary across observations, but the model estimation process becomes considerably more complex (Anastasopoulos and Mannering, 2009;ElBasyouny and Sayed, 2009b;Washington et al, 2010). sense because multiplying traffic flow and segment length gives a traditional exposure measure (vehicle-miles traveled).…”