Crash Frequency Modeling using Negative Binomial Models: An Application of Generalized Estimating Equation to Longitudinal Data

By M. Mohammadi, V. A. Samaranayake, G. Bham. 2014

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Random parameters multivariate tobit and zero-inflated count data models: addressing unobserved and zero-state heterogeneity in accident injury-severity rate and frequency analysis (2016, background): “67 In fact, numerous studies (Abdel-Aty and Radwan, 2000; Anastasopoulos et al., 2008; Geedipally and Lord, 68 2010; Mohammadi et al., 2014; Zou et al., 2014; Barua et al., 2015; for a detailed list, see Lord and 69 Mannering, 2010) have presented a great amount of roadway segments of varying…”
A Novel Hybrid Method for Measuring the Spatial Autocorrelation of Vehicular Crashes: Combining Moran’s Index and Getis-Ord G i * Statistic (2017, background): “Therefore, the consideration of spatial autocorrelations has been gaining attention in crash data modeling in recent years, and researchers have shown that ignoring this factor may lead to a biased estimation of the model parameters [3]-[12].”