Severity of driver injury and vehicle damage in traffic crashes at intersections: a Bayesian hierarchical analysis.

By Helai Huang, H. Chin, M. Haque. Accident Analysis and Prevention, 2008

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Investigation of factors influencing motorcyclist injury severity using random parameters logit model with heterogeneity in means and variances (2021, methodology): “Some of the methods that have been used for, include a binary logit model [7], binary probit model [8] ordered logit model [9], ordered probit model [10], bivariate probit model [11], multinomial logit model [12], random parameter logit model [13], artificial neural network [14], Bayesian [15,16] an”
Multivariate random parameters zero-inflated negative binomial regression for analyzing urban midblock crashes (2018, background): “When these crashes are jointly analyzed, multivariate count data models are necessary, as univariate models may produce biased and inefficient results because the unobserved heterogeneity often present across crash types is ignored (Huang et al., 2008; Dong et al., 2014a; Mannering et al., 2016).”
Joint Analysis of Injury Severity of Drivers in Two-Vehicle Crashes Accommodating Seat Belt Use Endogeneity (2013, background): “In recent years, unordered-response specifications have also been considered (see, for example, Rifaat et al., 2011, Yan et al., 2011, Malyshkina and Mannering, 2009, Huang et al., 2008, Milton et al., 2008, Kim et al., 2010, and Moore et al., 2011).”