From: Analysis of injuries and deaths from road traffic accidents in Iran: bivariate regression approach
Model type | Year | Conclusion |
---|---|---|
A joint model with Weighted risk score to combine crash count and crash severity [29] | 2020 | using of crash severity and crash count amended the accuracy of prediction model |
A bivariate Bayesian hierarchical extreme value model for traffic conflict-based crash estimation [30] | 2020 | The bivariate model estimate regression coefficients more precisely than univariate models |
Bayesian multivariate hierarchical spatial joint model [31] | 2018 | This model has a better fit for the crash data compared to the univariate alternative model |
Copula-Based Joint Model of Injury Severity and Vehicle Damage in Two-Vehicle Crashes [32] | 2015 | On the basis of goodness-of-fit statistics, the Gaussian copula model that was calculated interrelationships between injury severity and vehicle damage was suitable |
using the random-parameters tobit model for factors affecting highway accident rates [33] | 2012 | The empirical results show that this model was proper fit to the data |
A joint-probability approach to crash prediction models [34] | 2011 | Joint probability model that modeled Crash occurrence and severity simultaneously, shown the good fit for data |
Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity [35] | 2007 | The results show multivariate model that accounted correlation of variables, was achieved more accurate estimates |