A joint econometric framework for modeling crash counts by severity

References

• Abdel-Aty, M., J. Lee, C. Siddiqui, and K. Choi. 2013. “Geographical Unit Based Analysis in the Context of Transportation Safety Planning.” Transportation Research Part A: Policy and Practice 49: 62–75.
   Web of Science ®Google Scholar
• Abdel-Aty, M., C. Siddiqui, H. Huang, and X. Wang. 2011. “Integrating Trip and Roadway Characteristics to Manage Safety in Traffic Analysis Zones.” Transportation Research Record: Journal of the Transportation Research Board 2213 (1): 20–28. doi: 10.3141/2213-04
   Web of Science ®Google Scholar
• Aguero-Valverde, J., and P. P. Jovanis. 2006. “Spatial Analysis of Fatal and Injury Crashes in Pennsylvania.” Accident Analysis & Prevention 38 (3): 618–625. doi: 10.1016/j.aap.2005.12.006
   PubMed Web of Science ®Google Scholar
• Aguero-Valverde, J., and P. Jovanis. 2009. “Bayesian Multivariate Poisson Lognormal Models for Crash Severity Modeling and Site Ranking.” Transportation Research Record: Journal of the Transportation Research Board 2136: 82–91. doi: 10.3141/2136-10
   Web of Science ®Google Scholar
• Aguero-Valverde, J., K.-F. K. Wu, and E. T. Donnell. 2016. “A Multivariate Spatial Crash Frequency Model for Identifying Sites with Promise Based on Crash Types.” Accident Analysis & Prevention 87: 8–16. doi: 10.1016/j.aap.2015.11.006
   PubMed Web of Science ®Google Scholar
• Anastasopoulos, P. C. 2016. “Random Parameters Multivariate Tobit and Zero-Inflated Count Data Models: Addressing Unobserved and Zero-State Heterogeneity in Accident Injury-Severity Rate and Frequency Analysis.” Analytic Methods in Accident Research 11: 17–32. doi: 10.1016/j.amar.2016.06.001
   Web of Science ®Google Scholar
• Anastasopoulos, P. C., V. N. Shankar, J. E. Haddock, and F. L. Mannering. 2012. “A Multivariate Tobit Analysis of Highway Accident-Injury-Severity Rates.” Accident Analysis & Prevention 45: 110–119. doi: 10.1016/j.aap.2011.11.006
   PubMed Web of Science ®Google Scholar
• Aptech. 2015. “ Aptech Systems Inc.” Accessed 19 September 2015. http://www.aptech.com/.
   Google Scholar
• Barua, S., K. El-Basyouny, and M. T. Islam. 2014. “A Full Bayesian Multivariate Count Data Model of Collision Severity with Spatial Correlation.” Analytic Methods in Accident Research 3-4: 28–43. doi: 10.1016/j.amar.2014.09.001
   Google Scholar
• Barua, S., K. El-Basyouny, and M. T. Islam. 2016. “Multivariate Random Parameters Collision Count Data Models with Spatial Heterogeneity.” Analytic Methods in Accident Research 9: 1–15. doi: 10.1016/j.amar.2015.11.002
   Web of Science ®Google Scholar
• Bhat, C. R. 2001. “Quasi-random maximum Simulated Likelihood Estimation of the Mixed Multinomial Logit Model.” Transportation Research Part B: Methodological 35 (7): 677–693. doi: 10.1016/S0191-2615(00)00014-X
   Web of Science ®Google Scholar
• Brijs, T., D. Karlis, F. Van Den Bossche, and G. Wets. 2007. “A Bayesian Model for Ranking Hazardous Road Sites.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 170 (4): 1001–1017. doi: 10.1111/j.1467-985X.2007.00486.x
   Web of Science ®Google Scholar
• Cai, Q., J. Lee, N. Eluru, and M. Abdel-Aty. 2016. “Macro-level Pedestrian and Bicycle Crash Analysis: Incorporating Spatial Spillover Effects in Dual State Count Models.” Accident Analysis & Prevention 93: 14–22. doi: 10.1016/j.aap.2016.04.018
   PubMed Web of Science ®Google Scholar
• Chamberlain, G. 1980. “Analysis of Covariance with Qualitative Data.” The Review of Economic Studies 47 (1): 225–238. doi: 10.2307/2297110
   Web of Science ®Google Scholar
• Cheng, W., G. S. Gill, R. Dasu, M. Xie, X. Jia, and J. Zhou. 2017. “Comparison of Multivariate Poisson Lognormal Spatial and Temporal Crash Models to Identify Hot Spots of Intersections Based on Crash Types.” Accident Analysis & Prevention 99 (Part A): 330–341. doi: 10.1016/j.aap.2016.11.022
   PubMed Web of Science ®Google Scholar
• Chiou, Y.-C., and C. Fu. 2013. “Modeling Crash Frequency and Severity Using Multinomial-Generalized Poisson Model with Error Components.” Accident Analysis & Prevention 50: 73–82. doi: 10.1016/j.aap.2012.03.030
   PubMed Web of Science ®Google Scholar
• Chiou, Y.-C., and C. Fu. 2015. “Modeling Crash Frequency and Severity with Spatiotemporal Dependence.” Analytic Methods in Accident Research 5-6: 43–58. doi: 10.1016/j.amar.2015.03.002
   Web of Science ®Google Scholar
• Chiou, Y.-C., C. Fu, and H. Chih-Wei. 2014. “Incorporating Spatial Dependence in Simultaneously Modeling Crash Frequency and Severity.” Analytic Methods in Accident Research 2: 1–11. doi: 10.1016/j.amar.2013.12.001
   Google Scholar
• Dong, C., D. B. Clarke, S. S. Nambisan, and B. Huang. 2016. “Analyzing Injury Crashes Using Random-Parameter Bivariate Regression Models.” Transportmetrica A: Transport Science 12 (9): 794–810. doi: 10.1080/23249935.2016.1177134
   Web of Science ®Google Scholar
• Dong, C., D. B. Clarke, X. Yan, A. Khattak, and B. Huang. 2014. “Multivariate Random-Parameters Zero-Inflated Negative Binomial Regression Model: An Application to Estimate Crash Frequencies at Intersections.” Accident Analysis & Prevention 70: 320–329. doi: 10.1016/j.aap.2014.04.018
   PubMed Web of Science ®Google Scholar
• Dong, C., S. S. Nambisan, K. Xie, D. B. Clarke, and X. Yan. 2017. “Analyzing the Effectiveness of Implemented Highway Safety Laws for Traffic Safety Across US States.” Transportmetrica A: Transport Science 13 (2): 91–107. doi: 10.1080/23249935.2016.1212290
   Web of Science ®Google Scholar
• El-Basyouny, K., and T. Sayed. 2009. “Collision Prediction Models Using Multivariate Poisson-Lognormal Regression.” Accident Analysis & Prevention 41 (4): 820–828. doi: 10.1016/j.aap.2009.04.005
   PubMed Web of Science ®Google Scholar
• Eluru, N., and C. R. Bhat. 2007. “A Joint Econometric Analysis of Seat Belt use and Crash-related Injury Severity.” Accident Analysis & Prevention 39 (5): 1037–1049. doi: 10.1016/j.aap.2007.02.001
   PubMed Web of Science ®Google Scholar
• Eluru, N., C. R. Bhat, and D. A. Hensher. 2008. “A Mixed Generalized Ordered Response Model for Examining Pedestrian and Bicyclist Injury Severity Level in Traffic Crashes.” Accident Analysis & Prevention 40 (3): 1033–1054. doi: 10.1016/j.aap.2007.11.010
   PubMed Web of Science ®Google Scholar
• Eluru, N., V. Chakour, M. Chamberlain, and L. F. Miranda-Moreno. 2013. “Modeling Vehicle Operating Speed on Urban Roads in Montreal: A Panel Mixed Ordered Probit Fractional Split Model.” Accident Analysis & Prevention 59: 125–134. doi: 10.1016/j.aap.2013.05.016
   PubMed Web of Science ®Google Scholar
• FDOT and CUTR. 2015. “ Florida Transportation Trends & Conditions, Florida Department of Transportation Office of Policy Planning (FDOT) with support from Center for Urban Transportation Research (CUTR).”
   Google Scholar
• Hadayeghi, A., A. Shalaby, and B. Persaud. 2003. “Macrolevel Accident Prediction Models for Evaluating Safety of Urban Transportation Systems.” Transportation Research Record: Journal of the Transportation Research Board 1840: 87–95. doi: 10.3141/1840-10
   Web of Science ®Google Scholar
• Hadayeghi, A., A. Shalaby, and B. Persaud. 2007. “Safety Prediction Models: Proactive Tool for Safety Evaluation in Urban Transportation Planning Applications.” Transportation Research Record: Journal of the Transportation Research Board 2019: 225–236. doi: 10.3141/2019-27
   Web of Science ®Google Scholar
• Heydari, S., L. Fu, L. F. Miranda-Moreno, and L. Jopseph. 2017. “Using a Flexible Multivariate Latent Class Approach to Model Correlated Outcomes: A Joint Analysis of Pedestrian and Cyclist Injuries.” Analytic Methods in Accident Research 13: 16–27. doi: 10.1016/j.amar.2016.12.002
   Web of Science ®Google Scholar
• Hosseinpour, M., A. S. Yahaya, and A. F. Sadullah. 2014. “Exploring the Effects of Roadway Characteristics on the Frequency and Severity of Head-on Crashes: Case Studies From Malaysian Federal Roads.” Accident Analysis & Prevention 62: 209–222. doi: 10.1016/j.aap.2013.10.001
   PubMed Web of Science ®Google Scholar
• Huang, H., M. Abdel-Aty, and A. Darwiche. 2010. “County-level Crash Risk Analysis in Florida: Bayesian Spatial Modeling.” Transportation Research Record: Journal of the Transportation Research Board 2148: 27–37. doi: 10.3141/2148-04
   Web of Science ®Google Scholar
• Huang, H., B. Song, P. Xu, Q. Zeng, J. Lee, and M. Abdel-Aty. 2016. “Macro and Micro Models for Zonal Crash Prediction with Application in Hot Zones Identification.” Journal of Transport Geography 54: 248–256. doi: 10.1016/j.jtrangeo.2016.06.012
   Web of Science ®Google Scholar
• Huang, H., H. Zhou, J. Wang, F. Chang, and M. Ma. 2017. “A Multivariate Spatial Model of Crash Frequency by Transportation Modes for Urban Intersections.” Analytic Methods in Accident Research 14: 10–21. doi: 10.1016/j.amar.2017.01.001
   Web of Science ®Google Scholar
• Jiang, X., M. Abdel-Aty, J. Hu, and J. Lee. 2016. “Investigating Macro-Level Hotzone Identification and variable Importance Using Big Data: A Random Forest Models Approach.” Neurocomputing 181: 53–63. doi: 10.1016/j.neucom.2015.08.097
   Web of Science ®Google Scholar
• Khondakar, B., T. Sayed, and G. Lovegrove. 2010. “Transferability of Community-based Collision Prediction Models for Use in Road Safety Planning Applications.” Journal of Transportation Engineering 136 (10): 871–880. doi: 10.1061/(ASCE)TE.1943-5436.0000153
   Web of Science ®Google Scholar
• Ladron De Guevara, F., S. Washington, and J. Oh. 2004. “Forecasting Crashes at the Planning Level: Simultaneous Negative Binomial Crash Model Applied in Tucson, Arizona.” Transportation Research Record: Journal of the Transportation Research Board 1897: 191–199. doi: 10.3141/1897-25
   Web of Science ®Google Scholar
• Lee, J., M. Abdel-Aty, and X. Jiang. 2014. “Development of Zone System for Macro-level Traffic Safety Analysis.” Journal of Transport Geography 38: 13–21. doi: 10.1016/j.jtrangeo.2014.04.018
   Web of Science ®Google Scholar
• Lee, J., M. Abdel-Aty, and X. Jiang. 2015. “Multivariate Crash Modeling for Motor Vehicle and Non-motorized Modes at the Macroscopic Level.” Accident Analysis & Prevention 78: 146–154. doi: 10.1016/j.aap.2015.03.003
   PubMed Web of Science ®Google Scholar
• Lee, J., and F. Mannering. 2002. “Impact of Roadside Features on the Frequency and Severity of Run-off-roadway Accidents: An Empirical Analysis.” Accident Analysis & Prevention 34 (2): 149–161. doi: 10.1016/S0001-4575(01)00009-4
   PubMed Web of Science ®Google Scholar
• Lee, J., S. Yasmin, N. Eluru, M. Abdel-Aty, and Q. Cai. 2016. “Macroscopic Analysis of Crash Proportion by Mode: Fractional Split Multinomial Logit Modeling Approach.” Presented in the 95th Annual Meeting of the Transportation Research Board (TRB) of the National Academies, January 10–14, 2016, Washington, DC, USA.
   Google Scholar
• Li, Z., W. Wang, P. Liu, J. M. Bigham, and D. R. Ragland. 2013. “Using Geographically Weighted Poisson Regression for County-level Crash Modeling in California.” Safety Science 58: 89–97. doi: 10.1016/j.ssci.2013.04.005
   Web of Science ®Google Scholar
• Lord, D., and F. Mannering. 2010. “The Statistical Analysis of Crash-Frequency Data: A Review and Assessment of Methodological Alternatives.” Transportation Research Part A: Policy and Practice 44 (5): 291–305.
   Web of Science ®Google Scholar
• Ma, J., and K. Kockelman. 2006. “Bayesian Multivariate Poisson Regression for Models of Injury Count, by Severity.” Transportation Research Record: Journal of the Transportation Research Board 1950: 24–34. doi: 10.3141/1950-04
   Google Scholar
• Ma, J., K. M. Kockelman, and P. Damien. 2008. “A Multivariate Poisson-Lognormal Regression Model for Prediction of Crash Counts by Severity, Using Bayesian Methods.” Accident Analysis & Prevention 40 (3): 964–975. doi: 10.1016/j.aap.2007.11.002
   PubMed Web of Science ®Google Scholar
• Mannering, F. L., and C. R. Bhat. 2014. “Analytic Methods in Accident Research: Methodological Frontier and Future Directions.” Analytic Methods in Accident Research 1: 1–22. doi: 10.1016/j.amar.2013.09.001
   Google Scholar
• Mannering, F. L., V. Shankar, and C. R. Bhat. 2016. “Unobserved Heterogeneity and the Statistical Analysis of Highway Accident Data.” Analytic Methods in Accident Research 11: 1–16. doi: 10.1016/j.amar.2016.04.001
   Web of Science ®Google Scholar
• Milton, J. C., V. N. Shankar, and F. L. Mannering. 2008. “Highway Accident Severities and the Mixed Logit Model: An Exploratory Empirical Analysis.” Accident Analysis & Prevention 40 (1): 260–266. doi: 10.1016/j.aap.2007.06.006
   PubMed Web of Science ®Google Scholar
• Mothafer, G. I., T. Yamamoto, and V. N. Shankar. 2016. “Evaluating Crash Type Covariances and Roadway Geometric Marginal Effects Using the Multivariate Poisson Gamma Mixture Model.” Analytic Methods in Accident Research 9: 16–26. doi: 10.1016/j.amar.2015.11.001
   Web of Science ®Google Scholar
• Naderan, A., and J. Shahi. 2010. “Aggregate Crash Prediction Models: Introducing Crash Generation Concept.” Accident Analysis & Prevention 42 (1): 339–346. doi: 10.1016/j.aap.2009.08.020
   PubMed Web of Science ®Google Scholar
• Nashad, T., S. Yasmin, N. Eluru, J. Lee, and M. A. Abdel-Aty. 2016. “Joint Modeling of Pedestrian and Bicycle Crashes: Copula-based Approach.” Transportation Research Record: Journal of the Transportation Research Board 2601: 119–127. doi: 10.3141/2601-14
   Web of Science ®Google Scholar
• Ng, K.-S., W.-T. Hung, and W.-G. Wong. 2002. “An Algorithm for Assessing the Risk of Traffic Accident.” Journal of Safety Research 33 (3): 387–410. doi: 10.1016/S0022-4375(02)00033-6
   PubMed Web of Science ®Google Scholar
• Noland, R. B., and M. A. Quddus. 2004. “A Spatially Disaggregate Analysis of Road Casualties in England.” Accident Analysis & Prevention 36 (6): 973–984. doi: 10.1016/j.aap.2003.11.001
   PubMed Web of Science ®Google Scholar
• Papke, L. E., and J. M. Wooldridge. 1996. “Econometric Methods for Fractional Response Variables with an Application to 401 (k) Plan Participation Rates.” Journal of Applied Econometrics 11 (6): 619–632. doi: 10.1002/(SICI)1099-1255(199611)11:6<619::AID-JAE418>3.0.CO;2-1
   Web of Science ®Google Scholar
• Papke, L. E., and J. M. Wooldridge. 2008. “Panel Data Methods for Fractional Response Variables with an Application to Test Pass Rates.” Journal of Econometrics 145 (1): 121–133. doi: 10.1016/j.jeconom.2008.05.009
   Web of Science ®Google Scholar
• Park, E., and D. Lord. 2007. “Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity.” Transportation Research Record: Journal of the Transportation Research Board 2019: 1–6. doi: 10.3141/2019-01
   Web of Science ®Google Scholar
• Park, E. S., J. Park, and T. J. Lomax. 2010. “A Fully Bayesian Multivariate Approach to Before–After Safety Evaluation.” Accident Analysis & Prevention 42 (4): 1118–1127. doi: 10.1016/j.aap.2009.12.026
   PubMed Web of Science ®Google Scholar
• Pei, X., S. Wong, and N.-N. Sze. 2011. “A Joint-Probability Approach to Crash Prediction Models.” Accident Analysis & Prevention 43 (3): 1160–1166. doi: 10.1016/j.aap.2010.12.026
   PubMed Web of Science ®Google Scholar
• Rifaat, S., R. Tay, and A. De Barros. 2010. “Effect of Street Pattern on Road Safety: Are Policy Recommendations Sensitive to Aggregations of Crashes by Severity?” Transportation Research Record: Journal of the Transportation Research Board 2147: 58–65. doi: 10.3141/2147-08
   Web of Science ®Google Scholar
• Rifaat, S., R. Tay, A. Perez, and A. D. Barros. 2009. “Effects of Neighborhood Street Patterns on Traffic Collision Frequency.” Journal of Transportation Safety & Security 1 (4): 241–253. doi: 10.1080/19439960903328595
   Google Scholar
• Roshandeh, A. M., B. R. Agbelie, and Y. Lee. 2016. “Statistical Modeling of Total Crash Frequency at Highway Intersections.” Journal of Traffic and Transportation Engineering (English Edition) 3 (2): 166–171. doi: 10.1016/j.jtte.2016.03.003
   Google Scholar
• Serhiyenko, V., S. A. Mamun, J. N. Ivan, and N. Ravishanker. 2016. “Fast Bayesian Inference for Modeling Multivariate Crash Counts.” Analytic Methods in Accident Research 9: 44–53. doi: 10.1016/j.amar.2016.02.002
   Web of Science ®Google Scholar
• Shin, K., and S. P. Washington. 2012. “Empirical Bayes Method in the Study of Traffic Safety via Heterogeneous Negative Multinomial Model.” Transportmetrica 8 (2): 131–147. doi: 10.1080/18128601003680976
   Web of Science ®Google Scholar
• Song, J. J., M. Ghosh, S. Miaou, and B. Mallick. 2006. “Bayesian Multivariate Spatial Models for Roadway Traffic Crash Mapping.” Journal of Multivariate Analysis 97 (1): 246–273. doi: 10.1016/j.jmva.2005.03.007
   Web of Science ®Google Scholar
• Stamatiadis, N., and G. Puccini. 2000. “Socioeconomic Descriptors of Fatal Crash Rates in the Southeast USA.” Injury Control and Safety Promotion 7 (3): 165–173. doi: 10.1076/1566-0974(200009)7:3;1-N;FT165
   Google Scholar
• Tunaru, R. 2002. “Hierarchical Bayesian Models for Multiple Count Data.” Austrian Journal of Statistics 31 (3): 221–229.
   Google Scholar
• U.S. Census Bureau. 2012. 2010 Census of Population and Housing, Population and Housing Unit Counts, CPH-2-11, Florida. Washington, DC: US Government Printing Office.
   Google Scholar
• Wang, K., J. N. Ivan, N. Ravishanker, and E. Jackson. 2017. “Multivariate Poisson Lognormal Modeling of Crashes by Type and Severity on Rural two Lane Highways.” Accident Analysis & Prevention 99 (Part A): 6–19. doi: 10.1016/j.aap.2016.11.006
   PubMed Web of Science ®Google Scholar
• Wang, C., M. A. Quddus, and S. G. Ison. 2011. “Predicting Accident Frequency at Their Severity Levels and Its Application in Site Ranking Using a Two-Stage Mixed Multivariate Model.” Accident Analysis & Prevention 43 (6): 1979–1990. doi: 10.1016/j.aap.2011.05.016
   PubMed Web of Science ®Google Scholar
• Washington, S. P., M. G. Karlaftis, and F. Mannering. 2010. Statistical and Econometric Methods for Transportation Data Analysis. Boca Raton, FL: CRC Press.
   Google Scholar
• Wei, F., and G. Lovegrove. 2013. “An Empirical Tool to Evaluate the Safety of Cyclists: Community Based, Macro-Level Collision Prediction Models Using Negative Binomial Regression.” Accident Analysis and Prevention 61: 129–137. doi: 10.1016/j.aap.2012.05.018
   PubMed Web of Science ®Google Scholar
• Xu, X., S. Wong, and K. Choi. 2014. “A two-Stage Bivariate Logistic-Tobit Model for the Safety Analysis of Signalized Intersections.” Analytic Methods in Accident Research 3-4: 1–10. doi: 10.1016/j.amar.2014.08.001
   Google Scholar
• Yasmin, S., and N. Eluru. 2013. “Evaluating Alternate Discrete Outcome Frameworks for Modeling Crash Injury Severity.” Accident Analysis & Prevention 59 (1): 506–521. doi: 10.1016/j.aap.2013.06.040
   PubMed Web of Science ®Google Scholar
• Yasmin, S., and N. Eluru. 2016. “Latent Segmentation Based Count Models: Analysis of Bicycle Safety in Montreal and Toronto.” Accident Analysis & Prevention 95 (Part A): 157–171. doi: 10.1016/j.aap.2016.07.015
   PubMed Web of Science ®Google Scholar
• Yasmin, S., N. Eluru, J. Lee, and M. A. Abdel-Aty. 2016. “An Ordered Fractional Split Approach for Aggregate Injury Severity Modeling.” Transportation Research Record 2583: 119–126. doi: 10.3141/2583-15
   Google Scholar
• Ye, X., R. M. Pendyala, V. Shankar, and K. C. Konduri. 2013. “A Simultaneous Equations Model of Crash Frequency by Severity Level for Freeway Sections.” Accident Analysis & Prevention 57: 140–149. doi: 10.1016/j.aap.2013.03.025
   PubMed Web of Science ®Google Scholar
• Ye, X., R. M. Pendyala, S. P. Washington, K. Konduri, and J. Oh. 2009. “A Simultaneous Equations Model of Crash Frequency by Collision Type for Rural Intersections.” Safety Science 47 (3): 443–452. doi: 10.1016/j.ssci.2008.06.007
   Web of Science ®Google Scholar
• Zeng, Q., H. Wen, H. Huang, X. Pei, and S. Wong. 2017. “A Multivariate Random-Parameters Tobit Model for Analyzing Highway Crash Rates by Injury Severity.” Accident Analysis & Prevention 99: 184–191. doi: 10.1016/j.aap.2016.11.018
   PubMed Web of Science ®Google Scholar
• Zhan, X., H. M. A. Aziz, and S. V. Ukkusuri. 2015. “An Efficient Parallel Sampling Technique for Multivariate Poisson-Lognormal Model: Analysis with Two Crash Count Datasets.” Analytic Methods in Accident Research 8: 45–60. doi: 10.1016/j.amar.2015.10.002
   Web of Science ®Google Scholar