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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2021. Understanding and Communicating Reliability of Crash Prediction Models. Washington, DC: The National Academies Press. doi: 10.17226/26440.
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Page101
Page 102
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2021. Understanding and Communicating Reliability of Crash Prediction Models. Washington, DC: The National Academies Press. doi: 10.17226/26440.
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Page102

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99 References AASHTO (2010), Highway Safety Manual, Washington, D.C. Bahar, G., and E. Hauer (2014), User’s Guide to Develop Highway Safety Manual Safety Performance Function Calibration Factors, NCHRP Project 20-07/Task 332 Final Report, Transportation Research Board, Washington, D.C. Bonneson, J., S. Geedipally, M. Pratt, and D. Lord (2012), Safety Prediction Methodology and Analysis Tool for Freeways and Interchanges, NCHRP Project 17-45 Final Report, Transportation Research Board, Washington, D.C. Burnham, K.P., and Anderson, D.R. (2004), Multimodel Inference: Understanding AIC and BIC in Model Selection, Sociological Methods and Research, Vol. 33, pp. 261-304. Carter, D., R. Srinivasan, F. Gross, S. Himes, T. Le, B. Persaud, C. Lyon, and J. Bonneson (2017), Guidance for the Development and Application of Crash Modification Factors, NCHRP Project 17-63 Final Report, Transportation Research Board, Washington, D.C. (forthcoming). Connors, R.D., Maher, M., Wood, A., Mountain, L., and Ropkins, K. (2013), Methodology for Fitting and Updating Predictive Accident Models with Trend, Accident Analysis and Prevention, Vol. 56, pp. 82-94.. Ferguson, E., J. Bonneson, L. Rodegertdts, N. Foster, B. Persaud, C. Lyon, and D. Rhoades (2018), NCHRP Research Report 888: Development of Roundabout Crash Prediction Models and Methods, Transportation Research Board, Washington, D.C. Fridstrom, L., Ifver, J., Ingebrigtsen, S., Kulmala, R., and Thomsen, L. K. (1995), Measuring the Contribution of Randomness, Exposure, Weather, and Daylight to the Variation in Road Accident Counts. Accident Analysis and Prevention, Vol. 27, pp. 1-20. Hauer, E. (1997), Observational Before-After Studies in Road Safety: Estimating the Effect of Highway and Traffic Engineering Measures on Road Safety, Elsevier Science, Tarrytown, NY. Hauer, E., and Bamfo, J. (1997), Two Tools for Finding What Function Links the Dependent Variable to the Explanatory Variables, Proceedings ICTCT (International Cooperation on Theories and Concepts in Traffic Safety), Lund, Sweden. Hauer, E., J.A. Bonneson, F.M. Council, R. Srinivasan, and C. Zegeer (2012), Crash Modification Factors: Foundational Issues, Transportation Research Record: Journal of the Transportation Research Board, No. 2279, pp. 67–74. Hauer, E. (2015). The Art of Regression Modeling in Road Safety. Springer International Publishing, Switzerland. iTRANS (2006), Task 8A: Develop Decision Rule – AMF Acceptance Criteria, Working paper from NCHRP Project 17-27, Parts I and II of the Highway Safety Manual, iTrans Consulting Ltd.

100 Ivan, J. N., S. Al Mamun, N. Ravishanker, B. Persaud, C. Lyon, R. Srinivasan, B. Lan, S. Smith, T. Saleem, M. Abdel-Aty, J. Lee, A. Farid, and J.-H. Wang (2021), NCHRP Web-Only Document 295: Improved Prediction Models for Crash Types and Crash Severities. Transportation Research Board, Washington, D.C. Liu, W., and Cela, J. (2008), Count Data Models in SAS, SAS Global Forum 2008: Statistics and Data Analysis (Paper 371-2008). Lord, D. (2008), Methodology for Estimating the Variance and Confidence Intervals for the Estimate of the Product of Baseline Models and AMFs, Accident Analysis and Prevention, Vol. 40, pp. 1013-1017. Lyon, C., Persaud, B., and Gross, F. (2016), The Calibrator: An SPF Calibration and Assessment Tool: User Guide, Federal Highway Administration, Report FHWA-SA-17-016, Washington, D.C. Miaou, S.P. (1996), Measuring the Goodness-of-Fit of Accident Prediction Models, Federal Highway Administration, FHWA-RD-96-040, Oak Ridge, TN: Oak Ridge National Laboratory. Srinivasan, R., G. Ullman, M. Finley, and F. Council (2011), Use of Empirical Bayesian Methods to Estimate Crash Modification Factors for Daytime Versus Nighttime Work Zones, Transportation Research Record: Journal of the Transportation Research Board, No. 2241, pp. 29–38. Srinivasan, R., and K. Bauer (2013). Safety Performance Function Development Guide: Developing Jurisdiction-Specific SPFs, Report FHWA-SA-14-005, Federal Highway Administration, Washington, D.C., September 2013. Srinivasan, R., M. Colety, G. Bahar, B. Crowther, M. Farmen (2016), Estimation of Calibration Functions for Predicting Crashes on Rural Two-Lane Roads in Arizona, Transportation Research Record: Journal of the Transportation Research Board, No. 2583, pp. 17–24. Wood, G.R. (2002), Generalized Linear Accident Models and Goodness of Fit Testing, Accident Analysis and Prevention, Vol. 34, pp. 417-427. Wood, A.G., L.J. Mountain, R.D. Connors, M.J. Maher, and K. Ropkins (2013), Updating Outdated Predictive Accident Models, Accident Analysis and Prevention, 55, pp. 54-66.

Next: Appendix A: The Development of Procedures for Quantifying the Reliability of Crash Prediction Model Estimates with a Focus on Mismatch Between CMFs and SPF Base Conditions »
Understanding and Communicating Reliability of Crash Prediction Models Get This Book
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Understanding and communicating consistently reliable crash prediction results are critical to credible analysis and to overcome barriers for some transportation agencies or professionals utilizing these models.

The TRB National Cooperative Highway Research Program's NCHRP Web-Only Document 303: Understanding and Communicating Reliability of Crash Prediction Models provides guidance on being able to assess and understand the reliability of Crash Prediction Models.

This document is supplemental to NCHRP Research Report 983: Reliability of Crash Prediction Models: A Guide for Quantifying and Improving the Reliability of Model Results.

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