A full Bayes multivariate intervention model with random parameters among matched pairs for before-after safety evaluation

Accident Analysis and Prevention

Volumn 43, Issue 1, 2011, Pages 87-94

  El Basyouny, Karim ^a   Sayed, Tarek ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Controlled before after studies; Full Bayes; Multivariate intervention model; Odds ratio; Poisson lognormal hierarchy; Random parameters

Indexed keywords

BEFORE-AFTER STUDY; FULL BAYES; LOG-NORMAL; MULTIVARIATE INTERVENTION MODEL; ODDS RATIOS; RANDOM PARAMETERS;

BEHAVIORAL RESEARCH; ROADS AND STREETS;

POISSON RATIO;

ARTICLE; BAYES THEOREM; CANADA; CLASSIFICATION; COMPARATIVE STUDY; ENVIRONMENTAL PLANNING; HUMAN; INJURY; INJURY SCALE; MORTALITY; MULTIVARIATE ANALYSIS; POISSON DISTRIBUTION; RISK; RISK FACTOR; SAFETY; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS; SURVIVAL; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; BAYES THEOREM; BRITISH COLUMBIA; ENVIRONMENT DESIGN; HUMANS; INJURY SEVERITY SCORE; MATCHED-PAIR ANALYSIS; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; ODDS RATIO; POISSON DISTRIBUTION; RISK FACTORS; SAFETY MANAGEMENT; SURVIVAL ANALYSIS; WOUNDS AND INJURIES;

EID: 78650020622     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2010.07.015     Document Type: Article

References (34)

1. A. Aeron-Thomas, and S. Hess Red-light cameras for the prevention of road traffic crashes Cochrane Database of Systematic Reviews 2 2005 Art. No.: CD003862. doi:10.1002/14651858.CD003862.pub2
2. J. Aguero-Valverde, and P.P. Jovanis Bayesian multivariate Poisson log-normal models for crash severity modeling and site ranking Transportation Research Record 2136 2009 82 91
3. P.Ch. Anastasopoulos, and F. Mannering A note on modeling vehicle accident frequencies with random-parameters count models Accident Analysis and Prevention 41 1 2009 153 159
4. N. Aul, and G. Davis Use of propensity score matching method and hybrid Bayesian method to estimate crash modification factors of signal installation Transportation Research Record 1950 2006 17 23
5. E.J. Bedrick, R. Christensen, and W. Johnson A new perspective on priors for generalized linear models Journal of the American Statistical Association 91 1996 1450 1460
6. A. Carriquiry, and M.D. Pawlovich From Empirical Bayes to Full Bayes: Methods for Analyzing Traffic Safety Data 2005 http://www.dot.state.ia.us/ crashanalysis/pdfs/eb-fb-comparison-whitepaper-october2004.pdf
7. P. Congdon Applied Bayesian Modeling 2nd ed. 2006 John Wiley & Sons New York
8. Dang, J., 2007. Statistical Analysis of the Effectiveness of Electronic Stability Control (ESC) Systems. Report No. DOT HS 810 794, National Highway Traffic Safety Administration, Washington, D.C.
9. K. El-Basyouny, and T. Sayed Collision prediction models using multivariate Poisson-lognormal regression Analysis and Prevention 41 4 2009 820 828
10. K. El-Basyouny, and T. Sayed Accident prediction models with random corridor parameters Accidents Analysis and Prevention 41 5 2009 1118 1123
11. K. El-Basyouny, and T. Sayed A full Bayes approach to before-after safety evaluation with matched comparisons: a case study of stop-sign in-fill program Presented at the 89th Annual Meeting of the Transportation Research Board Washington, D.C. 2010
12. A. Gelman, X. Meng, and H. Stern Posterior predictive assessment of model fitness via realized discrepancies Statistica Sinica 6 1996 733 807 (Pubitemid 126706389)
13. E. Hauer Observational Before-After Studies in Road Safety: Estimating the Effect of Highway and Traffic Engineering Measures on Road Safety 1997 Elsevier Science Ltd
14. Klauer, S.G., Dingus, T.A., Neale, V.L., Sudweeks, J.D., Ramsey, D.J., 2006. The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis Using the 100-Car. Report No. DOT HS 810 594, National Highway Traffic Safety Administration, Washington, D.C.
15. B. Lan, B. Persaud, C. Lyon, and R. Bhim Validation of a full Bayes methodology for observational before-after road safety studies and application to evaluation of rural signal conversions Analysis and Prevention 41 3 2009 574 580
16. W. Li, A. Carriquiry, M. Pawlovich, and T. Welch The choice of statistical models in road safety countermeasures effectiveness studies in Iowa Accident Analysis and Prevention 40 4 2008 1531 1542
17. D.J. Lunn, A. Thomas, N. Best, and D. Spiegelhalter WinBUGS - a Bayesian modelling framework: concepts, structure, and extensibility Statistics and Computing 10 2000 325 337
18. J. Ma, K.M. Kockelman, and P. Damien A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods Accident Analysis and Prevention 40 2008 964 975
19. S. Miaou, and J. Song Bayesian ranking of sites for engineering safety improvements: decision parameter, treatability concept, statistical criterion, and spatial dependence Accident Analysis and Prevention 37 4 2005 699 720
20. J. Milton, V. Shankar, and F. Mannering Highway accident severities and the mixed logit model: an exploratory empirical analysis Accident Analysis and Prevention 40 1 2008 260 266
21. E.S. Park, and D. Lord Multivariate Poisson-lognormal models for jointly modeling crash frequency by severity Transportation Research Record 2019 2007 1 6
22. E.S. Park, J. Park, and T.J. Lomax A fully Bayesian multivariate approach to before-after safety evaluation Presented at the 89th Annual Meeting of the Transportation Research Board Washington, D.C. 2009
23. M.D. Pawlovich, W. Li, A. Carriquiry, and T. Welch Iowa's experience with road diet measures: use of Bayesian approach to assess impacts on crash frequencies and crash rates Transportation Research Record 1953 2006 163 171
24. B. Persaud, and C. Lyon Empirical Bayes before-after safety studies: lessons learned from two decades of experience and future directions Accident Analysis and Prevention 39 3 2007 546 555
25. B. Persaud, B. Lan, C. Lyon, and R. Bhim Comparison of empirical Bayes and full Bayes approaches for before-after road safety evaluations Presented at the 89th Annual Meeting of the Transportation Research Board Washington, D.C. 2009
26. A.E. Raftery, and V.E. Akman Bayesian analysis of a Poisson process with a change-point Biometrika 73 1 1986 85 89
27. T. Sayed, P. deLeur, and Z. Sawalha Evaluating the Insurance Corporation of British Columbia Road Safety Improvement Program Transportation Research Record 1865 2004 57 63
28. P.J. Schluter, J.J. Deely, and A.J. Nicholson Ranking and selecting motor vehicle accident sites by using a hierarchical Bayesian model Statistician 46 3 1997 293 316
29. D.J. Spiegelhalter, A. Thomas, and N.G. Best Computation on bayesian graphical models J.M. Bernardo, J.O. Berger, A.P. Dawid, A.F.M. Smith, Bayesian statistics 5 1996 Oxford University Press Oxford 407 425
30. D. Spiegelhalter, A. Thomas, N. Best, and D. Lunn WinBUGS User Manual 2005 MRC Biostatistics Unit Cambridge Available from http://www.mrc-cam.ac.uk/ bugs
31. D.J. Spiegelhalter, N.G. Best, B.P. Carlin, and A. Van der Linde Bayesian measures of model complexity and fit Journal of the Royal Statistical Society B 64 2002 1 34
32. H.S. Stern, and N. Cressie Posterior predictive model checks for disease mapping models Statistics in Medicine 19 2000 2377 2397
33. R. Tunaru Hierarchical Bayesian models for multiple count data Austrian Journal of Statistics 31 3 2002 221 229
34. C. Wilson, C. Willis, J.K. Hendrikz, and N. Bellamy Speed enforcement detection devices for preventing road traffic injuries Cochrane Database of Systematic Reviews 2 2006 Art. No.: CD004607. doi:10.1002/14651858.CD004607.pub2