메뉴 건너뛰기




Volumn , Issue 2165, 2010, Pages 21-32

Spatial correlation in multilevel crash frequency models: Effects of different neighboring structures

Author keywords

[No Author keywords available]

Indexed keywords

HIGHWAY ACCIDENTS; HIGHWAY ENGINEERING; MOTOR TRANSPORTATION; SAMPLING;

EID: 78651325886     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/2165-03     Document Type: Article
Times cited : (74)

References (29)
  • 2
  • 3
    • 33749051863 scopus 로고    scopus 로고
    • Temporal and spatial analysis of rear-end crashes at signalized intersections
    • Wang, X., and M. Abdel-Aty. Temporal and Spatial Analysis of Rear-End Crashes at Signalized Intersections. Accident Analysis and Prevention. Vol. 38, No. 6, 2006, pp. 1137-1150.
    • (2006) Accident Analysis and Prevention , vol.38 , Issue.6 , pp. 1137-1150
    • Wang, X.1    Abdel-Aty, M.2
  • 7
    • 4344608946 scopus 로고    scopus 로고
    • Bayesian spatial and ecological models for small-area accident and injury analysis
    • MacNab, Y. C. Bayesian Spatial and Ecological Models for Small-Area Accident and Injury Analysis, Accident Analysis and Prevention, Vol. 36, 2004, pp. 1019-1028.
    • (2004) Accident Analysis and Prevention , vol.36 , pp. 1019-1028
    • MacNab, Y.C.1
  • 8
    • 33644906631 scopus 로고    scopus 로고
    • Spatial analysis of fatal and injury crashes in pennsylvania
    • Aguero-Valverde, J., and P. Jovanis. Spatial Analysis of Fatal and Injury Crashes in Pennsylvania. Accident Analysis and Prevention. Vol. 38, No. 3, 2006, pp. 618-625.
    • (2006) Accident Analysis and Prevention , vol.38 , Issue.3 , pp. 618-625
    • Aguero-Valverde, J.1    Jovanis, P.2
  • 10
    • 4243702887 scopus 로고    scopus 로고
    • The use of multilevel models for the prediction of road accident outcomes
    • Jones, A. P., and S. H. Jørgensen. The Use of Multilevel Models for the Prediction of Road Accident Outcomes. Accident Analysis and Prevention. Vol. 35, No. 1, 2003, pp. 59-69.
    • (2003) Accident Analysis and Prevention , vol.35 , Issue.1 , pp. 59-69
    • Jones, A.P.1    Jørgensen, S.H.2
  • 11
    • 27644496387 scopus 로고    scopus 로고
    • Modelling the hierarchical structure of road crash data-application to severity analysis
    • Lenguerrand, E., J. L. Martin, and B. Laumon. Modelling the Hierarchical Structure of Road Crash Data-Application to Severity Analysis. Accident Analysis and Prevention. Vol. 38, No. 1, 2006, pp. 43-53.
    • (2006) Accident Analysis and Prevention , vol.38 , Issue.1 , pp. 43-53
    • Lenguerrand, E.1    Martin, J.L.2    Laumon, B.3
  • 12
    • 33750288910 scopus 로고    scopus 로고
    • Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models
    • Kim, D.-G., Y. Lee, S. Washington, and K. Choi. Modeling Crash Outcome Probabilities at Rural Intersections: Application of Hierarchical Binomial Logistic Models. Accident Analysis and Prevention. Vol. 39, 2007, pp. 125-134.
    • (2007) Accident Analysis and Prevention , vol.39 , pp. 125-134
    • Kim, D.-G.1    Lee, Y.2    Washington, S.3    Choi, K.4
  • 13
    • 34247476647 scopus 로고    scopus 로고
    • Multilevel modeling for the regional effect of enforcement on road accidents
    • Yannis, G., E. Papadimitriou, and C. Antoniou. Multilevel Modeling for the Regional Effect of Enforcement on Road Accidents. Accident Analysis and Prevention. Vol. 39, 2007, pp. 818-825.
    • (2007) Accident Analysis and Prevention , vol.39 , pp. 818-825
    • Yannis, G.1    Papadimitriou, E.2    Antoniou, C.3
  • 14
    • 43949127408 scopus 로고    scopus 로고
    • Impact of enforcement on traffic accidents and fatalities: A multivariate multilevel analysis
    • Yannis, G., E. Papadimitriou, and C. Antoniou. Impact of Enforcement on Traffic Accidents and Fatalities: A Multivariate Multilevel Analysis. Safety Science. Vol. 46, 2008, pp. 738-750.
    • (2008) Safety Science , vol.46 , pp. 738-750
    • Yannis, G.1    Papadimitriou, E.2    Antoniou, C.3
  • 15
    • 0028835190 scopus 로고
    • Bayesian estimates of disease maps: How important are priors?
    • Bernardinelli, L., D. Clayton, and C. Montomoli. Bayesian Estimates of Disease Maps: How Important Are Priors? Statistics in Medicine, Vol. 14, 1995, pp. 2411-2431.
    • (1995) Statistics in Medicine , vol.14 , pp. 2411-2431
    • Bernardinelli, L.1    Clayton, D.2    Montomoli, C.3
  • 19
    • 56749102809 scopus 로고    scopus 로고
    • Identifying road segments with high risk of weather-related crashes using full bayesian hierarchical models
    • Washington, D.C.
    • Aguero-Valverde, J., and P. P. Jovanis. Identifying Road Segments with High Risk of Weather-Related Crashes Using Full Bayesian Hierarchical Models. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, D.C., 2007.
    • (2007) 86th Annual Meeting of the Transportation Research Board
    • Aguero-Valverde, J.1    Jovanis, P.P.2
  • 25
    • 78651306241 scopus 로고    scopus 로고
    • Pennsylvania State University, Accessed May 2007
    • Pennsylvania Spatial Data Access. Pennsylvania State University. http://www.pasda.psu.edu/. Accessed May 2007.
    • Pennsylvania Spatial Data Access
  • 26
    • 79958252453 scopus 로고    scopus 로고
    • FHWA U.S. Department of Transportation. Accessed May 2007
    • Highway Safety Information System. FHWA, U.S. Department of Transportation. http://www.hsisinfo.org/. Accessed May 2007.
    • Highway Safety Information System
  • 27
    • 78651288824 scopus 로고    scopus 로고
    • Washington State Department of Transportation, Accessed May 2007
    • WSDOT GeoData Distribution Catalog. Washington State Department of Transportation. http://www.wsdot.wa.gov/mapsdata/geodatacatalog/. Accessed May 2007.
    • WSDOT GeoData Distribution Catalog


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.