These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

250 related items for PubMed ID: 15752487

  • 1. Identifying crash propensity using specific traffic speed conditions.
    Abdel-Aty M, Pande A.
    J Safety Res; 2005; 36(1):97-108. PubMed ID: 15752487
    [Abstract] [Full Text] [Related]

  • 2.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 3.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 4.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 5. Modeling crash-flow-density and crash-flow-V/C ratio relationships for rural and urban freeway segments.
    Lord D, Manar A, Vizioli A.
    Accid Anal Prev; 2005 Jan; 37(1):185-99. PubMed ID: 15607290
    [Abstract] [Full Text] [Related]

  • 6.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 7. Crash data analysis: collective vs. individual crash level approach.
    Abdel-Aty M, Pande A.
    J Safety Res; 2007 Jan; 38(5):581-7. PubMed ID: 18023643
    [Abstract] [Full Text] [Related]

  • 8. Validating a driving simulator using surrogate safety measures.
    Yan X, Abdel-Aty M, Radwan E, Wang X, Chilakapati P.
    Accid Anal Prev; 2008 Jan; 40(1):274-88. PubMed ID: 18215559
    [Abstract] [Full Text] [Related]

  • 9. Presence of passengers: does it increase or reduce driver's crash potential?
    Lee C, Abdel-Aty M.
    Accid Anal Prev; 2008 Sep; 40(5):1703-12. PubMed ID: 18760099
    [Abstract] [Full Text] [Related]

  • 10. On the nature of over-dispersion in motor vehicle crash prediction models.
    Mitra S, Washington S.
    Accid Anal Prev; 2007 May; 39(3):459-68. PubMed ID: 17161374
    [Abstract] [Full Text] [Related]

  • 11.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 12.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 13.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 14.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 15. Bayesian estimation of hourly exposure functions by crash type and time of day.
    Qin X, Ivan JN, Ravishanker N, Liu J, Tepas D.
    Accid Anal Prev; 2006 Nov; 38(6):1071-80. PubMed ID: 16782038
    [Abstract] [Full Text] [Related]

  • 16. Using hierarchical Bayesian binary probit models to analyze crash injury severity on high speed facilities with real-time traffic data.
    Yu R, Abdel-Aty M.
    Accid Anal Prev; 2014 Jan; 62():161-7. PubMed ID: 24172082
    [Abstract] [Full Text] [Related]

  • 17. Application of a Rule-Based Approach in Real-Time Crash Risk Prediction Model Development Using Loop Detector Data.
    Pirdavani A, De Pauw E, Brijs T, Daniels S, Magis M, Bellemans T, Wets G.
    Traffic Inj Prev; 2015 Jan; 16(8):786-91. PubMed ID: 25793926
    [Abstract] [Full Text] [Related]

  • 18. Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects.
    Xie M, Cheng W, Gill GS, Zhou J, Jia X, Choi S.
    Traffic Inj Prev; 2018 Feb 17; 19(2):207-213. PubMed ID: 28837362
    [Abstract] [Full Text] [Related]

  • 19.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 20.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 13.