AbstractStandard analysis of matched-pair cohort data requires information only from pairs in which at least one had the study outcome. This can be useful in traffic fatality studies of characteristics that can vary among vehicle occupants, such as seat belt use, as crash databases often lack information about vehicles in which all survived. However, matching crash victims who were in the same vehicle does not necessarily eliminate confounding by vehicle or crash related factors, because the matched occupants must be in different seat positions. This paper reviews three methods for estimating relative risks in matched-pair crash data. The first, Mantel–Haenszel stratified methods, may produce biased estimates if seat position is associated with the outcome. The second, the double-pair comparison method, was designed to deal with confounding by seat position. If the effects of seat position vary according to some vehicle or crash characteristic which is associated with the study exposure, adjustment for this characteristic may be needed to produce unbiased estimates. Third, conditional Poisson regression and Cox proportional hazards regression can produce unbiased estimates, but may require model interaction terms between seat position and vehicle or crash characteristics. This paper reviews some of the strengths and limitations of each of these methods, and illustrates their use in simulated and real crash data.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Matched-pair cohort methods in traffic crash research


    Contributors:

    Published in:

    Publication date :

    2001-10-22


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Matched-pair cohort methods in traffic crash research

    Cummings, Peter | Online Contents | 2003



    Estimating seat belt effectiveness using matched-pair cohort methods

    Cummings, Peter / Wells, James D. / Rivara, Frederick P. | Elsevier | 2001


    REROUTING TRAFFIC POST VEHICLE CRASH

    STÄHLIN ULRICH / MARLETT BRIAN J / CLELLAND MITCHELL E et al. | European Patent Office | 2023

    Free access

    Utilizing Ensemble Learning Methods in Real-Time Traffic Crash Prediction

    Xue, Mengdi / Huang, Jie / Gao, Zhen et al. | ASCE | 2018