The binary logistic model has been extensively used to analyze traffic collision and injury data where the outcome of interest has two categories. However, the assumption of a symmetric distribution may not be a desirable property in some cases, especially when there is a significant imbalance in the two categories of outcome. This study compares the standard binary logistic model with the skewed logistic model in two cases in which the symmetry assumption is violated in one but not the other case. The differences in the estimates, and thus the marginal effects obtained, are significant when the assumption of symmetry is violated.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Comparison of the binary logistic and skewed logistic (Scobit) models of injury severity in motor vehicle collisions


    Beteiligte:
    Tay, Richard (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2016




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    44.80 / 55.84 Straßenverkehr / 55.24 / 44.80 Unfallmedizin, Notfallmedizin / 55.84 / 55.24 Fahrzeugführung, Fahrtechnik



    A Logistic Regression Analysis of Traumatic Brain Injury Risk in Motor Vehicle Collisions

    Beaver, M. C. / Association for the Advancement of Automotive Medicine | British Library Conference Proceedings | 1996



    Analysis of Severity of Young Driver Crashes: Sequential Binary Logistic Regression Modeling

    Dissanayake, Sunanda / Lu, John | Transportation Research Record | 2002



    Analysis of Severity of Young Driver Crashes: Sequential Binary Logistic Regression Modeling

    Dissanayake, S. / Lu, J. / Transportation Research Board | British Library Conference Proceedings | 2002