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    The Application of Simulation to Quantifying the Influence of Bias in Perinatal Epidemiology

    Dunne J 2023 Public.pdf (6.456Mb)
    Access Status
    Open access
    Authors
    Dunne, Jennifer
    Date
    2023
    Supervisor
    Gavin Pereira
    Gizachew Tessema
    Type
    Thesis
    Award
    PhD
    
    Metadata
    Show full item record
    Faculty
    Health Sciences
    School
    Curtin School of Population Health
    URI
    http://hdl.handle.net/20.500.11937/93624
    Collection
    • Curtin Theses
    Abstract

    Perinatal aetiological associations derived from observational data are susceptible to various types of bias. This thesis demonstrated the application of simulation methodologies to quantify the influence of bias in perinatal epidemiology through a series of simulation studies which quantified the magnitude and direction of bias mechanisms. A framework to guide epidemiologists in the development, implementation and reporting of simulation studies to quantify bias was developed. Simulation is a potent tool to the quantification of bias.

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