Quantitative Bias Analysis in Regulatory Settings

    Basic Details
    Date
    Friday, June 10, 2016
    Type
    Publication
    Description

    Systematic errors can lead to inaccurate inferences, so it is critical to develop analytic methods that quantify uncertainty and bias and ensure that these methods are implemented when needed. “Quantitative bias analysis” is an overarching term for methods that estimate quantitatively the direction, magnitude, and uncertainty associated with systematic errors influencing measures of associations.

    Author(s)

    Timothy L. Lash DSc, MPH; Matthew P. Fox DSc, MPH; Darryl Cooney MStat; Yun Lu PhD, MS; Richard A. Forshee PhD

    Corresponding Author

    T. L. Lash, Department of Epidemiology, Rollins School of Public Health, 1518 Clifton Rd NE, 1518-002-3BB, Atlanta, GA 30322, USA. Email: tlash@emory.edu