Quantitative Bias Analysis in Regulatory Settings

Project Title Quantitative Bias Analysis in Regulatory Settings
Friday, June 10, 2016

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.

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


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

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