Online Program Home
  My Program

Abstract Details

Activity Number: 292 - SPEED: Statistics in Epidemiology
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract #324141 View Presentation
Title: Contextualizing Sensitivity Analysis in Observational Studies: Calculating Bias Factors for Known Covariates
Author(s): Lucy D'Agostino McGowan* and Robert A Greevy, Jr
Companies: and Vanderbilt University
Keywords: Sensitivity ; Unmeasured confounding ; Observational Studies ; Biostatistics ; Design sensitivity ; Shiny application

The strength of evidence provided by epidemiological and observational studies is inherently limited by the potential for unmeasured confounding. While methods exist to quantify the potential effect of a specified unmeasured confounder, these methods should be anchored and contextualized within each study. We put forward a method for merging sensitivity to unmeasured confounding analyses with the impacts of the observed covariates. We graphically display what we call the observed bias factors with the tipping point sensitivity analysis. We illustrate the method under various study designs and provide an application created to simplify the implementation of this methodology.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

Copyright © American Statistical Association