Sensitivity analysis for mediation analysis with partial information from publicly available sources

Oregon Convention Center 

Our original work was motivated by the question of whether and to what extent well-established risk factors mediate the racial disparity observed for colorectal cancer incidence in the US. Typical mediation analysis examines the relationships between exposure, a mediator, and an outcome but requires access to a single complete dataset containing all three variables. However, because population-based studies include only a few participants from racial minority groups, these approaches have limited utility here. For this purpose, I developed novel methods to integrate several data sets with partial information for mediation analysis that accommodates complex survey and registry data and allows for multiple mediators. I then apply our method to data from US cancer registries, a US population-representative survey, and summary-level odds-ratio estimates of selected CRC risk factors from a case-control study. In this presentation, I will discuss several approaches to evaluate the robustness of results to violation of model assumptions.

sensitivity analysis

data integration

summary level information,

survey sampling

registry data 

Biometrics Section