As a post-bacc at the Jackson Laboratory, my main research focus has been mediation analysis. A primary objective of mediation analysis is to infer the relationship among three variables, and it is becoming increasingly common to use it with multi-omics data to understand causal pathways underlying a phenotype. Mediation analysis is often done without distinguishing variation due to causal relationships from variation due to measurement noise, which can have a profound effect on inferences. In this analysis, we address the impact of applying a standard mediation analysis to data as if it is measured without error and identify ways to diagnose the accuracy of results from real data.
In collaboration with the Valdar lab at UNC, we developed a Bayesian model selection approach to mediation analysis implemented in the bmediatR R package. This approach allows for flexibility in both data inputs and potential inferences and uses conjugate priors to increase efficiency. I am currently extending the framework to allow for the inference of moderated mediation.
In collaboration with the Valdar lab at UNC, we developed a Bayesian model selection approach to mediation analysis implemented in the bmediatR R package. This approach allows for flexibility in both data inputs and potential inferences and uses conjugate priors to increase efficiency. I am currently extending the framework to allow for the inference of moderated mediation.