STATISTICS COLLOQUIUM
Bhramar Mukherjee
Professor and Chair of Biostatistics
School of Public Heath
University of Michigan
Handling Sampling and Selection Bias in Phenome-wide Association Studies
Abstract
In this talk I will discuss statistical challenges and opportunities with joint analysis of electronic
health records and genomic data through "Phenome-Wide Association Studies (PheWAS)". I will
posit a modeling framework that helps us to understand the effect of both selection bias and
outcome misclassification in assessing genetic associations across the medical phenome. I will
use data from the UK Biobank and the Michigan Genomics Initiative, a longitudinal biorepository
at Michigan Medicine, launched in 2012 to illustrate the analytic framework. The examples
illustrate that understanding sampling design and selection bias matters for big data, and are at
the heart of doing good science with data. This is joint work with Lauren Beesley and Lars Fritsche
at the University of Michigan.
DATE: Wednesday, April 17, 2019
TIME: 4:00 pm
PLACE: Philip E. Austin Bldg., Rm. 108
Coffee will be served at 3:30 in the Noether Lounge (AUST 326)
For more information, contact: Tracy Burke at tracy.burke@uconn.edu