Join us on Tuesday April 23 at 3PM in Rocky 300 for the second of two Henry Seely White Lectures delivered by Professor Bhramar Mukherjee, University of Michigan.

Note:  This is the second of two lectures in the Henry Seely White Lecture Series. The first lecture is on Monday April 22 at 5PM.

Title: Analysis of “Big” Real-World Health Care Data: Promises and Perils

Abstract: Using administrative patient-care data such as Electronic Health Records and medical/Pharmaceutical claims for population-based scientific research have become increasingly common. With vast sample sizes leading to very small standard errors, researchers need to pay more attention to potential biases in the estimates of association parameters of interest, specifically to biases that do not diminish with increasing sample size. Of these multiple sources of biases, in this talk, we primarily focus on understanding selection bias. We present an analytical framework for understanding selection bias and arriving at bias-reduced inference using external data from a target population. We illustrate our methods via case-studies in cancer and COVID-19. We try to highlight that sampling and study design are at the heart of analysis of big data. This is joint work with many students and colleagues at the University of Michigan School of Public Health.