Probabilistic Record Linkage for Computational Demography, Abraham Flaxman, UW
Zack Almquist Professional Development
Title: Probabilistic Record Linkage for Computational Demography
Abstract: Data linked between multiple sources can be a powerful resource for population health and social research more broadly. But large databases rarely include a “primary key” on which to linking, and probabilistic record linkage (PRL) is a computational technique that can identify which entities are likely to be the same in databases without a common unique identified. In this meeting, I’ll offer some overview of what PRL has been used for in demography and population health and how it works. And then we’ll work together to brainstorm what we might link and what we might learn from linked data, as well as what pitfalls we should avoid.
Bio: Abraham Flaxman, PhD, is Associate Professor of Health Metrics Science and Global Health at the Institute for Health Metrics and Evaluation (IHME) at the University of Washington. He is currently leading the development of new methods for cost effective analysis with microsimulation and is engaged in methodological and operational research on verbal autopsy. Dr. Flaxman is starting a new project to update record linkage software for the US Census Bureau.