Difference-in-Differences with Multilevel Data
Last updated on
May 1, 2025

Difference-in-differences compares changes in longitudinal outcome trajectories from before and after some exposure between exposed and unexposed units. Oftentimes, in health policy application, data is sourced from existing administrative databases (e.g., health insurance claims) that have multilevel structures. This work investigates practical analytic challenges and opportunities that arise because of that multilevel data structure.

Nicholas J. Seewald
Assistant Professor of Biostatistics
Assistant Professor of Biostatistics at the University of Pennsyvlania Perelman School of Medicine
Publications
Events
Health policy researchers often have questions about the effects of state policy on individual-level outcomes collected over multiple …
May 16, 2024 3:30 PM — 3:45 PM
Seattle, WA
Health policy researchers often have questions about the effects of a policy implemented at some cluster-level unit, e.g., states, …
Dec 17, 2023 1:50 PM — 3:30 PM
Berlin, Germany
Health policy researchers often have questions about the effects of state policy on individual-level outcomes collected over multiple …
May 24, 2023 1:45 PM — 3:00 PM
Austin, TX, USA
A contributed presentation at JSM 2022. Part of a session on “Statistical Methods in Policy Evaluation: From COVID-19 to Medical Cannabis–Related Policy”.
Jan 10, 2023 5:15 PM — 5:30 PM
Scottsdale, AZ, USA
A contributed presentation at JSM 2022. Part of a session on “Statistical Methods in Policy Evaluation: From COVID-19 to Medical Cannabis–Related Policy”.
Aug 8, 2022 3:20 PM — 3:35 PM
Washington, DC, USA
A poster at AcademyHealth Annual Research Meeting 2022. I describe a simulation study investigating performance of difference-in-differences methods using hierarchical data for state-level health policy evaluation.
Jun 6, 2022 3:00 PM — May 18, 2022 4:00 PM
Washington, DC, USA