Epidemiologic Methods Research Award

The Marshall Joffe Epidemiologic Methods Research Award is awarded annually to recognize outstanding accomplishments in developing, adapting, or translating a methodological concept or approach whose usefulness has been demonstrated through fruitful adoption in epidemiology, including applied population health research settings. The awarded work would typically be embodied by a set of methodologic and/or applied papers, and may additionally include other scholarly work (e.g., a book) or software, tutorials or other tools which developing, translating, or extending a quantitative method.

Eligibility

Open for candidates at any career level who are members of SER.

Requirements

Preliminary nominations consist of (1) a comprehensive list of the nominee\’s papers, software and/or tutorials related to the method, (2) up to three article full text PDFs, and (3) a brief letter (<=2 pages) summarizing the nominee’s body of methodological work or of a specific method to epidemiologic research, and how the three full text papers are illustrative of the nominee’s methodologic contributions to the field of epidemiology or of the nominees essential contributions to a specific method. Please submit these as a single combined file.

Final candidates will be selected from preliminary nomination packets. We will solicit additional letters of support (<=2 pages per letter) for these candidates.

Award Details

The award winner will be awarded $5,000 and be invited to give a presentation at the Annual Meeting.

Multiple nominations do not increase the likelihood of being awarded. In the case of multiple nominations for a single candidate, submitters will be contacted to coordinate a joint nomination.

Dr. Joffe has been widely recognized as a leader in statistical science among his peers nationally and internationally. In particular, he has earned international recognition for his methodological work in causal inference. His work in this area has involved several complementary components, including statistical method development and conceptual development.

Perelman School of Medicine University of Pennsylvania

Previous Award Winners

2025

Timothy Lash
Timothy L. Lash, DSc, MPH, is Rollins Professor and Chair of the Department of Epidemiology at the Rollins School of Public Health. Dr. Lash serves as Associate Director of Population Sciences at Winship Cancer Institute of Emory University. In this role, he directs the integration and strategic growth of population science-based research throughout Winship and its research programs.
Dr. Lash is a member of Winship’s Cancer Prevention and Control Research Program. He serves as chairperson of the Cancer, Heart and Sleep Epidemiology B Study Section, Center for Scientific Review at the National Institutes of Health (NIH). He also holds memberships with the American Association of Cancer Research and the Society for Epidemiologic Research.
Dr. Lash is Honorary Professor of Cancer Epidemiology in the Department of Clinical Epidemiology at Aarhus University in Aarhus, Denmark. He was also President of the Society for Epidemiologic Research (SER) for the 2014-2015 term.

2024

Eric Tchetgen Tchetgen
As University Professor, Dr. Tchetgen Tchetgen holds joint primary appointments in the Department of Statistics and Data Science at The Wharton School and in the Department of Biostatistics, Epidemiology and Informatics at the Perelman School of Medicine. He received his BS in Applied Mathematics from Yale University in 1999 and his PhD in Statistics from Harvard University in 2006. After serving on the faculty of the Harvard School of Public Health for ten years, he joined The Wharton School in 2018 as the Luddy Family President’s Distinguished Professor and Professor of Statistics and Data Science.
Dr. Tchetgen Tchetgen is a world leader in the field of causal inference. In recognition of his ground-breaking research, he was a co-recipient of the 2022 Rousseeuw Prize awarded to Causal Inference for pioneering research on causal inference with real-world applications in medicine and public health. He is co-director of the Center for Causal Inference at Penn.

2023

George Davey Smith

2022

Stephen Cole
Stephen R. Cole works to build robust, accurate, and impactful knowledge at the intersection of epidemiology and statistics. He is interested in study designs and analyses that accurately estimate parameters of central interest to population-health scientists. These study designs include randomized experiments and observational studies. In particular, he is interested in infectious diseases, primarily HIV, and birth outcomes.

2021

Malcolm Maclure
“I am a ‘case of crossover,’ oscillating between academe and government, trying to combine the active skepticism of Tom and Iain Chalmers with the skeptical activism of Dr. Bernard Lown, co-founder of International Physicians for Prevention of Nuclear War. While I was an Assistant Professor at Harvard School of Public Health, helping Dr. Lown with a peace project (1986-88), I met another IPPNW activist, cardiologist James Muller, who invited me to help him design what became the Myocardial Infarction Onset Study.
My doctoral work, a case-control study of kidney cancer, had sensitized me to selection bias in control groups. So, for the Onset Study, I agonized over every suggested control group until I hit upon using afternoon heart attacks as controls for morning cases, and vice versa. Gradually I realized cases could be their own controls. Emboldened by teaching a course using Sander Greenland’s Evolution of Epidemiologic Ideas, I named it the case-crossover design, hoping it might be useful to others. After publishing the paper and wearily completing revision #23 of the interview form, I left the Onset Study to Murray Mittleman who solved its logistics challenges and developed theory on control sampling strategies for case-crossover studies.

2020

Elisabeth Stuart
Elizabeth A. Stuart is a professor of mental health, biostatistics, and health policy and management in the Johns Hopkins Bloomberg School of Public Health, where she is also Associate Dean for Education. Her research involves causal inference and missing data methods and their application to mental health, substance use, education, and public health more broadly. She has done influential work in propensity score methods for non-experimental studies, and in methods for assessing and enhancing the external validity (generalizability) of randomized trials to target populations. She received her AB from Smith College and her Ph.D. in statistics from Harvard University. After working for two years as a researcher at Mathematica Policy Research, she joined the Johns Hopkins faculty in 2006.
She is a Fellow of the American Statistical Association, chair of the SERV (Mental health services research) NIH study section, and recent recipient of the Gertrude M. Cox Award from the Washington Statistical Society and RTI International. She is also heavily involved with the Bloomberg American Health Initiative, for which she leads the evidence workgroup.

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