Marshall Joffe's Contributions to Causal Inference, Biostatistics and Epidemiology

Author:

Isenberg Dane1,Kennedy Edward H2,Landis J Richard1,Mitra Nandita1,Robins James M345,Roy Jason6,Stephens-Shields Alisa J1,Yang Wei1,Small Dylan S7

Affiliation:

1. University of Pennsylvania Department of Biostatistics, Epidemiology and Informatics, , Philadelphia, Pennsylvania, United States

2. Carnegie Mellon University Department of Statistics and Data Science, , Pittsburgh, Pennsylvania, United States

3. Department of Biostatistics, Harvard T. H. Chan School of Public Health , Boston, Massachusetts, United States

4. Department of Epidemiology, Harvard T. H. Chan School of Public Health , Boston, Massachusetts, United States

5. CAUSALab, Harvard T. H. Chan School of Public Health , Boston, Massachusetts, United States

6. Rutgers University Department of Biostatistics and Epidemiology, , Piscataway, New Jersey, United States

7. University of Pennsylvania Department of Statistics and Data Science, The Wharton School, , Philadelphia, Pennsylvania, United States

Abstract

Abstract We pay tribute to Marshall Joffe, PhD, and his substantial contributions to the field of causal inference with focus in biostatistics and epidemiology. By compiling narratives written by us, his colleagues, we not only present highlights of Marshall’s research and their significance for causal inference but also offer a portrayal of Marshall’s personal accomplishments and character. Our discussion of Marshall’s research notably includes (but is not limited to) handling of post-treatment variables such as noncompliance, employing G-estimation for treatment effects on failure-time outcomes, estimating effects of time-varying exposures subject to time-varying confounding, and developing a causal framework for case-control studies. We also provide a description of some of Marshall’s unpublished work, which is accompanied by a bonus anecdote. We discuss future research directions related to Marshall’s research. While Marshall’s impact in causal inference and the world outside of it cannot be wholly captured by our words, we hope nonetheless to present some of what he has done for our field and what he has meant to us and to his loved ones.

Publisher

Oxford University Press (OUP)

Subject

Epidemiology

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