Department Highlights
Three New Faculty Members to Join the Department in August
Xingche Guo (Statistical Machine Learning), Trevor Harris (cluster hire in Artificial Intelligence/Machine Learning: Understanding and Addressing Natural and Climate Change-Related Disasters), and Wenrui Li (Modern Statistical Computing) will start as assistant professors of statistics this fall.
Two New Undergraduate Degrees in Data Science
Learn more about the Department's new Bachelor of Science (BS) in Statistical Data Science.
Upcoming Local Conferences
Learn more about a range of upcoming academic conferences organized by UConn statistics department faculty
News and Announcements
Upcoming Events
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Apr
24
Robert W. Makuch Distinguished Lecture in Biostatistics: Roderick J. Little, University of Michigan 4:00pm
Robert W. Makuch Distinguished Lecture in Biostatistics: Roderick J. Little, University of Michigan
Wednesday, April 24th, 2024
04:00 PM - 05:00 PM
Some Reflections on Rosenbaum and Rubin’s Propensity Score Paper
Presented by Roderick J. Little
Richard D. Remington Distinguished University Professor of Biostatistics
Department of Biostatistics, University of MichiganWednesday, April 24, 2024
4:00 PM-5:00 PM ET
AUST 163
Webex Meeting Link
Coffee will be served at 3:30 pm in the Noether Lounge (AUST 326)Rosenbaum and Rubin’s paper is highly cited because the basic idea is simple and insightful, and it has applications to important practical problems in treatment comparisons with observational data, and selection bias and nonresponse in surveys. I discuss several issues related to the method, including use of the propensity score for weighting or prediction, and two robust methods that use the propensity score as a covariate and can be more efficient that weighting when the weights are highly variable, namely Penalized Spline of Propensity Prediction (PSPP) and Penalized Spline of Propensity for Treatment Comparisons (PENCOMP). Approaches to addressing highly variable weights are discussed, including omitting variables in the propensity model that are unrelated to outcomes, and redefining the estimand.
Keywords: confounding by indication, nonresponse modeling, penalized spline of propensity, robust causal inference.
Speaker Bio:
Roderick J. Little is Richard D. Remington Distinguished University Professor of Biostatistics at the University of Michigan, where he also holds appointments in the Department of Statistics and the Institute for Social Research. He chaired the Biostatistics Department at Michigan for 11 years. He has over 250 publications, notably on methods for the analysis of data with missing values and model-based survey inference, and the application of statistics to diverse scientific areas, including medicine, demography, economics, psychiatry, aging and the environment. Little is an elected member of the International Statistical Institute, a Fellow of the American Statistical Association and the American Academy of Arts and Sciences, and a member of the National Academy of Medicine. In 2005, Little was awarded the American Statistical Association’s Wilks Medal for research contributions, and he gave the President’s Invited Address at the Joint Statistical Meetings. He was the COPSS Fisher Lecturer at the 2012 Joint Statistics Meetings.
Robert Makuch is a Professor in the Department of Biostatistics at the Yale School of Public Health and Director of the Regulatory Affairs Track. A graduate of the University of Connecticut (BA), University of Washington (MA – mathematics), and Yale University (MPhil, PhD), Professor Makuch worked at the National Cancer Institute (NCI) and the World Health Organization’s International Agency for Research on Cancer early in his career. He also worked for six months at the National Cancer Research Center in Tokyo, Japan.
He also was heavily involved in HIV research from the mid 80’s through the early-mid 90’s. He participated on the data monitoring committee for the original AZT vs. placebo randomized clinical trial in AIDS patients, and served on numerous committees for the NCI and the National Institute of Allergy and Infectious Diseases. He also worked closely with the Food and Drug Administration (FDA), developing and implementing more than 200 HIV studies. He also served as a Special Government Employee (SGE) to the FDA. He returned to Yale in 1986, and has worked extensively on methodologic issues in clinical trials and large population-based studies since. Another area of current interest involves detection of rare adverse drug events, especially in the post-marketing environment.
These areas of methodologic research evolved as a result of his continued interest (since the mid 1980s) in regulatory affairs science. In addition, Makuch developed a regulatory affairs track at YSPH for graduate and post-doctoral level students, and over the past 10 years has been the leader of more than 25 training programs for senior delegations of the Chinese Food and Drug Administration. His areas of medical application include cancer, HIV, arthritis, and cardiovascular disease.
In 2003, Makuch received the American Statistical Association Fellow Award for his numerous contributions to the field. In 2008, Makuch was received a Distinguished Alumni Award from the University of Connecticut. In 2012, Makuch was nominated to serve on the University of Connecticut Dean’s Advisory Board for the College of Liberal Arts and Sciences. He also has been a decades-long member of Phi Beta Kappa. He also developed a 5-year biostatistics training program in Japan, in collaboration with the Japanese government. His primary research interests continue to be methodologic issues in the design, conduct, analysis, and interpretation of clinical and large-population/epidemiologic studies. Design and sample size considerations for Phase IV studies is another active research area, in which a new class of hybrid designs has been proposed for scientific and regulatory purposes to detect rare adverse events.
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May
9
The Stat4Onc Annual Symposium All Day
The Stat4Onc Annual Symposium
Thursday, May 9th, 2024
All Day
The Stat4Onc Annual Symposium is a venue for interdisciplinary dialogue among clinical and quantitative scientists about cancer clinical trials. We seek participation by researchers from academia, industry, and regulatory agencies to share new research, discuss novel ideas, ask questions, and provide solutions for cancer clinical trials. Oncologists and statisticians can exchange views on trial design and conduct, drug development, and translation to patient care. Topics for this symposium include training for new generation of statisticians and clinicians, translational and precision oncology, master protocols, pediatric oncology research and drug development, populational cancer research, biomarkers and subgroups, real world data/evidence, and engagement of under-representative population in oncology research.Please visit the event’s homepage for this information at https://stat4onc.org/events/stat4onc2024/. -
May
21
New England Statistics Symposium All Day
New England Statistics Symposium
Tuesday, May 21st, 2024
All Day
The symposium has been bringing together statisticians from all over New England and beyond to a central location to share research, discuss emerging issues in the field, and network with colleagues since it was first started at UConn in 1987.Please visit the event’s homepage for this information at
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